Medicine最新文献

Sepsis-associated encephalopathy (SAE) is common in the intensive care unit (ICU) and portends worse short- and long-term outcomes. To enable real-time bedside use and multicenter deployment, we aimed to develop a parsimonious, transparent day-1 prediction model using routinely available variables while preserving discrimination, calibration, and clinical utility. Using MIMIC-IV (2008-2022), we conducted a single-center retrospective study of adult sepsis patients with KDIGO-defined AKI. Predictors were restricted to the first 24 hours after ICU admission; the endpoint was any in-ICU SAE ("ever" vs "never"). After multiple imputation (m = 5), 44 baseline variables were standardized and entered into LASSO with 20-fold cross-validation. A 3-rule clinical screen (24 hours availability; non-treatment; low collinearity) distilled LASSO-selected features to a four-predictor logistic model; performance was internally validated (bootstrap) and compared with an XGBoost benchmark. SHAP analyses supported interpretability. Among 6780 ICU stays (training n = 4746; validation n = 2034), SAE occurred in 69.8%. The final 4 predictors were age, SAPS II, serum sodium, and mean arterial pressure (MAP). Discrimination was stable (AUC 0.734 training; 0.739 validation) with excellent calibration (validation CITL = -0.045; slope = 0.996; Brier = 0.182). Decision-curve analysis showed greater net benefit than XGBoost across thresholds 0.15 to 0.55; although AUCs were similar, XGBoost calibrated worse (CITL = -0.289; slope = 0.729). SHAP ranked contributions as SAPS II, sodium, age, and MAP, indicating a near-linear sodium-risk rise within 138 to 144 mmol/L, age-related risk above ~70 years, and a U-shaped MAP effect with protection around 55 to 75 mm Hg. We developed and validated a four-factor nomogram that uses only routine day-1 data to stratify SAE risk rapidly and transparently, outperforming a complex learner in calibration and net benefit. This parsimonious, interpretable tool highlights modifiable targets (sodium, individualized MAP) and provides a pragmatic foundation for multicenter validation and EMR-embedded early warning and intervention strategies.

This study aims to investigate the clinicopathological features and prognosis of brain metastasis in non-small cell lung cancer (NSCLC). A total of 80 patients with brain metastases from NSCLC admitted to our hospital from Jan 2021 to Dec 2023 were retrospectively selected as patients in the brain metastasis group. One hundred patients with NSCLC who were admitted during the same period were selected as patients with non-brain metastasis. The relationship between different clinicopathological characteristics of lung cancer and brain metastasis was analyzed, the survival curves of patients in the 2 groups were compared, and the prognostic impact was analyzed by univariate and multifactor Logistics regression. The differences were statistically significant among histological types, metastasis time, and gene mutations (P < .05). The results of single and multivariate Logistics regression analysis showed that age, smoking history, T-stage, and tumor node metastasis stage were independent factors influencing the prognostic outcome of patients with brain metastasis of NSCLC (P < .05). Age, smoking history, T-stage, and tumor node metastasis stage are independent influencing factors on the prognosis of patients with brain metastases from NSCLC, and intervention should be taken based on the influencing factors.

Using a retrospective cohort from the MIMIC-IV database, we aimed to investigate the independent association between the admission plasma glucose-to-lactate ratio (GLR) and 28-day all-cause mortality in adult sepsis patients with Escherichia coli bacteremia. We further characterized the shape of this relationship and assessed its consistency across clinically relevant subgroups. Adult patients with sepsis and confirmed E coli bacteremia from the Medical Information Mart for Intensive Care IV database were included. The association between GLR (analyzed both continuously and in quartiles) and 28-day mortality was assessed using multivariable Cox proportional hazards regression, adjusting for potential confounders. Subgroup analyses were performed. Among 395 included patients, 47 (11.9%) died within 28 days. Patients in the lowest GLR quartile (Q1, <43.5) had higher Sequential Organ Failure Assessment scores, lactate levels, and the highest mortality (22.2%). After multivariable adjustment, a higher GLR was independently associated with lower mortality (adjusted hazard ratio per 1-unit increase = 0.98, 95% confidence interval: 0.97-1.00). A nonlinear relationship was observed, with mortality risk decreasing steeply until a GLR of approximately 75. A lower admission GLR is an independent predictor of higher 28-day mortality in adults with E coli sepsis, exhibiting a nonlinear relationship. GLR may serve as a simple early prognostic marker for risk stratification in this patient population.

Erectile dysfunction (ED) is a common and serious condition. As people's lifestyles change and the aging of the population, the incidence of ED is increasing. traditional Chinese medicine (TCM) has long been a traditional clinical approach for treating ED in China and has been shown to be effective and safe. A large amount of studies on TCM for ED have revealed various therapeutic mechanisms; however, few reviews have summarized the TCM therapeutic mechanisms currently available for the treatment of ED. Therefore, a systematic analysis of the therapeutic mechanisms of TCM is of great academic and clinical value. Summarizing the molecular mechanisms of TCM for ED from multiple directions enriches the theory of TCM for ED and establishes the clinical significance and development prospect of TCM for ED. It provides basic theoretical support for the discovery and utilization of TCM resources, and provides up-to-date and comprehensive insights into the clinical application of TCM for the treatment of ED. This knowledge may pave the way for the development of more effective drugs and methods.

Some patients suspected of infection may have potential causes, such as tumors, but conventional examination methods are negative. Copy number variation (CNV) analysis based on metagenomics next generation sequencing (mNGS) can simultaneously detect pathogenic microorganisms and tumors signals. Patients with suspected infection in our department were retrospectively analyzed, and mNGS and chromosomal CNV analysis were performed simultaneously. A total of 9 patients with positive tumor signal were included in the study. This study was divided into 2 parts: in the first part, patients suspected of infection were finally diagnosed with a tumor by CNV assisted analysis; in the second part, the accuracy of this analysis was verified again by patients with a history of cancer. Three of five patients without a history of tumor were diagnosed with hematological malignancy. All patients with active tumor had obvious abnormal CNV signals. The chromosomal abnormalities mainly included multiple chromosome duplication and deletion, arm level duplication and deletion, and chromosome aneuploidy. mNGS-based CNV analysis had clinical value for patients with underlying tumor.

Rationale: Apalutamide is a generation androgen antagonist for the treatment of metastatic hormone sensitive prostate cancer and non-metastatic castration resistant prostate cancer. Skin adverse reactions caused by apalutamide are mostly rashes and maculopapules.

Patient concerns: There are a few reports about exfoliative dermatitis caused by apalutamide.

Diagnoses: Severe exfoliative dermatitis induced by apalutamide.

Interventions: Gamma globulin, cefoperazone sulbactam sodium, albumin, ebastine, loratadine, hydrocortisone cream, and 3% boric acid lotion.

Outcomes: Whole-body skin was red, without exudation, and with a small amount of desquamation.

Lessons: The incidence of exfoliative dermatitis due to apalutamide is low but severe, and if a serious adverse skin reaction is suspected, apalutamide needs to be discontinued immediately and treated accordingly.

This study aimed to identify lactylation-associated genes linked to immune infiltration and diagnostic potential in neuropathic pain using integrated bioinformatic and machine learning approaches. Two microarray datasets (GSE124272 and GSE150408) comprising peripheral blood transcriptomes from 25 NP patients and 25 healthy controls were obtained from the gene expression omnibus. After batch correction and merging, the combined dataset served as the training set. Differentially expressed genes overlapping with lactylation-related gene sets were identified. Functional enrichment analyses, including gene ontology and Kyoto encyclopedia of genes and genomes pathway analyses, were performed. A protein-protein interaction network was constructed. Three machine learning algorithms-least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest-were applied to identify robust diagnostic gene signatures. Subsequently, the candidate biomarkers were validated using an independent test set (GSE95849). A diagnostic nomogram was developed, and regulatory networks were analyzed. Immune infiltration analysis was conducted via cell-type identification by estimating relative subsets of RNA transcripts. Functional analyses indicated involvement of pathways such as glucagon signaling, thermogenesis, and mitochondrial inner membrane function. Machine learning-identified 5 diagnostic gene candidates: CYP27A1, ELAC2, TMEM126B, LYRM7, and PHKB. Among these, CYP27A1 and PHKB were further investigated in an independent test set. Immune infiltration analysis showed significant alterations in 19 immune cell types, with CYP27A1 and PHKB closely correlated with immune cell distribution. This study identified CYP27A1 and PHKB as potential lactylation-associated biomarkers for NP, offering new insights into its pathogenesis and a theoretical basis for improved diagnosis.

This study aims to explore the association between frailty scores (FS) and latent tuberculosis infection (LTBI) and analyze the impact of FS on all-cause mortality in the LTBI population, providing a reference for optimizing screening strategies in high-risk groups. A total of 3520 adults aged 18 to 79 years from the National Health and Nutrition Examination Survey 2011 to 2012 cycle were included, comprising 564 individuals in the LTBI group and 2956 in the non-LTBI group. LTBI was diagnosed through a combination of the tuberculin skin test and interferon-gamma release assays. The FS was constructed based on 53 health deficit indicators covering cognitive function, comorbidities, nutritional metrics, and laboratory parameters. The natural logarithm of FS was generated as natural logarithm of FS (LnFS). A multivariable logistic regression model was used to analyze the association between LnFS and LTBI, while Cox proportional hazards models assessed its impact on all-cause mortality. A mediation analysis was performed with LnFS as the exposure, LTBI as the outcome, and serum globulin concentration as the hypothesized mediator. The FS score was notably greater in the LTBI group than in the non-LTBI group (0.15 ± 0.09 vs 0.13 ± 0.08; P = .003). The association between LnFS and LTBI was stronger (odds ratio = 1.26, 95% confidence interval: 1.05-1.52, P = .016). Globulin partially mediated the link between LTBI and FS (12.5% mediation effect, P = .04). The risk of all-cause mortality was increased by 32% in LTBI patients (hazard ratio = 1.32, 95% confidence interval: 1.05-1.66), and this risk intensified in a dose-dependent manner with increasing FS scores (interaction P = .02). FS are significantly positively correlated with LTBI, and this relationship accelerates the frailty process through chronic inflammatory responses mediated by globulin. FS independently increases the risk of all-cause mortality. The findings provide scientific evidence for early frailty screening and targeted interventions in high-risk LTBI populations, while emphasizing the importance of serum globulin levels.

Durable glycemic control remains challenging in patients with type 2 diabetes mellitus inadequately controlled with metformin alone. Liraglutide, a glucagon-like peptide-1 receptor agonist, has been proposed as a beneficial add-on therapeutic option. This retrospective study included adults with type 2 diabetes mellitus treated between March 2021 and March 2025. Patients were divided into a combination group receiving liraglutide plus metformin and a control group receiving metformin alone. Glycemic parameters and safety outcomes were assessed at baseline and after 6 months of treatment. Statistical comparisons were conducted using Welch t test and Chi-square or Fisher exact test. A total of 207 patients were analyzed. Compared with metformin monotherapy, combination therapy achieved greater reductions in glycated hemoglobin (-1.8 ± 0.9% vs -1.3 ± 0.8%; P < .001), fasting and postprandial plasma glucose, fasting insulin, and homeostasis model assessment of insulin resistance. The proportion achieving composite glycemic targets was higher in the combination group (76.5% vs 57.9%; P = .006). Adverse event incidence and treatment discontinuation did not differ significantly between groups. Liraglutide add-on therapy provided superior glycemic improvement compared with metformin alone and demonstrated acceptable safety and tolerability.

Abnormally corrected serum calcium (sCa) levels are associated with poor outcomes in various diseases, yet their relationship with short-term mortality in sepsis patients remains underexplored. This study investigates the association between corrected sCa levels and 28-day mortality in sepsis patients. We analyzed data from 7627 sepsis patients in the electronic intensive care unit Collaborative Research Database, categorizing them into 4 groups based on corrected sCa levels. Multivariate logistic regression, subgroup analysis, restricted cubic splines, and segmented regression models assessed the relationship between corrected calcium levels and mortality. Kaplan-Meier curves compared survival probabilities across groups. The 28-day mortality rate was 15.94%. After adjusting for confounders, patients in the highest corrected sCa group (>10.5 mg/dL) exhibited a significantly increased mortality risk (hazard ratio [HR]: 1.642, 95% confidence interval: 1.278-2.109) compared to the reference group (8.5-9.5 mg/dL). A U-shaped relationship was noted, with an inflection point at 9.08 mg/dL. Below this point, each 1.0 mg/dL increase in corrected sCa reduced mortality risk by 7.0% (HR, 0.930). Above 9.08 mg/dL, each 1.0 mg/dL increase raised mortality risk by 21.3% (HR, 1.213). Both low and high corrected sCa levels are linked to increased 28-day mortality in sepsis patients, highlighting the importance of monitoring calcium levels in this population.