Accuracy and clinical effectiveness of risk prediction tools for pressure injury occurrence: An umbrella review

Background Pressure injuries (PIs) pose a substantial healthcare burden and incur significant costs worldwide. Several risk prediction models to allow timely implementation of preventive measures and potentially reduce healthcare system burden are available and in use. The ability of risk prediction tools to correctly identify those at high risk of PI (prognostic accuracy) and to have a clinically significant impact on patient management and outcomes (effectiveness) is not clear. We aimed to evaluate the prognostic accuracy and clinical effectiveness of risk prediction tools for PI, and to identify gaps in the literature. Methods and Findings The umbrella review was conducted according to Cochrane guidance. MEDLINE, Embase, CINAHL, EPISTEMONIKOS, Google Scholar and reference lists were searched to identify relevant systematic reviews. Risk of bias was assessed using adapted AMSTAR-2 criteria. Results were described narratively. We identified 16 reviews that assessed prognostic accuracy and 10 that assessed clinical effectiveness of risk prediction tools for PI. The 16 reviews of prognostic accuracy evaluated 63 tools (39 scales and 24 machine learning models), with the Braden, Norton, Waterlow, Cubbin-Jackson scales (and modifications thereof) the most evaluated tools. Meta-analyses from a focused set of included reviews showed that the scales had sensitivities and specificities ranging from 53%-97% and 46%-84%, respectively. Only 2/16 reviews performed appropriate statistical synthesis and quality assessment. One review assessing machine learning based algorithms reported high prognostic accuracy estimates, but some of which were sourced from the same data within which the models were developed, leading to potentially overoptimistic results. Two randomised trials assessing the effect of PI risk assessment tools on incidence of PIs were identified from the 10 systematic reviews of clinical effectiveness; both were included in a Cochrane review and assessed as high risk of bias. Both trials found no evidence of an effect on PI incidence. Conclusions Our findings underscore the lack of high-quality evidence for the accuracy of risk prediction tools for PI. There is no reliable evidence to suggest that using existing risk prediction tools effectively reduces the incidence of PIs. Further research is needed on their clinical effectiveness, but only once promising prediction tools have been developed and appropriately validated. ### Competing Interest Statement VV is an employee of Paul Hartmann AG; ES and THB received consultancy fees from Paul Hartmann AG. All other authors received no personal funding or personal compensation from Paul Hartmann AG and have declared that no competing interests exist. ### Clinical Protocols ### Funding Statement This work was commissioned and supported by Paul Hartmann AG (Heidenheim, Germany). The contract with the University of Birmingham was agreed on the legal understanding that the authors had the freedom to publish results regardless of the findings. YT, JD, BH, KS and AC are funded by the National Institute for Health and Care Research (NIHR) Birmingham Biomedical Research Centre (BRC). This paper presents independent research supported by the NIHR Birmingham BRC at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript and supplementary file