Medicine
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Observational Study
Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.
Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work was to develop a ML model to predict 30-day all-cause rehospitalizations based on the French hospital medico-administrative database. ⋯ In contrast, LR was superior to CART (H-measure = 0.16, AUC = 0.70), P < .0001. The use of ML may be an alternative to regression models to predict health outcomes. The integration of ML, particularly the RF algorithm, in the prediction of unplanned rehospitalization may help health service providers target patients at high risk of rehospitalizations and propose effective interventions at the hospital level.
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Only a few cases of accidental deaths due to speargun injuries are reported in the literature. Murder or suicide cases are even rarer. ⋯ The investigation into unusual cases of death constitutes a complex matter and requires a careful evaluation on the part of the forensic pathologist. A differential diagnosis may be necessary in order to rule out simulated suicide/homicide. In this particular case, the analysis of the scene of the self-suppression event and available circumstantial information, the evaluation of clinical data, the complete autopsy and the comparison between the injuries of the victim and the characteristics of the weapon used led to the confirmation of the suicidal nature of the death.
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Observational Study
Genotyping and antiretroviral drug resistance of human immunodeficiency Virus-1 in Jazan, Saudi Arabia.
Determination of human immunodeficiency virus-1 (HIV-1) genotypes and identification of antiretroviral drug-resistant mutations. Among treatment naïve HIV patients in Jazan, Saudi Arabia. HIV is a major public health problem. ⋯ Mutations conferring resistance to NNRTI were detected in 5.3% of cases. Mutations associated with antiretroviral drugs include (V82A+I84IV), (L10F+Q58E), (L10F+V82Y), L10FV, L33LF, L89LMV, M184V, E138A, V106I, and V179VD. The prevalence of HIV-1 antiretroviral resistance mutations is 22.8% in the studied population, which may warrant antiretroviral drug resistance testing as a pretreatment to help and guide physicians for the proper HIV treatment.
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Observational Study
Excessive splenic volume is an unfavorable prognostic factor in patients with non-small cell lung cancer treated with chemoradiotherapy.
The relationship between splenic volume and the outcome of chemoradiotherapy for lung cancer has rarely been studied or addressed. The purpose of our study was to investigate whether splenic volume was associated with prognosis in patients treated with chemoradiotherapy for advanced or locally advanced non-small cell lung cancer (NSCLC). A retrospective investigation was conducted. ⋯ In multivariate analyses, splenic volume remained an independent predictor of OS as a binary dependent variable (P = .003). Excessive splenic volume was associated with decreased OS and DFS in patients with NSCLC treated with chemoradiotherapy. Splenic volume should be regarded as an independent prognostic factor for patients treated with chemoradiotherapy for advanced or locally advanced NSCLC.
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Observational Study
Corona Virus Disease 2019 patients with different disease severity or age range: A single-center study of clinical features and prognosis.
This study aimed to describe clinical characteristics and prognosis of Corona Virus Disease 2019 (COVID-19) patients, and to compare these features among COVID-19 patients with different disease severity or age range. Totally, 129 COVID-19 patients were retrospectively enrolled, and the information about demographics, comorbidities, medical histories, clinical symptoms, and laboratory findings at the time of hospital admission were collected. Meanwhile, their clinical outcomes were recorded. ⋯ Subgroup analyses disclosed that severe/critical patients exhibited increased neutrophil count, neutrophils, C-reactive protein, calcitonin, alpha-hydroxybutyric dehydrogenase, lactate dehydrogenase, aspartate aminotransferase, gamma-glutamyl transferase, creatinine, and D-dimer levels, and more deaths compared with that in moderate patients. Regarding age, it correlated with more common fever, higher levels of red blood cell, neutrophil count, lymphocyte count, neutrophils, red cell volume distribution width standard deviation-coefficient of variation, calcitonin, alpha-hydroxybutyric dehydrogenase, Creatine Kinase, aspartate aminotransferase, gamma-glutamyl transferase, and D-dimer, raised death rate and prolonged hospital stay. Our findings provide valuable evidence regarding clinical characteristics and prognosis of COVID-19 patients to help with the understanding of the disease and prognosis improvement.