Ban, Jong-Wook;
Chan, Mei Sum;
Muthee, Tonny Brian;
Paez, Arsenio;
Stevens, Richard;
Perera, Rafael;
(2021)
Design, methods, and reporting of impact studies of cardiovascular clinical prediction rules are suboptimal: a systematic review.
Journal of Clinical Epidemiology
, 133
pp. 111-120.
10.1016/j.jclinepi.2021.01.016.
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Abstract
Objectives: To evaluate design, methods, and reporting of impact studies of cardiovascular clinical prediction rules (CPRs). Study Design and Setting: We conducted a systematic review. Impact studies of cardiovascular CPRs were identified by forward citation and electronic database searches. We categorized the design of impact studies as appropriate for randomized and nonrandomized experiments, excluding uncontrolled before-after study. For impact studies with appropriate study design, we assessed the quality of methods and reporting. We compared the quality of methods and reporting between impact and matched control studies. Results: We found 110 impact studies of cardiovascular CPRs. Of these, 65 (59.1%) used inappropriate designs. Of 45 impact studies with appropriate design, 31 (68.9%) had substantial risk of bias. Mean number of reporting domains that impact studies with appropriate study design adhered to was 10.2 of 21 domains (95% confidence interval, 9.3 and 11.1). The quality of methods and reporting was not clearly different between impact and matched control studies. Conclusion: We found most impact studies either used inappropriate study design, had substantial risk of bias, or poorly complied with reporting guidelines. This appears to be a common feature of complex interventions. Users of CPRs should critically evaluate evidence showing the effectiveness of CPRs.
| Type: | Article |
|---|---|
| Title: | Design, methods, and reporting of impact studies of cardiovascular clinical prediction rules are suboptimal: a systematic review |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.jclinepi.2021.01.016 |
| Publisher version: | https://doi.org/10.1016/j.jclinepi.2021.01.016 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Cardiovascular disease, Clinical prediction rule, Reporting guideline, Risk of bias, Study design, Adult, Aged, Aged, 80 and over, Cardiovascular Diseases, Clinical Decision Rules, Comparative Effectiveness Research, Decision Support Techniques, Female, Humans, Male, Middle Aged, Randomized Controlled Trials as Topic |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Applied Health Research UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10154718 |
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