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Completed Systematic Reviews




Diet-Related Fibers and Human Health Outcomes, Version 5.0


Public Project Complete

Statistics: 1156 Studies, 1 Key Question, 1 Extraction Form,
Date Published: Jul 09, 2019 05:48PM
Description: The objectives of this database are to: 1. Systematically compile and provide access to primary, English-language, peer-reviewed science linking dietary fiber intake in humans to one or more of 10 potential health benefits 2. Provide researchers with a tool to understand how different fibers are characterized in studies 3. Facilitate researchers in identifying gaps in the current research 4. Create a database to serve as a starting foundation of primary human literature for conducting evidence-based reviews and meta-analyses 5. Efficiently assist researchers in identifying fibers of interest. This database should serve as a foundation for future work. Specific inclusion and exclusion criteria, detailed in the user manual, were applied in determining database eligibility; thus, this database is not intended to serve as a sole source for identifying all possible fiber literature for the purposes of conducting a meta-analysis or systematic review. This database contains Population, Intervention, Comparator, and Outcome (PICO) data to help users formulate and narrow the focus of their research question. It is expected that secondary searches will be conducted to augment this database.
Contributor(s): Nicola McKeown (PI), Mei Chung (Co-I), Kara Livingston (Sr. Project & Data Manager), Caleigh Sawicki, Danielle Haslam, Deena Wang, Caitlin Blakeley, Yinan Jia, Nicole Baruch, Micaela Karlsen, Carrie Brown, Chenyueyi Ding, Bridget Gayer, Carolyn Lois, Kelly Cara
DOI: DOI pending.
Funding Source: International Life Sciences Institute – North America branch (ILSI-NA)
Methodology Description: Please see user manual.

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Physiologic Predictors of Severe Injury: Systematic Review [Entered Retrospectively]


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Statistics: 138 Studies, 3 Key Questions, 1 Extraction Form,
Date Published: May 30, 2019 05:31PM
Description: Objectives. To systematically identify and summarize evaluations of measures of circulatory and respiratory compromise, focusing on measures that can be used in field assessment by emergency medical services to inform decisions about the level of trauma care needed. We identified research on the ability of different measures to predict whether a patient was seriously injured and thus required transport to the highest level of trauma care available. Data sources. We searched Ovid MEDLINE®, CINAHL®, and the Cochrane databases from 1996 through August 2017. Reference lists of included articles were reviewed for additional relevant citations. Review methods. We included studies of individual measures and measures that combined circulatory, respiratory, and level of consciousness assessment. Evaluations included diagnostic accuracy (sensitivity and specificity) and area under the receiver operating characteristic curve (AUROC). We used data provided to calculate values that were not reported and pooled estimates across studies when feasible. Results. We identified and included 138 articles reporting results of 134 studies. Circulatory compromise measures evaluated in these studies included systolic blood pressure, heart rate, shock index, lactate, base deficit, and heart rate variability or complexity. The respiratory measures evaluated included respiration rate, oxygen saturation, partial pressure of carbon dioxide, and need for airway support. Many different combination measures were identified, but most were evaluated in only one or two studies. Pooled AUROCs from out-of-hospital data were 0.67 for systolic blood pressure (moderate strength of evidence); 0.67 for heart rate, 0.72 for shock index, 0.77 for lactate, 0.70 for respiratory rate, and 0.89 for Revised Trauma Score combination measure (all low strength of evidence); and were considered poor to fair. The only AUROC that reached a level considered excellent was for the Glasgow Coma Scale, age, and arterial pressure (GAP) combination measure (AUROC, 0.96; estimate based on emergency department data). All of the measures had low sensitivities and comparatively high specificities (e.g., sensitivities ranging from 13% to 74% and specificities ranging from 62% to 96% for out-of-hospital pooled estimates). Conclusions. Physiologic measures usable in triaging trauma patients have been evaluated in multiple studies; however, their predictive utilities are moderate and far from ideal. Overall, the measures have low sensitivities, high specificities, and AUROCs in the poor-to-fair range. Combination measures that include assessments of consciousness seem to perform better, but whether they are feasible and valuable for out-of-hospital use needs to be determined. Modification of triage measures for children or older adults is needed, given that the measures perform worse in these age groups; however, research has not yet conclusively identified modifications that result in better performance.
Contributor(s): Annette M. Totten, Ph.D. Tamara P. Cheney, M.D. Maya E. O'Neil, Ph.D. Craig D. Newgard, M.D., M.P.H. Mohamud Daya, M.D., M.S. Rongwei Fu, Ph.D. Ngoc Wasson, M.P.H. Erica L. Hart, M.S.T. Roger Chou, M.D.
DOI: DOI pending.
Funding Source: Agency for Healthcare Research and Quality (AHRQ)
Methodology Description: Review methods. We included studies of individual measures and measures that combined circulatory, respiratory, and level of consciousness assessment. Evaluations included diagnostic accuracy (sensitivity and specificity) and area under the receiver operating characteristic curve (AUROC). We used data provided to calculate values that were not reported and pooled estimates across studies when feasible.

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Short- and Long-Term Outcomes after Bariatric Surgery in the Medicare Population


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Statistics: 83 Studies, 5 Key Questions, 1 Extraction Form,
Date Published: May 29, 2019 04:17PM
Description: We conducted a technology assessment to summarize and appraise the current evidence regarding the effectiveness and safety of bariatric surgery in the Medicare-eligible population.
Contributor(s): Orestis A. Panagiotou, M.D., Ph.D. Georgios Markozannes, M.Sc. Rishi Kowalski, M.P.H. Abhilash Gazula, M.P.H. Mengyang Di, M.D. Dale S. Bond, Ph.D. Beth A. Ryder, M.D. Gaelen P. Adam, M.L.I.S. Thomas A. Trikalinos, M.D.
DOI: DOI pending.
Funding Source: AHRQ
Methodology Description: We searched six bibliographic databases and the reference lists of published clinical practice guidelines, relevant narrative and systematic reviews, and scientific information packages from manufacturers and other stakeholders on the outcomes and prediction models of different bariatric procedures studied in the Medicare-eligible population.

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Decision Aids for Cancer Screening and Treatment


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Statistics: 75 Studies, 2 Key Questions, 2 Extraction Forms,
Date Published: May 23, 2019 03:00PM
Description: Background: Many health decisions about screening and treatment for cancers involve uncertainty or tradeoffs between the expected benefits and harms. Patient decision aids have been developed to help health care consumers and their providers identify the available alternatives and choose the one that aligns with their values. It is unclear whether the effectiveness of decision aids for decisions related to cancers differs by people’s average risk of cancer or by the content and format of the decision aid.; Objectives: We sought to appraise and synthesize the evidence assessing the effectiveness of decision aids targeting health care consumers who face decisions about cancer screening or prevention, or early cancer treatment (Key Question 1), particularly with regard to decision aid or patient characteristics that might function as effect modifiers. We also reviewed interventions targeting providers for promotion of shared decision making using decision aids (Key Question 2).; Data sources: We searched MEDLINE®, Embase®, the Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO®, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL®) from inception to the end of June 2014.; Review methods: For Key Question 1, we included randomized controlled trials comparing decision aid interventions among themselves or with a control. We included trials of previously developed decision aids that were delivered at the point of the actual decision. We predefined three population groups of interest based on risk or presence of cancer (average cancer risk, high cancer risk, early cancer). The assessed outcomes pertained to measurements of decisional quality and cognition (e.g., knowledge scores), attributes of the decision-making process (e.g., Decisional Conflict Scale), emotion and quality of life (e.g., decisional regret), and process and system-level attributes. We assessed for effect modification by population group, by the delivery format or content of the decision aid or other attributes, or by methodological characteristics of the studies. For Key Question 2, we included studies of any intervention to promote patient decision aid use, regardless of study design and outcomes assessed.; Results: Of the 16,669 screened citations, 87 publications were eligible, corresponding to 83 (68 trials; 25,337 participants) and 5 reports for Key Questions 1 and 2, respectively. Regarding the evolution of the decision aid format and content over time, more recent trials increasingly studied decision aids that were more practical to deliver (e.g., over the Internet or without human mediation) and more often clarified preferences explicitly. Overall, participants using decision aids had higher knowledge scores compared with those not using decision aids (standardized mean difference, 0.23; 95% credible interval [CrI], 0.09 to 0.35; 42 comparison strata with 12,484 participants). Compared with not using decision aids, using decision aids resulted in slightly lower decisional conflict scores (weighted mean difference of -5.3 units [CrI, -8.9 to - 1.8] on the 0-100 Decisional Conflict Scale; 28 comparison strata; 7,923 participants). There was no difference in State-Trait Anxiety Inventory scores (weighted mean difference = 0.1; 95% CrI, -1.0 to 0.7 on a 20-80 scale; 16 comparison strata; 2,958 participants). Qualitative synthesis suggested that patients using decision aids are more likely to make informed decisions and have accurate risk perceptions; further, they may make choices that best agree with their values and may be less likely to remain undecided. Because there was insufficient, sparse, or no information about effects of decision aids on patient-provider communication, patient satisfaction with decision-making process, resource use, consultation length, costs, or litigation rates, a quantitative synthesis was not done. There was no evidence for effect modification by population group, by the delivery format or content of the decision aid or other attributes, or by methodological characteristics of the studies. Data on Key Question 2 were very limited.; Conclusions: Cancer-related decision aids have evolved over time, and there is considerable diversity in both format and available evidence. We found strong evidence that cancer-related decision aids increase knowledge without adverse impact on decisional conflict or anxiety. We found moderate- or low-strength evidence that patients using decision aids are more likely to make informed decisions, have accurate risk perceptions, make choices that best agree with their values, and not remain undecided. This review adds to the literature that the effectiveness of cancer-related decision aids does not appear to be modified by specific attributes of decision aid delivery format, content, or other characteristics of their development and implementation. Very limited information was available on other outcomes or on the effectiveness of interventions that target providers to promote shared decision making by means of decision aids.
Contributor(s): Gaelen Adam Thomas Trikalinos L. Susan Wieland Anja Zgodic Evangelia Ntzani
Funding Source: AHRQ
Methodology Description: Eligible Studies for Key Question 1: We included randomized controlled trials comparing use of patient decision aids with other patient decision aids or with no decision aid intervention. We included trials of mature patient decision aids delivered at the point of the actual decision. We excluded trials about hypothetical treatment decisions. For example, we excluded hypothetical questions about early cancer treatment in people not yet diagnosed with cancer, or trials about cancer screening among people who would not be typical screening candidates. We predefined three populations of interest, based on risk or presence of cancer. The first population included people without cancer who are at average risk and face decisions about cancer screening (whether or how to be screened). The second population included people without cancer but with high risk of cancer, e.g., because they are suspected or known to have a hereditary cancer-related condition, such as the Lynch or von Hippel-Lindau syndromes, or are carriers of deleterious BRCA gene mutations. This group may face decisions about further diagnostic workup or about undergoing preventive interventions. The third population included patients diagnosed with early cancer, defined as being at a stage with favorable prognosis (typically local disease only) and where interventions have curative intent (e.g., stage IIa or lower for prostate cancer). We accepted the individual study claims for the definition of early cancer. When a study used an alternative cancer staging, we adjudicated an early cancer stage using information for the National Cancer Institute site. We included only studies in people who were legally able to make decisions for themselves or an underage minor. We followed the IPDAS collaboration and previous systematic reviews in defining decision aid-based interventions as, at a minimum, (1) informing about available options and the expected associated benefits and harms, and (2) incorporating at least implicit clarification of the decisionmaker’s values.3,4 ; Eligible Studies for Key Question 2: For the second Key Question, we included comparative studies informing on the effectiveness of interventions for promoting shared decision making to providers caring for the populations discussed for the first Key Question, specifically provider-targeted interventions to increase shared decision making with the use or increased use of a decision aid. Because so few studies have been done on this topic, eligible designs included randomized and cluster- randomized trials, nonrandomized studies with concurrent comparators, before-after studies, and interrupted time series studies.

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Telehealth for Acute and Chronic Care Consultations


Public Project Complete

Statistics: 216 Studies, 5 Key Questions, 1 Extraction Form,
Date Published: May 08, 2019 11:57AM
Description: Objectives: To conduct a systematic review to identify and summarize the available evidence about the effectiveness of telehealth consultations and to explore using decision modeling techniques to supplement the review. Telehealth consultations are defined as the use of telehealth to facilitate collaboration between two or more providers, often involving a specialist, or among clinical team members, across time and/or distance. Consultations may focus on the prevention, assessment, diagnosis, and/or clinical management of acute or chronic conditions. Data Sources. We searched Ovid MEDLINE®, the Cochrane Central Register of Controlled Trials (CCRCT), and the Cumulative Index to Nursing and Allied Health Literature (CINAHL®) to identify studies published from 1996 to May 2018. We also reviewed reference lists of identified studies and systematic reviews, and we solicited published or unpublished studies through an announcement in the Federal Register. Data for the model came both from studies identified via the systematic review and from other sources. Methods. We included comparative studies that provided data on clinical, cost, or intermediate outcomes associated with the use of any technology to facilitate consultations for inpatient, emergency, or outpatient care. We rated studies for risk of bias and extracted information about the study design, the telehealth interventions, and results. We assessed the strength of evidence and synthesized the findings using quantitative and qualitative methods. An exploratory decision model was developed to assess the potential economic impact of telehealth consultations for traumatic brain injuries in adults. Results. The search yielded 9,366 potentially relevant citations. Upon review, 8,356 were excluded and the full text of 1,010 articles was pulled for review. Of these, 233 articles met our criteria and were included—54 articles evaluated inpatient consultations, 73 emergency care, and 106 outpatient care. The overall results varied by setting and clinical topic, but generally the findings are that telehealth improved outcomes or that there was no difference between telehealth and the comparators. Remote intensive care unit (ICU) consultations likely reduce ICU and total hospital mortality with no significant difference in ICU or hospital length of stay; specialty telehealth consultations likely reduce the time patients spend in the emergency department; telehealth for emergency medical services likely reduces mortality for patients with heart attacks, and remote consultations for outpatient care likely improve access and a range of clinical outcomes (moderate strength of evidence in favor of telehealth). Findings with lower confidence are that inpatient telehealth consultations may reduce length of stay and costs; telehealth consultations in emergency care may improve outcomes and reduce costs due to fewer transfers and also may reduce outpatient visits and costs due to less travel (low strength of evidence in favor of telehealth). Current evidence reports no difference in clinical outcomes with inpatient telehealth specialty consultations, no difference in mortality but also no difference in harms with telestroke consultations, and no difference in satisfaction with outpatient telehealth consultations (low strength of evidence of no difference). Too few studies reported information on potential harms from outpatient telehealth consultations for conclusions to be drawn (insufficient evidence). An exploratory cost model underscores the importance of perspective and assumptions in using modeling to extend evidence and the need for more detailed data on costs and outcomes when telehealth is used for consultations. For example, a model comparing telehealth to transfers and in-person neurosurgical consultations for acute traumatic brain injury identified that the impact of telehealth on costs may depend on multiple factors including how alternatives are organized (e.g., if the telehealth and in-person options are part of the same health care system) and whether the cost of a telehealth versus an in-person consultation differ. Conclusions. In general, the evidence indicates that telehealth consultations are effective in improving outcomes or providing services with no difference in outcomes; however, the evidence is stronger for some applications, and less strong or insufficient for others. Exploring the use of a cost model underscored that the economic impact of telehealth consultations depends on the perspective used in the analysis. The increase in both interest and investment in telehealth suggests the need to develop a research agenda that emphasizes rigor and focuses on standardized outcome comparisons that can inform policy and practice decisions.
Contributor(s): Totten A, Hansen R, Wagner J, Stillman L, Ivlev I, Davis-O’Reilly C, Towle C, Erickson J, Erten-Lyons D, Fu R, Fann J, Babigumira J, Palm-Cruz K, Avery M, McDonagh M.
DOI: DOI pending.
Funding Source: Agency for Healthcare Research and Quality (AHRQ), Contract No. 290-2015-00009-I
Methodology Description: The conduct of this systematic review followed the Methods Guide for Effectiveness and Comparative Effectiveness Reviews, and it is reported according to the PRISMA checklist. The scope, Key Questions, and inclusion criteria of this review were developed in consultation with a group of technical experts. Detailed methods are available in the full report and the posted protocol. A research librarian created the search strategy and another research librarian reviewed it before searching Ovid MEDLINE®, the Cochrane Central Register of Controlled Trials (CCRCT), and the Cumulative Index to Nursing and Allied Health Literature (CINAHL®) to identify studies published from 1996 through May 2018. We also reviewed reference lists of identified studies and systematic reviews, and solicited suggestions through an announcement in the Federal Register. We limited our study inclusion to the use of telehealth for consultations and outcomes that measure clinical and cost effectiveness. Otherwise our criteria were broad, and we included any technology and any comparative study, including before-after and retrospective as well as prospective designs, with quantitative outcomes data. Studies could compare telehealth consultations to consultations done in a different mode (e.g., in-person or telephone), no access to specialty care, or usual care which could be an unspecified mix of these options. We excluded descriptive studies, studies assessing only diagnostic concordance, studies where there was no nontelehealth comparison, and modeling studies that used hypothetical data. Two team members independently reviewed all abstracts and two reviewers independently assessed each full-text article. Disagreements were resolved by discussion among investigators. For included articles, investigators abstracted key characteristics and data about the studies for quantitative and qualitative synthesis. We were able to conduct meta-analyses for some but not all topics and outcomes due to the heterogeneity of outcome measures, study designs, and telehealth interventions. Two investigators independently rated the risk of bias of each study using predefined criteria consistent with the chapter, “Assessing the Risk of Bias of Individual Studies When Comparing Medical Interventions” in the Methods Guide for Effectiveness and Comparative Effectiveness Reviews. Risk of bias for economic evaluations were assessed using a modified version of the Consensus Health Economic Criteria. Disagreements were resolved by consensus. Strength of evidence was assessed for each outcome and Key Question as described in the Methods Guide for Effectiveness and Comparative Effectiveness Reviews. We assigned a strength of evidence grade of high, moderate, low, or insufficient for the body of evidence for each Key Question, based on evaluation of four domains: study limitations, consistency, directness, and precision. High, moderate, and low ratings reflect our confidence in the accuracy and validity of the findings and whether future studies might alter these findings (magnitude or direction). We gave a rating of insufficient when we were unable to draw conclusions due to serious inconsistencies, serious methodological limitations, or lack of evidence.

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