[{"data":1,"prerenderedAt":4},["ShallowReactive",2],{"guide-state-of-the-art-analyses":3},"\u003Ch2 id=\"introduction\">1 Introduction\u003C/h2>\n\u003Cdiv id=\"sec-introduction\">\u003C/div>\n\u003Cdiv class=\"multicols\">\n  \u003Cp>\u003Cspan>2\u003C/span>\u003C/p>\n  \u003Cp>\n    State of the Art (SOTA) analyses are the backbone of any technical documentation. Don’t believe\n    it? Let’s put it to the test.\n  \u003C/p>\n  \u003Cp>\n    Before developing your device, you likely assessed what the medical field needs—congratulations,\n    that’s a SOTA analysis. To market your device competitively, you probably researched what other\n    manufacturers are doing—again, SOTA. Struggling to define acceptance criteria for your clinical\n    evaluation? That’s because you need a solid SOTA foundation. Determining the clinical benefit of\n    your device compared to existing treatments? SOTA. Defining meaningful endpoints for clinical\n    studies? SOTA. Identifying device harms, risks, and probabilities for risk management? You\n    guessed it—SOTA. The same applies to Post-Market Surveillance (PMS): if you want to interpret\n    incident data beyond just “\u003Cem>3 incidents per 1,000 devices—sounds small\u003C/em>,” you need SOTA\n    insights at your fingertips. Which standards are relevant for your device or your company? SOTA\n    analysis. And what about the applicable guidance? SOTA, SOTA, SOTA.\n  \u003C/p>\n  \u003Cp>\n    The above examples should make clear that SOTA is not just for clinical evaluation. It is\n    essential for research and development, marketing, sales, risk management, post-market\n    surveillance, and even QMS.\n  \u003C/p>\n  \u003Cp>\n    Yet, if SOTA is so important, why do so many companies get it wrong? Because, currently, there\n    is no proper guide on how to do it right.\n  \u003C/p>\n  \u003Cp>This document is here to change that.\u003C/p>\n  \u003Cp>\n    While the identification of SOTA has gained particular relevance in Europe with the introduction\n    of \u003Ca href=\"#ref-mdr\">MDR\u003C/a>, the information in this document applies to certification\n    worldwide, not just in the EU. Let’s start.\n  \u003C/p>\n  \u003Cdiv class=\"warningbox\">\n    \u003Cdiv class=\"boxtitle\" id=\"box-1\">\n      \u003Cp>Box 1: Search, review, meta-analysis, umbrella review\u003C/p>\n    \u003C/div>\n    \u003Cdiv id=\"box-searchvsreview\">\u003C/div>\n    \u003Cp>The terms \"systematic search\" and \"systematic review\" are not synonymous.\u003C/p>\n    \u003Cp>\n      A systematic review begins with a systematic search but also includes critical appraisal and a\n      structured synthesis of the evidence, either qualitatively or quantitatively.\n    \u003C/p>\n    \u003Cp>Systematic reviews that synthesize results quantitatively are called meta-analyses.\u003C/p>\n    \u003Cp>Finally, umbrella reviews synthesize multiple systematic reviews and meta-analyses.\u003C/p>\n  \u003C/div>\n  \u003Ch3 id=\"making-clarity-on-sota\">1.1 Making clarity on SOTA\u003C/h3>\n  \u003Cp>\n    Let’s begin our journey into SOTA analyses by addressing some of the most common misconceptions.\n    The confusion often starts with the terminology itself. Many companies refer to SOTA analyses as\n    \u003Cem>the\u003C/em> literature search, a phrasing that reflects two key misunderstandings.\n  \u003C/p>\n  \u003Cp>\n    First, most SOTA activities are not merely literature searches. Instead, they take the form of\n    systematic reviews, meta-analyses, or umbrella reviews (see Box\n    \u003Ca href=\"#box-searchvsreview\">1\u003C/a> for an explanation of these terms). This means that SOTA\n    analyses go beyond simply retrieving literature—they involve a structured synthesis, either\n    textual or numerical.\n  \u003C/p>\n  \u003Cp>\n    Second, a SOTA analysis is not a single, monolithic process. Figure\n    \u003Ca href=\"#fig-sota-structure\">1.1\u003C/a> illustrates Typical list of systematic searches and\n    reviews required to establish the state of the art for a medical device. The analysis begins\n    with a systematic review to establish the medical background (the focus of this document). This\n    review is the topic of this document.\n  \u003C/p>\n  \u003Cp>\n    The analysis then proceeds with meta-analyses to evaluate the performance and safety of medical\n    alternatives (a dedicated guide on this will follow soon), which typically provides the criteria\n    for the acceptance of benefit and performance in the clinical evaluation.\n  \u003C/p>\n  \u003Cp>\n    Additionally, SOTA analyses extend beyond clinical evidence, and include the identification of\n    medical devices, applicable regulations, standards, and guidance. We will address these\n    additional searches and reviews in the upcoming articles.\n  \u003C/p>\n  \u003Cp>\n    Another major misconception that affects the way companies conduct SOTA analyses—and ultimately\n    their effectiveness—is the belief that SOTA analyses should be planned within the CEP. This is a\n    common mistake, where searches are structured in the CEP and merely summarized in the CER. When\n    done this way, the foundation for developing the CDP is missing.\n  \u003C/p>\n  \u003Cp>\n    For example, without a proper SOTA analysis, it is impossible to define \"\u003Cem\n      >an indicative list and specification of parameters to be used to determine, based on the\n      state of the art in medicine, the acceptability of the benefit-risk ratio for the various\n      indications and for the intended purpose or purposes of the device\u003C/em\n    >,\" as required by \u003Ca href=\"#ref-mdr\">MDR\u003C/a> Annex XIV for the CEP.\n  \u003C/p>\n  \u003Cp>\n    In reality, the SOTA analysis serves as underpinning of a wide range of regulatory processes,\n    including state of the art analyses, research and development, risk management, and post-market\n    surveillance. It should, therefore, be planned before these processes start.\n  \u003C/p>\n  \u003Cfigure>\n    \u003Cimg src=\"/guides/state-of-the-art-analyses/searches.png\" />\n    \u003Cdiv id=\"fig-sota-structure\">\u003C/div>\n    \u003Cfigcaption>\n      Figure 1.1: Typical list of systematic searches and reviews required to establish the state of\n      the art for a medical device.\n    \u003C/figcaption>\n  \u003C/figure>\n  \u003Cp>\n    One notable—albeit very rare—exception is when the medical field cannot be identified through\n    medical literature alone. In such cases, manufacturers would have to plan investigations to\n    establish the clinical background within the CEP.\n  \u003C/p>\n  \u003Cp>\n    A final note: SOTA analyses are not the only systematic searches and reviews conducted in the\n    pre-market phase (i.e., before receiving market access). Some systematic searches belong to PMCF\n    and are carried out before certification, even though they are technically part of PMS. Figure\n    \u003Ca href=\"#fig-pms-structure\">1.2\u003C/a> lists these searches.\n  \u003C/p>\n  \u003Cp>\n    Before continuing, we encourage you to read about post-market searches, which are detailed in\n    our guidance \u003Ca href=\"#ref-post-market-searches\">POST-MARKET SEARCHES\u003C/a>. Medical background\n    SOTA analyses are, in many ways, mirror approaches to post-market searches. Comparing the two\n    frameworks helps understanding how to take decisions on planning, executing, documenting, and\n    updating these searches. That is also the reason why at the end of chapter\n    \u003Ca href=\"#cha-plan\">2\u003C/a>, we provide a side-by-side comparison of medical background SOTA\n    analyses and post-market searches.\n  \u003C/p>\n  \u003Cfigure>\n    \u003Cimg src=\"/guides/state-of-the-art-analyses/searches2.png\" />\n    \u003Cdiv id=\"fig-pms-structure\">\u003C/div>\n    \u003Cfigcaption>\n      Figure 1.2: Typical list of post-market searches and reviews that should be conducted in\n      pre-market.\n    \u003C/figcaption>\n  \u003C/figure>\n  \u003Cp>\n    You might ask: \"\u003Cem>How do I know whether a search or review belongs to SOTA or PMS?\u003C/em>\". For\n    example, consider a SOTA search on similar devices and a post-market search on the same\n    subject—how do you differentiate between them?\n  \u003C/p>\n  \u003Cp>\n    A simple rule applies: SOTA searches and reviews never include a specific device trade name in\n    their queries. If your search is focused on a particular device, it is almost certainly a\n    post-market search.\n  \u003C/p>\n  \u003Cp>\n    There is only one exception: when a specific device brand represents the state of the art in the\n    medical field. That, however, is extremely rare.\n  \u003C/p>\n  \u003Ch3 id=\"medical-background\">1.2 Medical background\u003C/h3>\n  \u003Cp>\n    Now, let’s get to the core of the matter. This is where things become a bit more complex, but we\n    can break it down step by step.\n  \u003C/p>\n  \u003Cp>\n    This guide covers the first type of analysis in Figure \u003Ca href=\"#fig-sota-structure\">1.1\u003C/a>:\n    the medical background analysis. This analysis helps clinical reviewers understand the broader\n    medical context in which your device operates, including its role, alternatives, and clinical\n    relevance.\n  \u003C/p>\n  \u003Cp>There are two types of medical background analyses:\u003C/p>\n  \u003Cul>\n    \u003Cli>\u003Cp>condition-focused and\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>procedure-focused.\u003C/p>\u003C/li>\n  \u003C/ul>\n  \u003Cp>The first type—condition-focused—is aimed at device that are aimed at specific conditions.\u003C/p>\n  \u003Cp>\n    The term \"condition\" is not explicitly defined in regulatory guidance. However, it is widely\n    used in medicine to describe a broad category of health issues, including diseases, injuries,\n    disabilities, pathological processes.\n  \u003C/p>\n  \u003Cp>\n    The second option applies when your device is intended to assist, enable, or perform a medical\n    procedure, regardless of the underlying condition.\n  \u003C/p>\n  \u003Cp>\n    Determining which type is needed for your device depends on whether its indication is\n    condition-based or procedure-based. In version 3 of our guide on creating an intended\n    purpose–see \u003Ca href=\"#ref-intended-purpose\">INTENDED PURPOSE\u003C/a>—we cover this distinction in\n    detail. We strongly encourage reading that guide before proceeding.\n  \u003C/p>\n  \u003Cp>\n    A condition-based medical background SOTA analysis systematically examines the current state of\n    knowledge, clinical practices, and therapeutic approaches related to a specific medical\n    condition. Instead of focusing on a single device or procedure, this analysis provides a\n    comprehensive overview of all available alternatives for achieving the intended medical purpose.\n    For example, if evaluating a device for diabetes diagnosis, the analysis would explore various\n    diagnostic criteria and methods used for this condition.\n  \u003C/p>\n  \u003Cp>\n    A procedure-based medical background SOTA analysis, on the other hand, systematically examines\n    the techniques and technologies used to perform a specific medical function. For instance, if\n    the device under review is a thermometer, the analysis would cover all recognized methods of\n    temperature measurement.\n  \u003C/p>\n  \u003Cp>\n    At this stage, the SOTA analysis remains technology-agnostic, concentrating on the procedural\n    category rather than individual technical alternatives. This means you are not yet investigating\n    specific implementations (e.g., capillary vs. infrared thermometers). Instead, the goal is to\n    identify alternative methods, emerging innovations, and evidence-based best practices within the\n    field.\n  \u003C/p>\n  \u003Cp>\n    Similarly, analyzing the performance and safety characteristics of the identified alternatives\n    is not yet required at this stage. This evaluation will be conducted in the next phase of the\n    SOTA process, specifically during the meta-analysis of identified medical alternatives (see\n    Figure \u003Ca href=\"#fig-sota-structure\">1.1\u003C/a>).\n  \u003C/p>\n  \u003Cp>\n    Finally, remember that if your device has multiple indications—such as both the diagnosis and\n    prevention of diabetes—you are expected to provide a medical background for each indication\n    (diagnosis of diabetes and prevention of diabetes).\n  \u003C/p>\n  \u003Cp>\n    Medical background analyses Post-market searches are systematic reviews. This means that they\n    must be planned, conducted, reported, and updated according to best practices. Below, we outline\n    these best practices.\n  \u003C/p>\n\u003C/div>\n\u003Ch2 id=\"planning-the-search\">2 Planning the search\u003C/h2>\n\u003Cdiv id=\"cha-plan\">\u003C/div>\n\u003Cdiv class=\"multicols\">\n  \u003Cp>\u003Cspan>2\u003C/span>\u003C/p>\n  \u003Cp>\n    This chapter outlines the key elements to consider when planning medical background SOTA\n    analyses. These include defining objectives, selecting sources, developing a search strategy,\n    and establishing appraisal criteria. For additional guidance on planning systematic searches and\n    reviews, you may refer to the \u003Ca href=\"#ref-prisma-2020\">PRISMA 2020 statement\u003C/a>.\n  \u003C/p>\n  \u003Cp>\n    We also encourage you to read about medical background SOTA analyses, which are detailed in our\n    guidance SOTA_BACKGROUND. Post-market searches are, in many ways, mirror approaches to medical\n    background SOTA analyses. Comparing the two frameworks helps understanding how to take decisions\n    on planning, executing, documenting, and updating these searches. That is also the reason why at\n    the end of this chapter we provide a side-by-side comparison of post-market searches and medical\n    background SOTA analyses.\n  \u003C/p>\n  \u003Ch3 id=\"evaluators\">2.1 Evaluators\u003C/h3>\n  \u003Cp>\n    Specify who will perform the review. The definition of specific roles (such as author, reviewer,\n    approver, etc.) typically depends on company-specific procedures.\n  \u003C/p>\n  \u003Cp>\n    The requirements of \u003Ca href=\"#ref-meddev-2-7-1\">MEDDEV 2.7/1\u003C/a> concerning the expertise of\n    clinical evaluators also applies to post-market searches. These requirements include knowledge\n    of:\n  \u003C/p>\n  \u003Cul>\n    \u003Cli>\u003Cp>research methodology (including clinical investigation and biostatistics);\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>information management;\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>regulatory requirements;\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>medical writing;\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>the device technology and its applications,\u003C/p>\u003C/li>\n    \u003Cli>\n      \u003Cp>\n        diagnosis and management of the conditions intended to be diagnosed or managed by the\n        device, knowledge of medical alternatives, treatment standards and technology.\n      \u003C/p>\n    \u003C/li>\n  \u003C/ul>\n  \u003Cp>\n    In addition, evaluators must possess a relevant degree from higher education in the respective\n    field and 5 years of documented professional experience, or 10 years of documented professional\n    experience if a degree is not a prerequisite for the given task.\n  \u003C/p>\n  \u003Ch3 id=\"review-questions\">2.2 Review questions\u003C/h3>\n  \u003Cdiv id=\"sec-objectives\">\u003C/div>\n  \u003Cp>\n    As mentioned earlier, the goal of medical background SOTA analyses is to provide an objective,\n    unbiased overview of standard medical practice related to a specific condition or procedure.\n  \u003C/p>\n  \u003Cp>\n    Relevant medical literature is systematically retrieved, and information is extracted from each\n    source to address the specific review questions. These questions, which guide data extraction,\n    are defined in the objectives section of the review plan. Table\n    \u003Ca href=\"#tab-questions-condition\">2.1\u003C/a> summarizes these questions for a condition-based\n    medical background SOTA analysis.\n  \u003C/p>\n  \u003Cdiv class=\"table-wrap\">\n    \u003Ctable>\n      \u003Ctbody>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cstrong>Questions for condition-focused SOTAs\u003C/strong>\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Definition\u003C/em>: What is the definition of the condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Coding\u003C/em>: What are the specific codes for the condition in different medical\n            coding systems (e.g., ICD-10, ICD-11, SNOMED)?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Names\u003C/em>: Are there other medical or commonly used names for the condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Etiology\u003C/em>: What is the cause or origin of the condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Grading\u003C/em>: Are there standardized grading systems to classify or assess the\n            severity of the condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Epidemiology\u003C/em>: What is the distribution, prevalence, and incidence of the\n            condition in different populations?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Pathophysiology\u003C/em>: What are the functional and biological changes caused by the\n            condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Clinical presentation\u003C/em>: What are the signs, symptoms, and laboratory findings\n            associated with the condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Differential diagnosis\u003C/em>: What other conditions could present similarly to this\n            condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Risk factors\u003C/em>: What conditions, behaviors, or predisposing factors increase the\n            likelihood of developing this condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Natural course\u003C/em>: What is the expected progression of the condition, with and\n            without treatment?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Prognosis\u003C/em>: What is the anticipated outcome or long-term course of the\n            condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Complications\u003C/em>: What are the possible complications associated with the\n            condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Cultural and regional variations\u003C/em>: How do presentation, treatment, and outcomes\n            vary across different populations and regions?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Clinical outcomes and assessment tools\u003C/em>: What are the key clinical outcomes and\n            validated assessment tools used to evaluate the condition?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Medical alternatives\u003C/em>: What are the available medical alternatives available for\n            (select based on your device purpose) preventing / predicting / prognosing / diagnosing\n            / treating / etc. the condition? Which alternatives are considered outdated, standard of\n            care, novel, first-in-line, second-in-line, supportive/adjuvant, gold-standard? Which\n            alternatives can be combined?\n          \u003C/td>\n        \u003C/tr>\n      \u003C/tbody>\n    \u003C/table>\n  \u003C/div>\n  \u003Cdiv class=\"floatcaption\">\n    \u003Cp>\n      Table 2.1: List of typical questions concerning a condition to be answered in a medical\n      background SOTA analysis.\n    \u003C/p>\n  \u003C/div>\n  \u003Cdiv id=\"tab-questions-condition\">\u003C/div>\n  \u003Cp>\n    Table \u003Ca href=\"#tab-questions-procedure\">2.2\u003C/a> summarizes the questions concerning a procedure\n    to be answered in a procedure-focused medical background SOTA analysis.\n  \u003C/p>\n  \u003Ch3 id=\"source-selection\">2.3 Source selection\u003C/h3>\n  \u003Cp>\n    The objective of medical background reviews is to identify the highest-quality, evidence-based\n    information from the most reliable and reputable sources—the \"cream\" of the literature.\n  \u003C/p>\n  \u003Cdiv class=\"table-wrap\">\n    \u003Ctable>\n      \u003Ctbody>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cstrong>Questions for procedure-focused SOTAs\u003C/strong>\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Definition\u003C/em>: What is the definition of the type of procedure?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"odd\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Names\u003C/em>: Are there other medical or commonly used names for this type of\n            procedure?\n          \u003C/td>\n        \u003C/tr>\n        \u003Ctr class=\"even\">\n          \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n            \u003Cem>Medical alternatives\u003C/em>: What are the available medical alternatives for\n            performing the procedure? Which alternatives are considered outdated, standard of care,\n            novel, first-in-line, second-in-line, supportive/adjuvant, or gold-standard? Which\n            alternatives can be combined?\n          \u003C/td>\n        \u003C/tr>\n      \u003C/tbody>\n    \u003C/table>\n  \u003C/div>\n  \u003Cdiv class=\"floatcaption\">\n    \u003Cp>\n      Table 2.2: List of typical questions concerning a procedure to be answered in a medical\n      background SOTA analysis.\n    \u003C/p>\n  \u003C/div>\n  \u003Cdiv id=\"tab-questions-procedure\">\u003C/div>\n  \u003Cp>These criteria define the requirements for databases relevant to SOTA analyses.\u003C/p>\n  \u003Col>\n    \u003Cli>\n      \u003Cp>The selected databases should be specialized in medical and life sciences literature.\u003C/p>\n    \u003C/li>\n    \u003Cli>\u003Cp>Gray literature, preprints, and non-peer-reviewed sources are not of interest.\u003C/p>\u003C/li>\n    \u003Cli>\n      \u003Cp>\n        Full-text indexing is unnecessary. Since the focus is on high-level analyses related to the\n        condition or procedure of interest, relevant publications should explicitly mention these\n        terms in their title or abstract.\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        Reproducibility is crucial in medical background SOTA searches. Consequently, search engines\n        like Google Scholar, which lack transparency and consistency in their search algorithms, are\n        not recommended for this purpose.\n      \u003C/p>\n    \u003C/li>\n  \u003C/ol>\n  \u003Cp>\n    It is important to highlight that these source requirements apply specifically to medical\n    background SOTA analyses and do not necessarily extend to all searches conducted for technical\n    documentation. For instance, post-market searches—outlined in our guide\n    \u003Ca href=\"#ref-post-market-searches\">POST-MARKET SEARCHES\u003C/a>—prioritize breadth over\n    reproducibility and therefore permit the use of sources such as Google Scholar.\n  \u003C/p>\n  \u003Cp>Below is a minimum list of source types that post-market searches should rely on:\u003C/p>\n  \u003Cul>\n    \u003Cli>\u003Cp>Scholarly articles\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>Systematic reviews and meta-analyses\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>Medical associations websites\u003C/p>\u003C/li>\n  \u003C/ul>\n  \u003Cp>Below, we will consider each source type in detail.\u003C/p>\n  \u003Ch4 id=\"scholarly-articles\">2.3.1 Scholarly articles\u003C/h4>\n  \u003Cdiv id=\"subsec-scholarly-articles\">\u003C/div>\n  \u003Cp>\n    The term \"scholarly articles\" refers to publications authored in academic settings. It is\n    standard practice to begin with cross-publisher sources, as they streamline the search process\n    by aggregating content from multiple publishers in one place. We recommend using two freely\n    available aggregated sources that meet the four criteria outlined above: PubMed (US) and Livivo\n    (EU).\n  \u003C/p>\n  \u003Cp>\n    Once you’ve completed your search in aggregated databases, you can turn to publisher-specific\n    platforms. If you are aware that a specific journal or publisher is particularly likely to\n    publish relevant data on the device you are researching, consider supplementing the aggregated\n    database search with searches in the specific publisher’s databases.\n  \u003C/p>\n  \u003Ch4 id=\"systematic-reviews-and-meta-analyses-databases\">\n    2.3.2 Systematic reviews and meta-analyses databases\n  \u003C/h4>\n  \u003Cp>\n    Systematic review and meta-analysis databases serve as repositories for research that follows\n    structured methodologies to synthesize evidence on a given topic. These databases often include\n    records of planned or ongoing systematic reviews rather than the full published studies\n    themselves. Such records typically contain essential details about the review process, including\n    objectives, inclusion criteria, data extraction methods, and planned analyses—elements\n    collectively referred to as the protocol.\n  \u003C/p>\n  \u003Cp>\n    By registering systematic reviews in these databases, researchers enhance transparency, minimize\n    duplication of efforts, and reduce the risk of publication bias. Importantly, these databases\n    might not host the full systematic reviews or meta-analyses but instead provide structured\n    summaries that allow users to track ongoing research efforts and verify whether a particular\n    review is already in progress.\n  \u003C/p>\n  \u003Cp>\n    \u003Ca href=\"https://www.crd.york.ac.uk/prospero/\">PROSPERO\u003C/a> is an international database\n    specifically dedicated to prospectively registering systematic review protocols, primarily in\n    health and social care. It ensures methodological transparency by requiring detailed information\n    on the review plan before data extraction begins.\n  \u003C/p>\n  \u003Cp>\n    The \u003Ca href=\"https://www.cochranelibrary.com/cdsr\">CDSR\u003C/a>, managed by the Cochrane\n    Collaboration, is a key resource for high-quality, peer-reviewed systematic reviews in\n    healthcare, often considered the gold standard due to its rigorous methodology and evidence\n    synthesis approach. Access to CDSR articles may be geo-blocked in your country. If so, consider\n    \"traveling\" to locations that allow access. A list of such locations can be found\n    \u003Ca\n      href=\"https://www.cochranelibrary.com/help/access;jsessionid=1B2B75512EE6459FE55D9830B69D7D73\"\n      >here\u003C/a\n    >.\n  \u003C/p>\n  \u003Ch4 id=\"websites\">2.3.3 Websites\u003C/h4>\n  \u003Cdiv id=\"subsec-websites\">\u003C/div>\n  \u003Ch6 id=\"medical-associations\">Medical associations\u003C/h6>\n  \u003Cp>\n    Medical associations often publish clinical guidelines and position statements that reflect the\n    current standard of care for specific conditions, procedures, or interventions. These guidelines\n    are typically developed through expert consensus, systematic reviews, and evidence-based\n    methodologies. Searching the websites of relevant national and international medical\n    associations can provide access to high-quality recommendations that may not be fully indexed in\n    standard databases. For example, organizations such as the American Heart Association (AHA),\n    European Society of Cardiology (ESC), or the World Health Organization (WHO) regularly update\n    their clinical practice guidelines. If a particular association has published a guideline\n    relevant to your topic, it is worth reviewing their full list of documents and position\n    statements, as well as monitoring updates or ongoing guideline development efforts.\n  \u003C/p>\n  \u003Ch4 id=\"hand-search\">2.3.4 Hand search\u003C/h4>\n  \u003Cp>\n    Hand searching originated in an era when researchers manually sifted through physical sources in\n    libraries. Today, with searches conducted primarily online, it is essential to specify where\n    each record was located to ensure transparency and reproducibility. In the context of medical\n    background SOTA analyses, the use of hand searching is deprecated because the goal is to\n    identify the highest-quality, evidence-based information—the \"cream\" of the literature. If a\n    source does not appear through systematic database searches, its relevance and reliability are\n    questionable, making it inappropriate to introduce it arbitrarily.\n  \u003C/p>\n  \u003Ch4 id=\"which-sources-you-dont-need\">2.3.5 Which sources you don’t need\u003C/h4>\n  \u003Cdiv id=\"nosources\">\u003C/div>\n  \u003Cp>\n    Medical background SOTA analyses generally benefit little from including clinical trial\n    registries, such as ICTRP or ClinicalTrials.gov. This is because, whenever possible, these\n    analyses prioritize higher levels of evidence that synthesize and summarize findings from\n    individual trials.\n  \u003C/p>\n  \u003Cp>\n    You do not need to search safety information databases (e.g., incident and adverse event\n    databases such as MAUDE or DAEN, or databases tracking actions by manufacturers or authorities,\n    such as MHRA or BfArM). This is because SOTA analyses typically do not focus on specific\n    devices.\n  \u003C/p>\n  \u003Cp>\n    At this stage of the SOTA process, you do not need to include Health Technology Assessments (s).\n    Even if your SOTA is procedure-based, you are analyzing a medical procedure itself, not a\n    specific technology used to implement that procedure. We will consider s when discussing SOTA\n    analysis concerning the performance and safety of specific alternatives.\n  \u003C/p>\n  \u003Cp>\n    In the market, you’ll find plenty of paywalled databases claiming to deliver more relevant\n    results for device searches. However, in our experience, these sources often fall short compared\n    to the freely available ones we highlighted in the search strategy above. A CE mark can be\n    achieved successfully without relying on these paywalled options.\n  \u003C/p>\n  \u003Ch3 id=\"search-strategy\">2.4 Search strategy\u003C/h3>\n  \u003Cp>\n    Post-market searches aim to identify any written information concerning a specific device. For\n    this reason, the search strategy should be as broad as possible, while remaining manageable.\n    Below are the key steps.\n  \u003C/p>\n  \u003Ch4 id=\"inclusion-criteria\">2.4.1 Inclusion criteria\u003C/h4>\n  \u003Cp>\n    Medical background SOTA analyses reviews apply a version of the PICO framework that addresses\n    clinical questions related to interventions, exposure, and risk/prognostic factors:\n    (\u003Cem>P\u003C/em>)atient, (\u003Cem>I\u003C/em>)nvestigated condition or procedure, (\u003Cem>C\u003C/em>)omparison, and\n    (\u003Cem>O\u003C/em>)utcomes.\n  \u003C/p>\n  \u003Cp>\n    For medical background SOTA analyses, the \u003Cem>P\u003C/em> typically represents one of the target\n    populations relevant to the device under evaluation. In condition-based SOTA, the\n    \u003Cem>I\u003C/em> (Investigated condition) refers to the condition under analysis. In procedure-based\n    SOTA, the \u003Cem>I\u003C/em> (Intervention) represents the medical procedure being evaluated.\n  \u003C/p>\n  \u003Cp>\n    At this stage of the SOTA process, \u003Cem>C\u003C/em> (Comparison) and \u003Cem>O\u003C/em> (Outcomes) are often\n    not strictly defined and can remain broad or unspecified.\n  \u003C/p>\n  \u003Ch4 id=\"queries\">2.4.2 Queries\u003C/h4>\n  \u003Cp>\n    For condition-based SOTAs, use the condition’s name, including alternative terms or synonyms.\n    For procedure-based SOTAs, use the name of the procedure. You can also tailor the query to\n    restrict the level of evidence (see Section \u003Ca href=\"#subsec-limits\">2.4.3\u003C/a>). Indeed, that\n    database filters are not always reliable—some records may be misclassified or incorrectly\n    included. For example, in PubMed, studies are sometimes tagged with the wrong evidence level.\n  \u003C/p>\n  \u003Ch4 id=\"limits-and-filters\">2.4.3 Limits and filters\u003C/h4>\n  \u003Cdiv id=\"subsec-limits\">\u003C/div>\n  \u003Ch5 id=\"targeted-level-of-evidence\">Targeted level of evidence\u003C/h5>\n  \u003Cp>\n    Medical background SOTA analyses aim to retrieve the highest level of evidence available in the\n    medical field for the specific condition or procedure under review. The following represents the\n    typical hierarchy of evidence considered in systematic reviews, from which the most relevant and\n    highest-quality sources should be selected:\n  \u003C/p>\n  \u003Col>\n    \u003Cli>\u003Cp>Evidence-based guidelines\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>Systematic reviews / meta-anal.\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>Randomized controlled trials\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>Observational / cohort studies\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>Case studies, mechanistic reasoning, low-quality evidence.\u003C/p>\u003C/li>\n  \u003C/ol>\n  \u003Ch5 id=\"time-period\">Time Period\u003C/h5>\n  \u003Cp>\n    The search timeframe is typically set to the last 5, 10, or 20 years, depending on the update\n    frequency within the field:\n  \u003C/p>\n  \u003Cul>\n    \u003Cli>\n      \u003Cp>\n        5 years – Suitable for fast-evolving fields with frequent advancements (e.g., emerging\n        medical technologies, novel drug therapies).\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        10 years – Used when significant advancements occur, but older studies may still be relevant\n        (e.g., surgical techniques, chronic disease management).\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        20 years – Appropriate for slow-changing or rarely updated fields where foundational\n        knowledge remains largely unchanged (e.g., basic physiology, rare diseases).\n      \u003C/p>\n    \u003C/li>\n  \u003C/ul>\n  \u003Ch4 id=\"exclusion-criteria\">2.4.4 Exclusion criteria\u003C/h4>\n  \u003Cdiv id=\"subsec-exclusion-criteria\">\u003C/div>\n  \u003Cp>\n    For medical background SOTA analyses we recommend using a two-steps screening process: 1) Title\n    and abstract screening to filter out clearly irrelevant records, followed by 2) Full-text\n    screening to assess the relevance of the remaining records.\n  \u003C/p>\n  \u003Ch3 id=\"synthesis\">2.5 Synthesis\u003C/h3>\n  \u003Cp>\n    The synthesis step in a medical background SOTA analyses is primarily textual, focusing on\n    summarizing and interpreting findings rather than conducting a meta-analysis unless the data\n    allows for quantitative pooling.\n  \u003C/p>\n  \u003Ch3 id=\"appraisal\">2.6 Appraisal\u003C/h3>\n  \u003Cp>For medical background SOTA analyses, appraisal occurs at two levels.\u003C/p>\n  \u003Cp>\n    First, the appraisal of included records assesses their quality, risk of bias, and overall\n    reliability. The choice of appraisal method depends on the study type of the retrieved records,\n    which, in turn, is determined by the targeted level of evidence, as follows:\n  \u003C/p>\n  \u003Col>\n    \u003Cli>\n      \u003Cp>\n        Evidence-based guidelines — Assessed using AGREE II (Appraisal of Guidelines for Research\n        & Evaluation).\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        Systematic reviews / meta-analyes — Evaluated with AMSTAR 2 (A Measurement Tool to Assess\n        Systematic Reviews).\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        Randomized controlled trials — Appraised using the Cochrane Risk of Bias tool (RoB 2) or\n        GRADE (Grading of Recommendations, Assessment, Development, and Evaluations).\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        Observational / cohort studies — Assessed with the Newcastle-Ottawa Scale (NOS) or the\n        ROBINS-I tool (Risk of Bias in Non-Randomized Studies of Interventions). The GRADE framework\n        is also applied to adjust for potential confounding and bias.\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        Case studies, mechanistic reasoning, low-quality evidence — Evaluated using the Joanna\n        Briggs Institute (JBI) checklist.\n      \u003C/p>\n    \u003C/li>\n  \u003C/ol>\n  \u003Cp>\n    Second, once the evidence has been synthesized, it is further classified according to the Oxford\n    Centre for Evidence-Based Medicine (OCEBM) levels of evidence. Alternatively, other methods can\n    be used, such as GRADE (Grading of Recommendations, Assessment, Development, and Evaluations),\n    USPSTF (U.S. Preventive Services Task Force) grading system, NHMRC (National Health and Medical\n    Research Council) evidence hierarchy, or SIGN (Scottish Intercollegiate Guidelines Network)\n    levels of evidence, depending on the context and purpose of the review.\n  \u003C/p>\n\u003C/div>\n\u003Cdiv id=\"tab-plan-sota-vs-post-market\">\u003C/div>\n\u003Cdiv class=\"table-wrap\">\n  \u003Ctable>\n    \u003Ccaption>\n      Table 2.3: Comparison of the plan characteristics between medical background SOTA analyses and\n      post-market searches.\n    \u003C/caption>\n    \u003Ctbody>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cstrong>Medical background SOTA\u003C/strong> (This document)\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cstrong>Post-market searches\u003C/strong> (see reference\n          \u003Ca href=\"#ref-post-market-searches\">POST-MARKET SEARCHES\u003C/a>)\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\u003Cstrong>Type\u003C/strong>\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Systematic review\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Systematic search\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\u003Cstrong>Objectives\u003C/strong>\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          The objective of medical background SOTA analyses is to provide an objective, unbiased\n          overview about standard medical praxis concerning a specific condition or procedure.\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          Gather \u003Cem>any\u003C/em> written record that provides information about the performance and\n          safety of a particular medical device.\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cstrong>Source Selection\u003C/strong>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Scholarly article databases\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>PubMed\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Livivo\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>PubMed\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>PMC\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>EU PMC\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>OpenAlex\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Google Scholar\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Publisher specific\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">Ad hoc\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">Ad hoc\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Clinical trials\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Rarely required\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">ICTRP\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Health technology assessments\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Rarely required\u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cp>\u003C/p>\n          \u003Cp>Incidents and adverse events\u003C/p>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Rarely required\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>MAUDE\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>DAEN\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>MDID\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cp>\u003C/p>\n          \u003Cp>Actions by manufacturers and authorities\u003C/p>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Rarely required\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          Database of any authority in countries in which the devices is sold\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Patient registries\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Rarely required\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">Ad hoc\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Websites\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>Medical associations\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>Author websites\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Manufacturer websites\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>App stores\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Use of handsearch\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Not acceptable\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightorange\">\n          May be acceptable: reporting evidence has priority over how evidence is found.\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Systematic reviews\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>Cochrane CDRS\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>PROSPERO\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Rarely required\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cp>\u003C/p>\n          \u003Cp>Paywalled databases (e.g., Embase, Scopus, Web of Science)\u003C/p>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">Not required\u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cstrong>Search Strategy\u003C/strong>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Inclusion criteria\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">PICO strategy\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          Any record that reports information concerning the performance or safety of the device (in\n          humans)\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Queries\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">Condition or procedure name(s)\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>Device name\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Device name + manufacturer name (if device name too generic)\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Time limits\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          Last 5, 10, or 20 years, depending on field update frequency.\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          From date device was brought onto the market to search date\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Peer review\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">Records must be peer-reviewed\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">\n          Records do not need to be peer-reviewed\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Continues on the next page ...\u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n      \u003C/tr>\n    \u003C/tbody>\n  \u003C/table>\n\u003C/div>\n\u003Cdiv class=\"table-wrap\">\n  \u003Ctable>\n    \u003Ctbody>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\">\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cstrong>Medical background SOTA\u003C/strong> (This document)\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">\n          \u003Cstrong>Post-market searches\u003C/strong> (see reference\n          \u003Ca href=\"#ref-post-market-searches\">POST-MARKET SEARCHES\u003C/a>)\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Level of evidence\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>The highest level among:\u003C/p>\n          \u003Col>\n            \u003Cli>\u003Cp>Evidence-based guidelines\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Systematic reviews / meta-anal.\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Randomized controlled trials\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Observational / cohort studies\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Case studies, mechanistic reasoning, low-quality evidence.\u003C/p>\u003C/li>\n          \u003C/ol>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">Any\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Exclusion criteria\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cp>\n            The record does not provide information concerning the performance and safety of the\n            device (on humans)\n          \u003C/p>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>Non relevant patient population\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Non relevant intervention\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Non relevant comparator\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Non relevant outcome\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"even\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Synthesis\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">Textual synthesis\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">None\u003C/td>\n      \u003C/tr>\n      \u003Ctr class=\"odd\">\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgray\">Appraisal\u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightgreen\">\n          \u003Cp>\u003C/p>\n          \u003Cul>\n            \u003Cli>\u003Cp>Single study appraisal\u003C/p>\u003C/li>\n            \u003Cli>\u003Cp>Synthesis appraisal\u003C/p>\u003C/li>\n          \u003C/ul>\n        \u003C/td>\n        \u003Ctd style=\"text-align: left\" class=\"cell-verylightred\">\n          Not required: appraisal will be conducted in the processes where data from the search are\n          used.\n        \u003C/td>\n      \u003C/tr>\n    \u003C/tbody>\n  \u003C/table>\n\u003C/div>\n\u003Cdiv class=\"evidencebox\">\n  \u003Cp>\u003Cimg class=\"boxlogo\" src=\"/guides/evidence-logo.png\" alt=\"Evidence\" />\u003C/p>\n  \u003Cp>\n    Create successful medical background SOTA analyses even \u003Cem>with no regulatory expertise\u003C/em>.\n    Follow the \"review wizard\", answer the questions. Evidence will \u003Cem>automatically\u003C/em> generate\n    the full review plan, including objectives, search questions, inclusion and exclusion criteria,\n    and appraisal plan. But that’s not all—Evidence goes a step further by\n    \u003Cem>automatically\u003C/em> conducting proposed searches across relevant scholarly, systematic\n    review, and health technology assessment databases. Simply review the plan, lock it, and shift\n    your focus to the science. No matter your level of regulatory expertise, Evidence ensures you’ll\n    get it right.\n  \u003C/p>\n\u003C/div>\n\u003Ch2 id=\"conducting-the-search\">3 Conducting the search\u003C/h2>\n\u003Cdiv class=\"multicols\">\n  \u003Cp>\u003Cspan>2\u003C/span>\u003C/p>\n  \u003Cp>\n    This chapter outlines the key elements to consider when conducting a medical background SOTA\n    analyses. These include collecting all database information such as search details and search\n    results, retrieving missing information, screening and data extraction. Below we review each\n    element in detail.\n  \u003C/p>\n  \u003Cp>\n    If you are familiar with our guide\n    \u003Ca href=\"#ref-post-market-searches\">POST-MARKET SEARCHES\u003C/a> SOTA, you may skip this section, as\n    it closely mirrors the content of that guide.\n  \u003C/p>\n  \u003Ch3 id=\"search-details\">3.1 Search details\u003C/h3>\n  \u003Cp>\n    For each query in each source, provide as much relevant information as possible. This should\n    include:\n  \u003C/p>\n  \u003Cul>\n    \u003Cli>\u003Cp>The source name and link\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>The original search query\u003C/p>\u003C/li>\n    \u003Cli>\n      \u003Cp>\n        The actual search conducted by the database (including any automatic modifications or\n        expansions to the terms)\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\u003Cp>Any filters applied (e.g., publication type)\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>Any limits or restrictions (e.g., date range)\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>The name of the person who performed the search\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>The date and time the search was conducted\u003C/p>\u003C/li>\n  \u003C/ul>\n  \u003Cdiv class=\"warningbox\">\n    \u003Cdiv class=\"boxtitle\" id=\"box-2\">\u003Cp>Box 2: Searches with no results\u003C/p>\u003C/div>\n    \u003Cp>\n      The fact that a search returns no hits is an information on its own. You should document it to\n      show to reviewers why a search strategy didn’t provide results.\n    \u003C/p>\n  \u003C/div>\n  \u003Ch3 id=\"search-results\">3.2 Search results\u003C/h3>\n  \u003Cp>Document all records identified during database searches.\u003C/p>\n  \u003Cp>\n    Make sure the metadata are complete for all retrieved records, even for those you already plan\n    to exclude. These should include:\n  \u003C/p>\n  \u003Cul>\n    \u003Cli>\n      \u003Cp>\n        Full citation details (e.g., title, authors, journal, volume, issue, page numbers, year,\n        report number, study number)\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        Any further information required to uniquely identify the record (e.g., incident number or\n        trial identifier)\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\n      \u003Cp>\n        The abstract of scholarly articles (some scholarly articles does not provide an abstract,\n        you should note this information in the documentation)\n      \u003C/p>\n    \u003C/li>\n    \u003Cli>\u003Cp>The text of all records that you scan on full text.\u003C/p>\u003C/li>\n  \u003C/ul>\n  \u003Cp>\n    You can retrieve missing metadata by cross-verifying with other databases or the publisher’s\n    website.\n  \u003C/p>\n  \u003Ch3 id=\"deduplication\">3.3 Deduplication\u003C/h3>\n  \u003Cp>\n    Before processing the records you must identify duplicates. While this may seem straightforward,\n    there are several common misconceptions about the process (see also Box\n    \u003Ca href=\"#box-duplicated-records-vs-data\">3.3\u003C/a>). Finding duplicates involves identifying\n    instances where the same record appears across different searches within the same source or from\n    multiple sources. However, this task is more complex than it seems, as the same record may be\n    represented with different metadata in different sources. It’s important to note that for one\n    record to be considered a duplicate of another, it must represent the exact same full text. For\n    instance, a preprint is \u003Cem>not\u003C/em> a duplicate of the corresponding journal-published article,\n    as editorial changes may have occurred during final publication.\n  \u003C/p>\n  \u003Cdiv class=\"warningbox\">\n    \u003Cdiv class=\"boxtitle\" id=\"box-3\">\u003Cp>Box 3: Duplicated records vs. duplicated data\u003C/p>\u003C/div>\n    \u003Cdiv id=\"box-duplicated-records-vs-data\">\u003C/div>\n    \u003Cp>\n      It is not uncommon that researchers publish the results of a single study across multiple\n      publications. In the terminology of the PRISMA 2020 flow diagram, this is described as\n      multiple reports corresponding to the same study (see also box\n      \u003Ca href=\"#box-prisma\">4.1.3\u003C/a>). Some may refer to this situation as \"duplicated data,\" but\n      it is important to clarify that two distinct publications based on the same dataset are not\n      considered duplicate records.\n    \u003C/p>\n  \u003C/div>\n  \u003Ch3 id=\"translation\">3.4 Translation\u003C/h3>\n  \u003Cp>\n    Translate relevant non-English documents for inclusion in the analysis. Ideally, translations\n    should be performed by a field expert proficient in both languages. However, in practice,\n    notified bodies in Europe currently accept automated translations.\n  \u003C/p>\n  \u003Ch3 id=\"screening\">3.5 Screening\u003C/h3>\n  \u003Cp>\n    For each identified record, clearly indicate whether the record is included or excluded based on\n    the exclusion criteria outlined in Section \u003Ca href=\"#subsec-exclusion-criteria\">2.4.4\u003C/a>. For\n    each excluded record, document the specific exclusion criterion applied.\n  \u003C/p>\n  \u003Ch3 id=\"full-text\">3.6 Full text\u003C/h3>\n  \u003Cp>\n    You are expected to retrieve the full text of all records that you include during the screening.\n    For two-step screening (first screening on title and abstract, followed by screening on full\n    text) you should also make available the full text of the records that were excluded during the\n    second (full-text) screening step.\n  \u003C/p>\n  \u003Ch3 id=\"contact-the-authors\">3.7 Contact the authors\u003C/h3>\n  \u003Cp>\n    Some information may be missing from the retrieved record. For example, articles often fail to\n    clearly specify the model or variant of a device family or device, and details about the\n    reported data may sometimes be unclear. In such cases, consider reaching out to the author of\n    the article, field safety notice, or incident report. While responses are not guaranteed and may\n    be rare, it is worth attempting to obtain clarification.\n  \u003C/p>\n  \u003Ch3 id=\"citation-search\">3.8 Citation search\u003C/h3>\n  \u003Cdiv id=\"sec-citation-search\">\u003C/div>\n  \u003Cp>\n    The process of including records in the search does not end with the imports from the sources.\n    For each record included during screening, you are expected to review the references cited\n    within those articles (see \u003Ca href=\"#ref-meddev-2-7-1\">MEDDEV 2.7/1\u003C/a>, Section A4). This is\n    because\n    \u003Cem\n      >literature found to be relevant is likely to cite other literature that is of direct interest\n      to the manufacturer\u003C/em\n    >.\n  \u003C/p>\n  \u003Cp>\n    Indeed, even the PRISMA 2020 flow diagram (see also Section \u003Ca href=\"#subsec-flow\">4.1.3\u003C/a>)\n    provides a dedicated space for documenting records retrieved through citation search.\n  \u003C/p>\n  \u003Ch3 id=\"data-extraction\">3.9 Data extraction\u003C/h3>\n  \u003Cp>\n    For each question defined in the objectives of your literature search plan (see Section\n    \u003Ca href=\"#sec-objectives\">2.2\u003C/a>), extract the information pertaining to that question from\n    each record included in the screening. Document when a record does not provide information for a\n    specific question.\n  \u003C/p>\n  \u003Cp>\n    If the record is a study report (see Box \u003Ca href=\"#box-prisma\">4.1.3\u003C/a>) it is best practice to\n    extract basic study information for future retrieval. These include study characteristics such\n    as country, number of sites, study direction, type (interventional or observational), design,\n    inclusion and inclusion criteria, primary and secondary outcomes, follow-up and main results.\n  \u003C/p>\n\u003C/div>\n\u003Cdiv class=\"evidencebox\">\n  \u003Cp>\u003Cimg class=\"boxlogo\" src=\"/guides/evidence-logo.png\" alt=\"Evidence\" />\u003C/p>\n  \u003Cp>\n    \u003Cem>Save hundreds of hours of tedious work\u003C/em>. Evidence automatically captures queries, search\n    date, search details, filters, and limits from your searches in PubMed, Google Scholar, PubMed\n    Central (PMC), Europe PMC, OpenAlex, Cochrane, Prospero, ICTRP, MAUDE, DAEN, MDID. It also\n    automatically imports the search results and works in the background to retrieve missing\n    metadata, including titles, authors, abstracts, journals, etc. Evidence then automatically\n    identifies duplicates and downloads the full text of open-access articles. But it doesn’t end\n    here Evidence provides suggestion for the screening, automatically extracting study\n    characteristics and answering the questions of your search objectives using the information from\n    the full texts, and automatically synthesizing the extracted evidence for you.\n  \u003C/p>\n\u003C/div>\n\u003Ch2 id=\"reporting-the-search\">4 Reporting the search\u003C/h2>\n\u003Cdiv class=\"multicols\">\n  \u003Cp>\u003Cspan>2\u003C/span>\u003C/p>\n  \u003Cp>\n    Reporting the search can be one of the most tedious and time-consuming tasks in systematic\n    searches and reviews, especially when it comes to managing screening details and summaries.\n    Below, we briefly outline the key principles for documenting medical background SOTA analyses.\n  \u003C/p>\n  \u003Cp>\n    If you are familiar with our guide\n    \u003Ca href=\"#ref-post-market-searches\">POST-MARKET SEARCHES\u003C/a> on SOTA, you may skip this section.\n    Apart from the reporting of synthesis results, the reporting of medical background SOTA analyses\n    closely follows that of post-market searches.\n  \u003C/p>\n  \u003Ch3 id=\"reporting-the-screening\">4.1 Reporting the screening\u003C/h3>\n  \u003Cp>\n    To ensure total clarity, in the search report, you should include three types of screening\n    summaries, each presented at a different level of granularity:\n  \u003C/p>\n  \u003Col>\n    \u003Cli>\u003Cp>screening summary for each query in each source;\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>screening details for each item retrieved in the search;\u003C/p>\u003C/li>\n    \u003Cli>\n      \u003Cp>\n        a flow diagram overview of the screening for the totality of the records imported in the\n        systematic search (see Section \u003Ca href=\"#subsec-flow\">4.1.3\u003C/a>).\n      \u003C/p>\n    \u003C/li>\n  \u003C/ol>\n  \u003Cp>below we analyze each report in detail.\u003C/p>\n  \u003Ch4 id=\"screening-report\">4.1.1 Screening report\u003C/h4>\n  \u003Cp>\n    Begin the screening summary by providing the reviewer with an overview of the different queries\n    across the various sources. For each query in each source, include the following details:\n  \u003C/p>\n  \u003Col>\n    \u003Cli>\u003Cp>The total number of records retrieved from the query.\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>The number of records that were ultimately included after screening.\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>The total number of records excluded during the screening process.\u003C/p>\u003C/li>\n    \u003Cli>\u003Cp>A detailed count of records excluded under each specific exclusion criterion.\u003C/p>\u003C/li>\n  \u003C/ol>\n  \u003Ch4 id=\"screening-detail-for-each-item\">4.1.2 Screening detail for each item\u003C/h4>\n  \u003Cp>\n    Provide detailed screening information for each item retrieved in the search, including the\n    specific exclusion criteria applied. To streamline the review process, display the screening\n    details alongside basic record information, such as the title, authors, and abstract/summary.\n    This approach allows reviewers to quickly sample and verify your screening without needing to\n    search for the information separately.\n  \u003C/p>\n  \u003Ch4 id=\"flow-diagram\">4.1.3 Flow diagram\u003C/h4>\n  \u003Cdiv id=\"subsec-flow\">\u003C/div>\n  \u003Cp>\n    The PRISMA 2020 flow diagram—see \u003Ca href=\"#ref-prisma-2020\">PRISMA 2020 statement\u003C/a>—is a\n    standardized tool designed to summarize the retrieval and screening process of studies (see Box\n    \u003Ca href=\"#box-prisma\">4.1.3\u003C/a>). It is expected that you use this diagram to document each\n    stage of the search process, including the number of records identified, screened, assessed for\n    eligibility, and included in the final synthesis.\n  \u003C/p>\n  \u003Cdiv class=\"warningbox\">\n    \u003Cdiv class=\"boxtitle\" id=\"box-4\">\u003Cp>Box 4: Record, report, study\u003C/p>\u003C/div>\n    \u003Cdiv id=\"box-prisma\">\u003C/div>\n    \u003Cp>\n      The PRISMA 2020 guidance\u003Ca href=\"#fn1\" class=\"footnote-ref\" id=\"fnref1\" role=\"doc-noteref\"\n        >\u003Csup>1\u003C/sup>\u003C/a\n      >\n      clarifies the difference between record, report and study.\n    \u003C/p>\n    \u003Cp>\n      Record—The title or abstract (or both) of a report indexed in a database or website (such as a\n      title or abstract for an article indexed in Medline).\n    \u003C/p>\n    \u003Cp>Report—A document (paper or electronic) supplying information about a particular study.\u003C/p>\n    \u003Cp>\n      Study—An investigation, such as a clinical trial, that includes a defined group of\n      participants and one or more interventions and outcomes. A “study” might have multiple\n      reports.\n    \u003C/p>\n  \u003C/div>\n  \u003Cp>\n    Results from search engines such as Google Scholar (see Section\n    \u003Ca href=\"#subsec-scholarly-articles\">2.3.1\u003C/a>), from citation searches (see Section\n    \u003Ca href=\"#sec-citation-search\">3.8\u003C/a>), and from websites (see Section\n    \u003Ca href=\"#subsec-websites\">2.3.3\u003C/a>) should be documented under the \"\u003Cem\n      >Identification of studies via other methods\u003C/em\n    >\" part of the diagram.\n  \u003C/p>\n  \u003Ch3 id=\"reporting-the-data\">4.2 Reporting the data\u003C/h3>\n  \u003Cp>\n    Ensure full transparency. Report every aspect of the data extraction for each included record.\n    This includes the information extracted for each question outlined in the search objectives,\n    study characteristics, and—if applying appraisal—the appraisal details for each record.\n  \u003C/p>\n  \u003Ch3 id=\"synthesis-1\">4.3 Synthesis\u003C/h3>\n  \u003Cp>\n    Medical background SOTA analyses are systematic reviews that include a synthesis step:\n    summarizing the bits of information that were extracted from each relevant record. For this\n    review, the synthesis is primarily textual, focusing on integrating findings from multiple\n    sources into a coherent narrative.\n  \u003C/p>\n  \u003Cp>\n    To ensure transparency and traceability, each synthesized statement must be directly linked to\n    the original sources from which the information was derived. This is done by placing references\n    next to each synthesis, allowing readers to verify the supporting evidence. The synthesis should\n    aim for clarity and conciseness while accurately reflecting the scope, quality, and limitations\n    of the available literature.\n  \u003C/p>\n\u003C/div>\n\u003Cdiv class=\"evidencebox\">\n  \u003Cp>\u003Cimg class=\"boxlogo\" src=\"/guides/evidence-logo.png\" alt=\"Evidence\" />\u003C/p>\n  \u003Cp>\n    \u003Cem>Generate a submission-ready literature search protocol with just one click\u003C/em>. Once\n    screening and data extraction are complete, your work is done. Why waste time with clunky Excel\n    tables or corrupted Word files? Simply download the protocol, sign it, and send it to your\n    notified body. And don’t worry—Evidence organizes all full texts seamlessly, ensuring reviewers\n    can easily follow every step.\n  \u003C/p>\n\u003C/div>\n\u003Ch2 id=\"updating-the-search\">5 Updating the search\u003C/h2>\n\u003Cdiv id=\"sec-updating\">\u003C/div>\n\u003Cdiv class=\"multicols\">\n  \u003Cp>\u003Cspan>2\u003C/span>\u003C/p>\n  \u003Cp>\n    The work of conducting medical background SOTA analyses does not stop with market approval.\n    These searches must be continuously updated through regular intervals as part of post-market\n    surveillance activities. Below we explain when, how, and how long you should be updating your\n    medical background SOTA analyses.\n  \u003C/p>\n  \u003Ch3 id=\"when-to-update\">5.1 When to update\u003C/h3>\n  \u003Cp>\n    At a minimum, updates are required to align with the updates to the clinical evaluation and\n    PSUR, which should ideally be synchronized. According to the \u003Ca href=\"#ref-mdr\">MDR\u003C/a>, Article\n    86, and \u003Ca href=\"#ref-ivdr\">IVDR\u003C/a>, Article 81, these updates must occur at least annually for\n    high-risk devices. For other devices, updates may be less frequent but should still adhere to a\n    periodic schedule defined by the manufacturer based on the risk classification and intended use\n    of the device.\n  \u003C/p>\n  \u003Ch3 id=\"how-to-update\">5.2 How to update\u003C/h3>\n  \u003Cp>\n    A common misconception about search updates is that using the \"delta\" approach is sufficient.\n    This method involves updating a search by retrieving only the results published after the date\n    of the last search. However, this approach is flawed because it overlooks how databases operate.\n    Records are often added to databases with significant delays, meaning that older records can be\n    added after the last search was completed. If your search update starts from the last date of\n    your search, you will miss these results, as illustrated in Figure\n    \u003Ca href=\"#fig-update\">5.1\u003C/a>.\n  \u003C/p>\n  \u003Cfigure>\n    \u003Cimg src=\"/guides/state-of-the-art-analyses/update.png\" />\n    \u003Cdiv id=\"fig-update\">\u003C/div>\n    \u003Cfigcaption>\n      Figure 5.1: The \"delta\" approach for updating searches misses records that have been added to\n      the sources after the last update. The correct way to update searches is to repeat the search\n      across the full planned time frame.\n    \u003C/figcaption>\n  \u003C/figure>\n  \u003Cp>\n    The correct way to update searches—whether for state-of-the-art reviews or medical background\n    SOTA analyses—is to repeat the search across the full planned time frame.\n  \u003C/p>\n  \u003Cp>\n    If you follow our recommendation to perform post-market searches without restrictive time\n    filters (see Section \u003Ca href=\"#subsec-limits\">2.4.3\u003C/a>), this means that each search update\n    should cover the entire period from date the device was first placed on the market (anywhere in\n    the world) onward. This does not mean, however, that you need to re-screen old records or\n    extract again their data. You can simply retain the results (screening and data extraction) from\n    the previous search for any records that reappear in the updated results.\n  \u003C/p>\n  \u003Ch3 id=\"how-long-to-udpate\">5.3 How long to udpate\u003C/h3>\n  \u003Cp>\n    You are expected to update medical background SOTA analyses throughout the lifetime of the\n    device (see \u003Ca href=\"#ref-mdr\">MDR\u003C/a> Article 86, and \u003Ca href=\"#ref-ivdr\">IVDR\u003C/a>, Article\n    81). For example, if a device has a lifetime of 6 years and you place the last device on the\n    market in 2024, you are expected to keep your PMCF up-to-date until 2030.\n  \u003C/p>\n\u003C/div>\n\u003Cdiv class=\"evidencebox\">\n  \u003Cp>\u003Cimg class=\"boxlogo\" src=\"/guides/evidence-logo.png\" alt=\"Evidence\" />\u003C/p>\n  \u003Cp>\n    \u003Cem>Keep your searches up-to-date with minimum effort\u003C/em>. Evidence is the only literature\n    software that allows you to update searches in a methodologically correct way while minimizing\n    effort. How does it work? Simply inform Evidence that you’re updating a search. Import the new\n    results. Evidence will ensure that all your previous screening and data extraction work for\n    earlier articles is preserved.\n  \u003C/p>\n\u003C/div>\n\u003Ch3 class=\"unnumbered\" id=\"references\">References\u003C/h3>\n\u003Cul>\n  \u003Cli>\n    \u003Cdiv id=\"ref-intended-purpose\">\u003C/div>\n    \u003Cp>\n      \u003Cstrong>INTENDED PURPOSE\u003C/strong> — How to write an intended purpose for MDR. 4BetterDevices\n      GmbH, 2025\n    \u003C/p>\n  \u003C/li>\n  \u003Cli>\n    \u003Cdiv id=\"ref-ivdr\">\u003C/div>\n    \u003Cp>\n      \u003Cstrong>IVDR\u003C/strong> — Regulation (EU) 2017/746 on in vitro diagnostic medical devices.\n      European Parliament and Council of the European Union, 2024\n    \u003C/p>\n  \u003C/li>\n  \u003Cli>\n    \u003Cdiv id=\"ref-mdr\">\u003C/div>\n    \u003Cp>\n      \u003Cstrong>MDR\u003C/strong> — Regulation (EU) 2017/745 on medical devices. European Parliament and\n      Council of the European Union, 2024\n    \u003C/p>\n  \u003C/li>\n  \u003Cli>\n    \u003Cdiv id=\"ref-meddev-2-7-1\">\u003C/div>\n    \u003Cp>\n      \u003Cstrong>MEDDEV 2.7/1\u003C/strong> — Guidelines on medical devices, clinical evaluation: a guide\n      for manufacturers and notified bodies under Directives 93/42/EEC and 90/385/EEC. European\n      Commission, 2016\n    \u003C/p>\n  \u003C/li>\n  \u003Cli>\n    \u003Cdiv id=\"ref-post-market-searches\">\u003C/div>\n    \u003Cp>\n      \u003Cstrong>POST-MARKET SEARCHES\u003C/strong> — How to conduct post-market searches. 4BetterDevices\n      GmbH, 2025\n    \u003C/p>\n  \u003C/li>\n  \u003Cli>\n    \u003Cdiv id=\"ref-prisma-2020\">\u003C/div>\n    \u003Cp>\n      \u003Cstrong>PRISMA 2020 statement\u003C/strong> — The PRISMA 2020 statement: an updated guideline for\n      reporting systematic reviews. Page, Matthew J. and McKenzie, Joanne E. and Bossuyt, Patrick M.\n      and Boutron, Isabelle and Hoffmann, Tammy C. and Mulrow, Cynthia D. and et al., 2021.\n      \u003Ca href=\"https://doi.org/10.1136/bmj.n71\" class=\"uri\">https://doi.org/10.1136/bmj.n71\u003C/a>\n    \u003C/p>\n  \u003C/li>\n\u003C/ul>\n\u003Csection id=\"footnotes\" class=\"footnotes footnotes-end-of-document\" role=\"doc-endnotes\">\n  \u003Chr />\n  \u003Col>\n    \u003Cli id=\"fn1\">\n      \u003Cp>BMJ 2021;372:n160\u003Ca href=\"#fnref1\" class=\"footnote-back\" role=\"doc-backlink\">↩︎\u003C/a>\u003C/p>\n    \u003C/li>\n  \u003C/ol>\n\u003C/section>\n",1792608381978]