Risk prediction and early intervention strategies for persistent SARS-CoV-2 infection in patients with non-Hodgkin lymphoma: a retrospective cohort study.

Background: Patients with non-Hodgkin lymphoma (NHL) face heightened mortality and accelerated disease progression when persistently infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This critical situation underscores the urgent need to identify risk factors and establish early intervention strategies tailored to this vulnerable population. The primary aim of this study was to investigate the risk factors associated with persistent SARS-CoV-2 infection in NHL patients during the COVID-19 pandemic.

The serum gamma-glutamyl transpeptidase-to-platelet ratio predicts HELLP syndrome.

Background: HELLP (Hemolysis, elevated liver enzymes, and low platelets) syndrome is a dangerous obstetric condition that is in great need of simple and inexpensive non-invasive early predictors, but it has been poorly studied. This study was conducted to investigate the predictive role of serum gamma-glutamyl transpeptidase to platelet ratio (GPR) during pregnancy in HELLP syndrome and its adverse pregnancy outcomes.

Methods: This was a retrospective study in a tertiary hospital.

Theoretical model and experimental verification of seepage-transition-spontaneous imbibition in water migration of water-injected coal.

Coal seam water injection is widely applied to prevent mine disasters. In the traditional water migration model of water-injected coal, from ignoring capillary force in the seepage stage to generating the capillary dynamic during the spontaneous imbibition state, no transition state exists from 0 to generating capillary force. In this paper, on the basis of theoretical analysis, an equivalent capillary term is introduced to modify the Forchheimer model, and then a seepage-transition-spontaneous imbibition model that is suitable for water migration of water-injected coal is proposed.

Machine learning-based prediction models for renal impairment in Chinese adults with hyperuricaemia: risk factor analysis.

In hyperuricaemic populations, multiple factors may contribute to impaired renal function. This study aimed to establish a machine learning-based model to identify characteristic factors related to renal impairment in hyperuricaemic patients, determine dose‒response relationships, and facilitate early intervention strategies. Data were collected through the big data platform of Nanjing Hospital of Traditional Chinese Medicine, encompassing 2,705 patients with hyperuricaemia (1,577 with renal impairment, 828 without) from June 2019 to June 2022.