Sep 14, 2024
Protocol: Evaluation of the quality of reporting and risk of bias of predictive models widely used in UK perioperative practice
- Joseph Alderman1
- 1University of Birmingham
External link: http://www.periopprediction.co.uk
Protocol Citation: Joseph Alderman 2024. Protocol: Evaluation of the quality of reporting and risk of bias of predictive models widely used in UK perioperative practice. protocols.io https://dx.doi.org/10.17504/protocols.io.ewov19bwylr2/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
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Created: September 13, 2024
Last Modified: September 14, 2024
Protocol Integer ID: 107593
Keywords: Predictive models, prognostic models, healthcare, medicine, surgery, anaesthesia, anesthesiology, uk perioperative practice the aim, uk perioperative practice, perioperative practice, validation study, development of predictive model, systematic review, systematic review of the evidence, future research study, policy recommendation, predictive model, design of future research study, future research, methodological robustness of study, clinical context, literature review, targeted literature review, actionable recommendations for future development
Abstract
The aim of this targeted literature review is to critically appraise the reporting and methodological robustness of studies describing the development of predictive models which are most widely used in UK perioperative practice. This is not intended to be a systematic review of the evidence supporting each model - more a review of the state of evidence in general to inform the design of future research studies and develop policy recommendations.
Objectives include:
- Apply the TRIPOD+AI and PROBAST frameworks to papers describing development of predictive models used frequently in perioperative practice.
- Summarise the clinical context and population groups represented in any development and validation datasets.
- Identify the ‘intended use’ of PMCS being investigated.
- Identify actionable recommendations for future development/validation studies by comparing limitations across literature sources.
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