Machine learning to predict myocardial injury and death after non-cardiac surgery

Myocardial injury due to ischaemia within 30 days of non-cardiac surgery is prognostically relevant. We aimed to determine the discrimination, calibration, accuracy, sensitivity and specificity of single-layer and multiple-layer neural networks for myocardial injury and death within 30 postoperative days. We analysed data from 24,589 participants in the Vascular Events in Non-cardiac Surgery Patients Cohort Evaluation study. Validation was performed on a randomly selected subset of the study population. Discrimination for myocardial injury by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.70 (0.69–0.72) vs. 0.71 (0.70–0.73) with variables available before surgical referral, p < 0.001; 0.73 (0.72–0.75) vs. 0.75 (0.74–0.76) with additional variables available on admission, but before surgery, p < 0.001; and 0.76 (0.75–0.77) vs. 0.77 (0.76–0.78) with the addition of subsequent variables, p < 0.001. Discrimination for death by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.71 (0.66–0.76) vs. 0.74 (0.71–0.77) with variables available before surgical referral, p = 0.04; 0.78 (0.73–0.82) vs. 0.83 (0.79–0.86) with additional variables available on admission but before surgery, p = 0.01; and 0.87 (0.83–0.89) vs. 0.87 (0.85–0.90) with the addition of subsequent variables, p = 0.52. The accuracy of the multiple-layer model for myocardial injury and death with all variables was 70% and 89%, respectively.     

Accuracy of direct examination and culture as compared to the anatomopathological examination for the diagnosis of chromoblastomycosis: a systematic review

BackgroundChromoblastomycosis is a skin infection caused by dematiaceous fungi that take the form of muriform cells in the tissue. It mainly manifests as verrucous plaques on the lower limbs of rural workers in tropical countries.ObjectivesThe primary objective of this review is to evaluate the accuracy of diagnostic methods for the identification of chromoblastomycosis, considering the histopathological examination as the reference test.MethodsMEDLINE, LILACS and Scielo databases were consulted using the terms “chromoblastomycosis” AND “diagnosis”. The eligibility criteria were: studies that evaluated the accuracy of tests for the diagnosis of chromoblastomycosis. Eleven studies were selected. Statistical analysis included the calculation of sensitivity and specificity of the diagnostic methods.ResultsConsidering the histopathological examination as the reference test, the culture showed a sensitivity (S) of 37.5% - 90.9% and a specificity (Sp) of 100%; while direct mycological examination showed S = 50% - 91.6% and Sp of 100% . Considering the culture as the reference test, the serology (precipitation techniques) showed S of 36% - 99%; and Sp of 80% - 100%; while the intradermal test showed S of 83.3% - 100% and Sp of 99.4% - 100%.Study limitationsThe small number of studies and very discrepant sensitivity results among them do not allow the calculation of summary measures through a meta-analysis.ConclusionsDirect mycological examination, culture, intradermal test and serology show sensitivity and specificity values ??for the diagnosis of chromoblastomycosis with no significant difference between the studies.