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The use of non-invasive tools in conjunction with artificial intelligence (AI) to detect diseases has the potential to revolutionize healthcare. Near-infrared spectroscopy (NIR) is a technology that can be used to analyze biological samples in a non-invasive manner. This study evaluated the use of NIR spectroscopy in the fingertip to detect neutropenia in solid-tumor oncologic patients. A total of 75 patients were enrolled in the study. Fingertip NIR spectra and complete blood counts were collected from each patient. The NIR spectra were pre-processed using Savitzky–Golay smoothing and outlier detection. The pre-processed data were split into training/validation and test sets using the Kennard–Stone method. A toolbox of supervised machine learning classification algorithms was applied to the training/validation set using a stratified 5-fold cross-validation regimen. The algorithms included linear discriminant analysis (LDA), logistic regression (LR), random forest (RF), multilayer perceptron (MLP), and support vector machines (SVMs). The SVM model performed best in the validation step, with 85% sensitivity, 89% negative predictive value (NPV), and 64% accuracy. The SVM model showed 67% sensitivity, 82% NPV, and 57% accuracy on the test set. These results suggest that NIR spectroscopy in the fingertip, combined with machine learning methods, can be used to detect neutropenia in solid-tumor oncology patients in a non-invasive and timely manner. This approach could help reduce exposure to invasive tests and prevent neutropenic patients from inadvertently undergoing chemotherapy. [ABSTRACT FROM AUTHOR]

Contrast-induced acute kidney injury (CI-AKI) is a serious complication associated with considerable morbidity and mortality. Heat-shock protein 27 (HSP27) plays a role in the defense of the kidney tissue against various forms of cellular stress, including hypoxia and oxydative stress, both features associated with CI-AKI. The aim of our study was to evaluate a potential predictive value of HSP27 for CI-AKI in patients subjected to percutaneous coronary interventions (PCI). Included were 343 selected patients subjected to PCI. Exclusion criteria were conditions that potentially might influence HSP27 levels. HSP27 serum levels were evaluated prior to PCI, together with serum creatinine, the concentration of which was also evaluated twice at 48 and 72 h post PCI. CI-AKI was diagnosed in 9.3% of patients. Patients in whom CI-AKI was diagnosed were older (p < 0.001), were more often females (p = 0.021), had higher prevalence of diabetes (p = 0.011), hypotension during PCI (p < 0.001), albuminuria (p = 0.004) as well as multivessel disease (p = 0.002), received higher contrast volume (p = 0.006), more often received contrast volume (CV) above the maximum allowed contrast dose (MACD) (p < 0.001), and had lower HSP27 level (p < 0.001). On multivariate analysis, CV > MACD (OR 1.23, p = 0.001), number of diseased vessels (OR 1.27, p = 0.006), and HSP27 (OR 0.81, p = 0.001) remained independent predictors of CI-AKI. Low concentration of HSP27 is an emerging, strong and independent predictor of CI-AKI in patients subjected to PCI. [ABSTRACT FROM AUTHOR]