A Systematic Review of Patient-reported Outcomes in Randomized Controlled Trials of Unplanned General Surgery
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- 作者：Daniel J. Stevens ; Natalie S. Blencowe ; Philip J. McElnay…
- 刊名：World Journal of Surgery
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：40
- 期：2
- 页码：267-276
- 全文大小：548 KB
- 刊物类别：Medicine
- 刊物主题：Medicine & Public Health
Surgery
Abdominal Surgery
Cardiac Surgery
General Surgery
Thoracic Surgery
Vascular Surgery - 出版者：Springer New York
- ISSN：1432-2323
文摘
Unplanned general surgery represents a major workload and requires comprehensive evaluation with appropriate outcomes. This study aimed to summarize current reporting of patient-reported outcomes (PROs) in randomized clinical trials (RCTs) in unplanned general surgery. A systematic review identified RCTs reporting PROs in the commonest six areas of unplanned general surgery. Details of the PRO measures were examined using the CONSORT extension for PRO reporting in RCTs. Extracted information about each PRO domain included the reporting of baseline PROs, rationale for PRO selection and whether PRO findings were used in conjunction with clinical outcomes to inform treatment recommendations. The internal validity of included studies was assessed using the Cochrane risk of bias tool. 12,519 abstracts were screened and 20 RCTs containing data from 2037 patients included. Included studies used 14 separate PRO measures covering 35 different health domains. A visual analogue assessment of pain was most frequently reported (n = 13). Reporting of baseline PRO data was uncommon (11/35 PRO domains). The rationale for PRO data collection and a PRO-specific hypothesis were provided for 9 (25.7 %) and 5 (14.3 %) domains, respectively. Seventeen RCTs (85.0 %) used the PRO data alongside clinical outcomes to inform treatment recommendations. Of the 116 risk of bias assessments, 77 (66.0 %) were judged as high or unclear. There is a lack of well designed, and conducted RCTs in unplanned general surgery that include PROs. Future work to define relevant PROs and methods for optimal assessment are needed to inform health care decision-making.