Staphylococcus aureus bacteremia in alcoholics.

BACKGROUND: Alcoholism associates with increased Staphylococcus aureus bacteremia incidence and mortality. The objective was to compare disease progression, treatment and prognosis of Staphylococcus aureus bacteremia in alcoholics versus non-alcoholics. METHODS: The study design was a multicenter retrospective analysis of methicillin-sensitive Staphylococcus aureus bacteremia with 90-day follow-up. Patients were stratified as alcoholics or non-alcoholics based on electronic health record data. Altogether 617 Staphylococcus aureus bacteremia patients were included of which 83 (13%) were alcoholics. RESULTS: Alcoholics, versus non-alcoholics, were younger, typically male and more commonly had community-acquired Staphylococcus aureus bacteremia. No differences in McCabe´s classification of underlying conditions was observed. Higher illness severity at blood culture sampling, including severe sepsis (25% vs. 7%) and intensive care unit admission (39% vs. 17%), was seen in alcoholics versus non-alcoholics. Clinical management, including infectious disease specialist (IDS) consultations and radiology, were provided equally. Alcoholics, versus non-alcoholics, had more pneumonia (49% vs. 35%) and fewer cases of endocarditis (7% vs. 16%). Mortality in alcoholics versus non-alcoholics was significantly higher at 14, 28 and 90 days (14% vs. 7%, 24% vs. 11% and 31% vs. 17%), respectively. Considering all prognostic parameters, male sex (OR 0.19, p = 0.021) and formal IDS consultation (OR 0.19, p = 0.029) were independent predictors of reduced mortality, whereas ultimately or rapidly fatal comorbidity in McCabe´s classification (OR 12.34, p < 0.001) was an independent predictor of mortality in alcoholics. CONCLUSIONS: Alcoholism deteriorates Staphylococcus aureus bacteremia prognosis, and our results suggests that this is predominantly through illness severity at bacteremia onset. Three quarters of Staphylococcus aureus bacteremia patients we studied had identified deep infection foci, and of them alcoholics had significantly less endocarditis but nearly half of them had pneumonia.

Deep Learning Algorithms for Corneal Amyloid Deposition Quantitation in Familial Amyloidosis.

OBJECTIVES: The aim of this study was to train and validate deep learning algorithms to quantitate relative amyloid deposition (RAD; mean amyloid deposited area per stromal area) in corneal sections from patients with familial amyloidosis, Finnish (FAF), and assess its relationship with visual acuity. METHODS: Corneal specimens were obtained from 42 patients undergoing penetrating keratoplasty, stained with Congo red, and digitally scanned. Areas of amyloid deposits and areas of stromal tissue were labeled on a pixel level for training and validation. The algorithms were used to quantify RAD in each cornea, and the association of RAD with visual acuity was assessed. RESULTS: In the validation of the amyloid area classification, sensitivity was 86%, specificity 92%, and F-score 81. For corneal stromal area classification, sensitivity was 74%, specificity 82%, and F-score 73. There was insufficient evidence to demonstrate correlation (Spearman's rank correlation, -0.264, p = 0.091) between RAD and visual acuity (logMAR). CONCLUSIONS: Deep learning algorithms can achieve a high sensitivity and specificity in pixel-level classification of amyloid and corneal stromal area. Further modeling and development of algorithms to assess earlier stages of deposition from clinical images is necessary to better assess the correlation between amyloid deposition and visual acuity. The method might be applied to corneal dystrophies as well.