Aims/hypothesis Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10-20 times higher than that of people without type 2 diabetes. Prognostic... Show moreAims/hypothesis Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10-20 times higher than that of people without type 2 diabetes. Prognostic models can aid in targeted monitoring but an overview of their performance is lacking. This study aimed to systematically review prognostic models for the risk of foot ulcer or amputation and quantify their predictive performance in an independent cohort.Methods A systematic review identified studies developing prognostic models for foot ulcer or amputation over minimal 1 year follow-up applicable to people with type 2 diabetes. After data extraction and risk of bias assessment (both in duplicate), selected models were externally validated in a prospective cohort with a 5 year follow-up in terms of discrimination (C statistics) and calibration (calibration plots).Results We identified 21 studies with 34 models predicting polyneuropathy, foot ulcer or amputation. Eleven models were validated in 7624 participants, of whom 485 developed an ulcer and 70 underwent amputation. The models for foot ulcer showed C statistics (95% CI) ranging from 0.54 (0.54, 0.54) to 0.81 (0.75, 0.86) and models for amputation showed C statistics (95% CI) ranging from 0.63 (0.55, 0.71) to 0.86 (0.78, 0.94). Most models underestimated the ulcer or amputation risk in the highest risk quintiles. Three models performed well to predict a combined endpoint of amputation and foot ulcer (C statistics >0.75).Conclusions/interpretation Thirty-four prognostic models for the risk of foot ulcer or amputation were identified. Although the performance of the models varied considerably, three models performed well to predict foot ulcer or amputation and may be applicable to clinical practice. Show less
Huizinga, C.R.H.; Tummers, F.H.M.P.; Marang-van de Mheen, P.J.; Cohen, A.E.; Bogt, K.E.A. van der 2019
The need for data to study the relationship between fatigued healthcare professionals and performance outcomes is evident, however, it is unclear which methodology is most appropriate to provide... Show moreThe need for data to study the relationship between fatigued healthcare professionals and performance outcomes is evident, however, it is unclear which methodology is most appropriate to provide these insights. To address this issue, we performed a systematic review of relevant articles by searching the MEDLINE, EMBASE, Cochrane, Web of Science, and CINAHL databases. The literature search identified 2960 unique references, of which 82 were identified eligible. The impact on performance was studied on clinical outcomes, medical simulation, neurocognitive performance, sleep quantification and subjective assessment. In general results on performance are conflicting; impairment, no effect, and improvement were found. This review outlines the various methods currently available for assessing fatigue-impaired performance. The contrasting outcomes can be attributed to three main factors: differences in the operationalisation of fatigue, incomplete control data, and the wide variety in the methods used. We recommend the implementation of a clinically applicable tool that can provide uniform data. Until these data become available, caution should be used when developing regulations that can have implications for physicians, education, manpower planning, and - ultimately - patient care. (C) 2019 Elsevier Ltd. All rights reserved. Show less
Munter, L. de; Polinder, S.; Nieboer, D.; Lansink, K.W.W.; Steyerberg, E.W.; Jongh, M.A.C. de 2018
