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Article ; Online: Pharmacologic and Dietary Treatments for Epilepsies in Children Aged 1-36 Months: A Systematic Review.

Treadwell, Jonathan R / Kessler, Sudha Kilaru / Wu, Mingche / Abend, Nicholas S / Massey, Shavonne / Tsou, Amy Y

2022

Abstract: Background and objectives: Early-life epilepsies are common and often debilitating, but no evidence-based management guidelines exist outside of those for infantile spasms. We conducted a systematic review of effectiveness and harms of pharmacologic and ...

Abstract	Background and objectives: Early-life epilepsies are common and often debilitating, but no evidence-based management guidelines exist outside of those for infantile spasms. We conducted a systematic review of effectiveness and harms of pharmacologic and dietary treatments for epilepsy in children aged 1-36 months without infantile spasms. Methods: We searched EMBASE, MEDLINE, PubMed, and the Cochrane Library for studies published from 1/1/1999 to 8/19/21. Using prespecified criteria, we identified studies reporting data on children aged 1-36 months receiving pharmacologic or dietary treatments for epilepsy. We did not require that studies report etiology-specific data. We excluded studies of neonates, infantile spasms, and status epilepticus. We included studies administering one of 29 pharmacologic treatments and/or one of five dietary treatments reporting effectiveness outcomes at ≥ 12 weeks. We reviewed the full text to find any subgroup analyses of children age 1-36 months. Results: Twenty-three studies met inclusion criteria (6 randomized studies, 2 non-randomized comparative studies, and 15 pre-post studies). All conclusions were rated Low strength of evidence. Levetiracetam leads to seizure freedom in some infants (32% and 66%, respectively in studies reporting seizure freedom), but data on six other medications were insufficient to permit conclusions about effectiveness (topiramate, lamotrigine, phenytoin, vigabatrin, rufinamide, and stiripentol). Three medications (levetiracetam, topiramate, and lamotrigine) were rarely discontinued due to adverse effects, and severe events were rare. For diets, the ketogenic diet leads to seizure freedom in some infants (rates 12%-37%), and both the ketogenic diet and modified Atkins diet reduce average seizure frequency, but reductions are greater with the ketogenic diet (one RCT reported a 71% frequency reduction at six months for ketogenic diet, vs. only a 28% reduction for the modified Atkins diet). Dietary harms were not well-reported. Discussion: Little high-quality evidence exists on pharmacologic and dietary treatments for early-life epilepsies. Future research should isolate how treatments contribute to outcomes, conduct etiology-specific analyses, and report patient-centered outcomes such as hospitalization, neurodevelopment, functional performance, sleep quality, and patient and caregiver quality of life. Registration: This systematic review was registered in PROSPERO (CRD42021220352) on March 5, 2021.
Language	English
Publishing date	2022-10-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/WNL.0000000000201026
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Article ; Online: Surgical Treatments for Epilepsies in Children Aged 1-36 Months: A Systematic Review.

Tsou, Amy Y / Kessler, Sudha Kilaru / Wu, Mingche / Abend, Nicholas S / Massey, Shavonne / Treadwell, Jonathan R

Neurology

2022

Abstract: Objectives: Early-life epilepsies (epilepsies in children 1 to 36 months old) are common and may be refractory to anti-seizure medications. We summarize findings of a systematic review commissioned by the American Epilepsy Society to assess evidence and ...

Abstract	Objectives: Early-life epilepsies (epilepsies in children 1 to 36 months old) are common and may be refractory to anti-seizure medications. We summarize findings of a systematic review commissioned by the American Epilepsy Society to assess evidence and identify evidence gaps for surgical treatments for epilepsy in children aged 1 to 36 months without infantile spasms. Methods: EMBASE, MEDLINE, PubMed, and the Cochrane Library were searched for studies published from 1/1/1999 to 8/19/21. We included studies reporting data on children aged 1 month to ≤ 36 months undergoing surgical interventions or neurostimulation for epilepsy and enrolling ≥ 10 patients per procedure. We excluded studies of infants with infantile spasms or status epilepticus. For effectiveness outcomes (seizure freedom, seizure frequency), studies were required to report follow-up at ≥ 12 weeks. For harm outcomes, no minimum follow-up was required. Outcomes for all epilepsy types, regardless of etiology were reported together. Results: Eighteen studies (in 19 articles) met inclusion criteria. Sixteen pre/post studies reported on efficacy and twelve studies addressed harms. Surgeries were performed from 1979 to 2020. Seizure freedom for infants undergoing hemispherectomy/hemispherotomy ranged from 7% to 76% at 1 year after surgery. For non-hemispheric surgeries seizure freedom ranged from 40% to 70%. For efficacy, we concluded low strength of evidence suggests some infants achieve seizure freedom after epilepsy surgery. Over half of infants undergoing hemispherectomy/hemispherotomy achieved a favorable outcome (Engel I or II, ILAE I to IV, or >50% seizure reduction) at follow-up of >1 year, although studies had key limitations.Surgical mortality was rare for functional hemispherectomy/hemispherotomy, and non-hemispheric resections. Low strength of evidence suggests post-operative hydrocephalus is uncommon for infants undergoing non-hemispheric procedures for epilepsy. Conclusion: Although existing evidence remains sparse and low quality, some infants achieve seizure freedom after surgery and ≥50% achieve favorable outcomes. Future prospective studies in this age group are needed. In addition to seizure outcomes, studies should evaluate other important outcomes (developmental outcomes, quality of life [QOL], sleep, functional performance, and caregiver QOL). Registration: This systematic review was registered in PROSPERO (CRD42021220352) on March 5, 2021.
Language	English
Publishing date	2022-10-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	207147-2
ISSN	1526-632X ; 0028-3878
ISSN (online)	1526-632X
ISSN	0028-3878
DOI	10.1212/WNL.0000000000201012
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Article ; Online: Pre-diabetes as a contributor to stroke.

Treadwell, Jonathan R

BMJ (Clinical research ed.)

2012 Volume 344, Page(s) e3285

MeSH term(s)	Diabetes Mellitus, Type 2/epidemiology ; Humans ; Prediabetic State/epidemiology ; Stroke/epidemiology
Language	English
Publishing date	2012-06-07
Publishing country	England
Document type	Comment ; Editorial
ZDB-ID	1362901-3
ISSN	1756-1833 ; 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
ISSN (online)	1756-1833
ISSN	0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
DOI	10.1136/bmj.e3285
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Article ; Online: Consumer Devices for Patient-Generated Health Data Using Blood Pressure Monitors for Managing Hypertension: Systematic Review.

Treadwell, Jonathan R / Rouse, Benjamin / Reston, James / Fontanarosa, Joann / Patel, Neha / Mull, Nikhil K

JMIR mHealth and uHealth

2022 Volume 10, Issue 5, Page(s) e33261

Abstract: Background: In the era of digital health information technology, there has been a proliferation of devices that collect patient-generated health data (PGHD), including consumer blood pressure (BP) monitors. Despite their widespread use, it remains ... ...

Abstract	Background: In the era of digital health information technology, there has been a proliferation of devices that collect patient-generated health data (PGHD), including consumer blood pressure (BP) monitors. Despite their widespread use, it remains unclear whether such devices can improve health outcomes. Objective: We performed a systematic review of the literature on consumer BP monitors that collect PGHD for managing hypertension to summarize their clinical impact on health and surrogate outcomes. We focused particularly on studies designed to measure the specific effect of using a BP monitor independent of cointerventions. We have also summarized the process and consumer experience outcomes. Methods: An information specialist searched PubMed, MEDLINE, and Embase for controlled studies on consumer BP monitors published up to May 12, 2020. We assessed the risk of bias using an adapted 9-item appraisal tool and performed a narrative synthesis of the results. Results: We identified 41 different types of BP monitors used in 49 studies included for review. Device engineers judged that 38 (92%) of those devices were similar to the currently available consumer BP monitors. The median sample size was 222 (IQR 101-416) participants, and the median length of follow-up was 6 (IQR 3-12) months. Of the included studies, 18 (36%) were designed to isolate the clinical effects of BP monitors; 6 of the 18 (33%) studies evaluated health outcomes (eg, mortality, hospitalizations, and quality of life), and data on those outcomes were unclear. The lack of clarity was due to low event rates, short follow-up duration, and risk of bias. All 18 studies that isolated the effect of BP monitors measured both systolic and diastolic BP and generally demonstrated a decrease of 2 to 4 mm Hg in systolic BP and 1 to 3 mm Hg in diastolic BP compared with non-BP monitor groups. Adherence to using consumer BP monitors ranged from 38% to 89%, and ease of use and satisfaction ratings were generally high. Adverse events were infrequent, but there were a few technical problems with devices (eg, incorrect device alerts). Conclusions: Overall, BP monitors offer small benefits in terms of BP reduction; however, the health impact of these devices continues to remain unclear. Future studies are needed to examine the effectiveness of BP monitors that transmit data to health care providers. Additional data from implementation studies may help determine which components are critical for sustained BP improvement, which in turn may improve prescription decisions by clinicians and coverage decisions by policy makers.
MeSH term(s)	Blood Pressure ; Blood Pressure Monitors ; Humans ; Hypertension/diagnosis ; Hypertension/therapy ; Quality of Life ; Sphygmomanometers
Language	English
Publishing date	2022-05-02
Publishing country	Canada
Document type	Journal Article ; Review ; Systematic Review ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	2719220-9
ISSN	2291-5222 ; 2291-5222
ISSN (online)	2291-5222
ISSN	2291-5222
DOI	10.2196/33261
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The Impact of Health Care Algorithms on Racial and Ethnic Disparities : A Systematic Review.

Siddique, Shazia Mehmood / Tipton, Kelley / Leas, Brian / Jepson, Christopher / Aysola, Jaya / Cohen, Jordana B / Flores, Emilia / Harhay, Michael O / Schmidt, Harald / Weissman, Gary E / Fricke, Julie / Treadwell, Jonathan R / Mull, Nikhil K

Annals of internal medicine

2024 Volume 177, Issue 4, Page(s) 484–496

Abstract: Background: There is increasing concern for the potential impact of health care algorithms on racial and ethnic disparities.: Purpose: To examine the evidence on how health care algorithms and associated mitigation strategies affect racial and ethnic ...

Abstract	Background: There is increasing concern for the potential impact of health care algorithms on racial and ethnic disparities. Purpose: To examine the evidence on how health care algorithms and associated mitigation strategies affect racial and ethnic disparities. Data sources: Several databases were searched for relevant studies published from 1 January 2011 to 30 September 2023. Study selection: Using predefined criteria and dual review, studies were screened and selected to determine: 1) the effect of algorithms on racial and ethnic disparities in health and health care outcomes and 2) the effect of strategies or approaches to mitigate racial and ethnic bias in the development, validation, dissemination, and implementation of algorithms. Data extraction: Outcomes of interest (that is, access to health care, quality of care, and health outcomes) were extracted with risk-of-bias assessment using the ROBINS-I (Risk Of Bias In Non-randomised Studies - of Interventions) tool and adapted CARE-CPM (Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models) equity extension. Data synthesis: Sixty-three studies (51 modeling, 4 retrospective, 2 prospective, 5 prepost studies, and 1 randomized controlled trial) were included. Heterogenous evidence on algorithms was found to: a) reduce disparities (for example, the revised kidney allocation system), b) perpetuate or exacerbate disparities (for example, severity-of-illness scores applied to critical care resource allocation), and/or c) have no statistically significant effect on select outcomes (for example, the HEART Pathway [history, electrocardiogram, age, risk factors, and troponin]). To mitigate disparities, 7 strategies were identified: removing an input variable, replacing a variable, adding race, adding a non-race-based variable, changing the racial and ethnic composition of the population used in model development, creating separate thresholds for subpopulations, and modifying algorithmic analytic techniques. Limitation: Results are mostly based on modeling studies and may be highly context-specific. Conclusion: Algorithms can mitigate, perpetuate, and exacerbate racial and ethnic disparities, regardless of the explicit use of race and ethnicity, but evidence is heterogeneous. Intentionality and implementation of the algorithm can impact the effect on disparities, and there may be tradeoffs in outcomes. Primary funding source: Agency for Healthcare Quality and Research.
MeSH term(s)	Humans ; Retrospective Studies ; Prospective Studies ; Healthcare Disparities ; Ethnicity ; Quality of Health Care
Language	English
Publishing date	2024-03-12
Publishing country	United States
Document type	Systematic Review ; Journal Article ; Review
ZDB-ID	336-0
ISSN	1539-3704 ; 0003-4819
ISSN (online)	1539-3704
ISSN	0003-4819
DOI	10.7326/M23-2960
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Book ; Online: Imaging for the pretreatment staging of small cell lung cancer

Treadwell, Jonathan R

(Comparative effectiveness review ; number 174 ; AHRQ publication ; no. 16-EHC015-EF)

2016

Abstract: OBJECTIVES: For small cell lung cancer (SCLC), several imaging modalities can be used to determine cancer staging, which is important to ensure optimal management. Our aim was to synthesize the literature on whether some imaging modalities are better ... ...

Institution	ECRI Institute-Penn Medicine Evidence-based Practice Center, United States. / Agency for Healthcare Research and Quality,
Author's details	prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by ECRI-Penn Evidence-based Practice Center ; investigators, Jonathan R. Treadwell, Matthew D. Mitchell, Amy Tsou, Drew Torigian, Charu Aggarwal, Karen M. Schoelles
Series title	Comparative effectiveness review ; number 174 AHRQ publication ; no. 16-EHC015-EF
Abstract	OBJECTIVES: For small cell lung cancer (SCLC), several imaging modalities can be used to determine cancer staging, which is important to ensure optimal management. Our aim was to synthesize the literature on whether some imaging modalities are better than others for the pretreatment staging of small cell lung cancer. We searched for evidence on comparative accuracy (sensitivity, specificity) as well as subsequent clinical outcomes (choice of treatment, survival, and quality of life). DATA SOURCES: We searched EMBASE, MEDLINE, PubMed, and the Cochrane Library from 2000 through June 15, 2015, for full-length articles on the use of multidetector computed tomography (MDCT), positron emission tomography/computed tomography (PET/CT), magnetic resonance imaging (MRI), combined PET/MRI, endobronchial ultrasound (EBUS), endoscopic ultrasound with fine-needle aspiration (EUS-FNA), and bone scintigraphy in the pretreatment staging of small cell lung cancer. REVIEW METHODS: We included studies of pertinent imaging tests on SCLC patients before treatment that reported one or more of the outcomes of interest (studies did not have to directly compare two or more imaging modalities). We extracted data from the included studies and constructed evidence tables. Comparative outcomes of interest included test concordance, staging accuracy (sensitivity and specificity), choice of treatment, timeliness of treatment, tumor response, harms due to overtreatment or undertreatment, survival, and quality of life. For each pair of tests and each assessed aspect (e.g., determination of metastases), we determined whether the evidence was sufficient to permit a conclusion of a difference, a conclusion of similar accuracy, or neither (i.e., insufficient). We rated the risk of bias of individual studies using an internal validity instrument and graded the overall strength of evidence of conclusions using Evidence-Based Practice Center guidance. RESULTS: The searches identified 2,880 citations; after screening against the inclusion criteria, we included seven primary studies that enrolled a total of 408 patients. Six of the seven studies were deemed moderate risk of bias (principally due to failure to report on patient selection, reader blinding to results of comparator tests, and possible spectrum bias), and one was deemed high risk of bias (due to failure to blind readers to results of comparator tests and presence of spectrum bias). One of the studies reported test concordance, three studies reported the comparative accuracy of two or more testing strategies (one of which had also reported test concordance), and four studies reported the accuracy of a single imaging modality. Staging determinations included limited versus extensive disease, osseous (bone or bone marrow) metastases, lymph node involvement, liver metastases, spleen metastases, adrenal metastases, brain metastases, and any distant metastases. The most frequently reported imaging tests were MDCT, [18F]-fluorodeoxyglucose (FDG) PET/CT, and bone scintigraphy. No studies were included for any other outcomes or for associations with patient comorbidity, body habitus, or tumor characteristics. CONCLUSIONS: Evidence is sparse on imaging modalities in the pretreatment staging of small cell lung cancer. Nevertheless, we drew three conclusions about comparative accuracy: (1) FDG PET/CT is more sensitive than MDCT for detecting osseous metastases; (2) FDG PET/CT is more sensitive than bone scintigraphy for detecting osseous metastases; (3) Standard staging plus FDG PET/CT is more sensitive than standard staging alone for detecting any distant metastases. We assigned a grade of low to the strength of evidence for these conclusions, mostly due to risk of bias and a small number of studies. Research gaps include the dearth of evidence on several tests of interest (particularly MRI, EBUS, EUS, and PET/MRI), a lack of study designs to compare tests on patient-oriented outcomes such as survival, and a lack of data on whether comparative accuracy or effectiveness are associated with patient factors.
MeSH term(s)	Small Cell Lung Carcinoma/diagnosis ; Diagnostic Imaging ; Comparative Effectiveness Research
Language	English
Size	1 online resource (1 PDF file (various pagings)) :, illustrations.
Document type	Book ; Online
Database	Catalogue of the US National Library of Medicine (NLM)

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Article ; Online: Machine learning for screening prioritization in systematic reviews: comparative performance of Abstrackr and EPPI-Reviewer.

Tsou, Amy Y / Treadwell, Jonathan R / Erinoff, Eileen / Schoelles, Karen

Systematic reviews

2020 Volume 9, Issue 1, Page(s) 73

Abstract: Background: Improving the speed of systematic review (SR) development is key to supporting evidence-based medicine. Machine learning tools which semi-automate citation screening might improve efficiency. Few studies have assessed use of screening ... ...

Abstract	Background: Improving the speed of systematic review (SR) development is key to supporting evidence-based medicine. Machine learning tools which semi-automate citation screening might improve efficiency. Few studies have assessed use of screening prioritization functionality or compared two tools head to head. In this project, we compared performance of two machine-learning tools for potential use in citation screening. Methods: Using 9 evidence reports previously completed by the ECRI Institute Evidence-based Practice Center team, we compared performance of Abstrackr and EPPI-Reviewer, two off-the-shelf citations screening tools, for identifying relevant citations. Screening prioritization functionality was tested for 3 large reports and 6 small reports on a range of clinical topics. Large report topics were imaging for pancreatic cancer, indoor allergen reduction, and inguinal hernia repair. We trained Abstrackr and EPPI-Reviewer and screened all citations in 10% increments. In Task 1, we inputted whether an abstract was ordered for full-text screening; in Task 2, we inputted whether an abstract was included in the final report. For both tasks, screening continued until all studies ordered and included for the actual reports were identified. We assessed potential reductions in hypothetical screening burden (proportion of citations screened to identify all included studies) offered by each tool for all 9 reports. Results: For the 3 large reports, both EPPI-Reviewer and Abstrackr performed well with potential reductions in screening burden of 4 to 49% (Abstrackr) and 9 to 60% (EPPI-Reviewer). Both tools had markedly poorer performance for 1 large report (inguinal hernia), possibly due to its heterogeneous key questions. Based on McNemar's test for paired proportions in the 3 large reports, EPPI-Reviewer outperformed Abstrackr for identifying articles ordered for full-text review, but Abstrackr performed better in 2 of 3 reports for identifying articles included in the final report. For small reports, both tools provided benefits but EPPI-Reviewer generally outperformed Abstrackr in both tasks, although these results were often not statistically significant. Conclusions: Abstrackr and EPPI-Reviewer performed well, but prioritization accuracy varied greatly across reports. Our work suggests screening prioritization functionality is a promising modality offering efficiency gains without giving up human involvement in the screening process.
MeSH term(s)	Evidence-Based Medicine ; Humans ; Machine Learning ; Mass Screening ; Research ; Systematic Reviews as Topic
Language	English
Publishing date	2020-04-02
Publishing country	England
Document type	Journal Article
ZDB-ID	2662257-9
ISSN	2046-4053 ; 2046-4053
ISSN (online)	2046-4053
ISSN	2046-4053
DOI	10.1186/s13643-020-01324-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Quality and clarity in systematic review abstracts: an empirical study.

Tsou, Amy Y / Treadwell, Jonathan R

Research synthesis methods

2016 Volume 7, Issue 4, Page(s) 447–458

Abstract: Background: Systematic review (SR) abstracts are important for disseminating evidence syntheses to inform medical decision making. We assess reporting quality in SR abstracts using PRISMA for Abstracts (PRISMA-A), Cochrane Handbook, and Agency for ... ...

Abstract	Background: Systematic review (SR) abstracts are important for disseminating evidence syntheses to inform medical decision making. We assess reporting quality in SR abstracts using PRISMA for Abstracts (PRISMA-A), Cochrane Handbook, and Agency for Healthcare Research & Quality guidance. Methods: We evaluated a random sample of 200 SR abstracts (from 2014) comparing interventions in the general medical literature. We assessed adherence to PRISMA-A criteria, problematic wording in conclusions, and whether "positive" studies described clinical significance. Results: On average, abstracts reported 60% of PRISMA-A checklist items (mean 8.9 ± 1.7, range 4 to 12). Eighty percent of meta-analyses reported quantitative measures with a confidence interval. Only 49% described effects in terms meaningful to patients and clinicians (e.g., absolute measures), and only 43% mentioned strengths/limitations of the evidence base. Average abstract word count was 274 (SD 89). Word count explained only 13% of score variability. PRISMA-A scores did not differ between Cochrane and non-Cochrane abstracts (mean difference 0.08, 95% confidence interval -1.16 to 1.00). Of 275 primary outcomes, 48% were statistically significant, 32% were not statistically significant, and 19% did not report significance or results. Only one abstract described clinical significance for positive findings. For "negative" outcomes, we identified problematic simple restatements (20%), vague "no evidence of effect" wording (9%), and wishful wording (8%). Conclusions: Improved SR abstract reporting is needed, particularly reporting of quantitative measures (for meta-analysis), easily interpretable units, strengths/limitations of evidence, clinical significance, and clarifying whether negative results reflect true equivalence between treatments. Copyright © 2016 John Wiley & Sons, Ltd.
MeSH term(s)	Abstracting and Indexing/standards ; Databases, Bibliographic ; Decision Making ; Empirical Research ; Periodicals as Topic/standards ; Publishing/standards ; Quality Control ; Research Design ; Systematic Reviews as Topic ; United States ; United States Agency for Healthcare Research and Quality
Language	English
Publishing date	2016-10-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2548499-0
ISSN	1759-2887 ; 1759-2879
ISSN (online)	1759-2887
ISSN	1759-2879
DOI	10.1002/jrsm.1221
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Machine learning for screening prioritization in systematic reviews

Amy Y. Tsou / Jonathan R. Treadwell / Eileen Erinoff / Karen Schoelles

Systematic Reviews, Vol 9, Iss 1, Pp 1-

comparative performance of Abstrackr and EPPI-Reviewer

2020 Volume 14

Abstract: Abstract Background Improving the speed of systematic review (SR) development is key to supporting evidence-based medicine. Machine learning tools which semi-automate citation screening might improve efficiency. Few studies have assessed use of screening ...

Abstract	Abstract Background Improving the speed of systematic review (SR) development is key to supporting evidence-based medicine. Machine learning tools which semi-automate citation screening might improve efficiency. Few studies have assessed use of screening prioritization functionality or compared two tools head to head. In this project, we compared performance of two machine-learning tools for potential use in citation screening. Methods Using 9 evidence reports previously completed by the ECRI Institute Evidence-based Practice Center team, we compared performance of Abstrackr and EPPI-Reviewer, two off-the-shelf citations screening tools, for identifying relevant citations. Screening prioritization functionality was tested for 3 large reports and 6 small reports on a range of clinical topics. Large report topics were imaging for pancreatic cancer, indoor allergen reduction, and inguinal hernia repair. We trained Abstrackr and EPPI-Reviewer and screened all citations in 10% increments. In Task 1, we inputted whether an abstract was ordered for full-text screening; in Task 2, we inputted whether an abstract was included in the final report. For both tasks, screening continued until all studies ordered and included for the actual reports were identified. We assessed potential reductions in hypothetical screening burden (proportion of citations screened to identify all included studies) offered by each tool for all 9 reports. Results For the 3 large reports, both EPPI-Reviewer and Abstrackr performed well with potential reductions in screening burden of 4 to 49% (Abstrackr) and 9 to 60% (EPPI-Reviewer). Both tools had markedly poorer performance for 1 large report (inguinal hernia), possibly due to its heterogeneous key questions. Based on McNemar’s test for paired proportions in the 3 large reports, EPPI-Reviewer outperformed Abstrackr for identifying articles ordered for full-text review, but Abstrackr performed better in 2 of 3 reports for identifying articles included in the final report. For small reports, both ...
Keywords	Machine learning ; Citation screening ; Text-mining ; Abstrackr ; EPPI-Reviewer ; Screening prioritization ; Medicine ; R
Subject code	670
Language	English
Publishing date	2020-04-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Narrative Review and Proposed Framework for Using Health System Data with Systematic Reviews to Support Decision-making.

Lin, Jennifer S / Murad, M Hassan / Leas, Brian / Treadwell, Jonathan R / Chou, Roger / Ivlev, Ilya / Kansagara, Devan

Journal of general internal medicine

2020 Volume 35, Issue 6, Page(s) 1830–1835

Abstract: Systematic reviews are a necessary, but often insufficient, source of information to address the decision-making needs of health systems. In this paper, we address when and how the use of health system data might make systematic reviews more useful to ... ...

Abstract	Systematic reviews are a necessary, but often insufficient, source of information to address the decision-making needs of health systems. In this paper, we address when and how the use of health system data might make systematic reviews more useful to decision-makers. We describe the different ways in which health system data can be used with systematic reviews, identify scenarios in which the addition of health system data may be most helpful (i.e., to improve the strength of evidence, to improve the applicability of evidence, and to inform the implementation of evidence), and discuss the importance of framing the limitations and considerations when using unpublished health system data in reviews. We developed a framework to guide the use of health system data alongside systematic reviews based on a narrative review of the literature and empirical experience. We also offer recommendations to improve the transparency of reporting when using health system data alongside systematic reviews including providing rationale for employing additional data, details on the data source, critical appraisal to understand study design biases as well as limitations in data and information quality, and how the unpublished data compares to the systematically reviewed data. Future methodological work on how best to handle internal and external validity concerns of health system data in the context of systematically reviewed data and work on developing infrastructure to do this type of work is needed.
MeSH term(s)	Government Programs ; Humans ; Research Design
Language	English
Publishing date	2020-04-01
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, U.S. Gov't, P.H.S. ; Review
ZDB-ID	639008-0
ISSN	1525-1497 ; 0884-8734
ISSN (online)	1525-1497
ISSN	0884-8734
DOI	10.1007/s11606-020-05783-5
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Kategorien

Order via subito

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Inter-library loan at ZB MED

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In stock of ZB MED Cologne/Königswinter

Order via subito