Development and validation of a nomogram for 30-day readmission after hip fracture surgery in geriatric patients.

OBJECTIVE: 30-day readmission after hip fracture surgery in the elderly is common and costly. A predictive tool to identify high-risk patients could significantly improve outcomes. This study aims to develop and validate a risk nomogram for 30-day readmission after hip fracture surgery in geriatric patients. PATIENTS AND METHODS: We retrospectively analyzed 1,249 geriatric hip fracture patients (≥60 years) undergoing surgery at Dandong Central Hospital from October 2011 to October 2023. Using a 7:3 ratio, patients were randomly divided into training (n=877) and validation (n=372) sets. Independent risk factors for 30-day readmission were identified using LASSO regression and logistic regression in the training set. A nomogram was constructed using the identified predictors. Finally, the C-index, ROC curve, calibration curve, and decision curve analysis were used to validate the model in the training and validation sets respectively. RESULTS: The nomogram was developed based on the 8 predictors of age, prior stroke, chronic liver disease, treatment, uric acid (UA), total protein (TP), albumin (ALB), and pneumonia that were found to be independently associated with 30-day readmission. The nomogram showed good discrimination with a C-index of 0.88 in the training set and 0.84 in the validation set. Calibration curves exhibited good agreement between predicted and observed outcomes. Decision curve analysis demonstrated clinical utility. CONCLUSIONS: We developed and validated a nomogram incorporating eight clinical variables to accurately predict the individualized risk of 30-day readmission after hip fracture surgery in elderly patients. The model demonstrated favorable discrimination, calibration, and clinical utility. It can help to identify high-risk patients needing additional interventions to prevent avoidable hospital readmissions.

Development and validation of a nomogram for urinary tract infection in geriatric patients with hip fracture: a retrospective study.

OBJECTIVE: This study aims to develop and validate a risk nomogram for urinary tract infections (UTIs) in geriatric patients with hip fractures. PATIENTS AND METHODS: A total of 900 geriatric patients who underwent hip fracture surgery at Dandong Central Hospital between June 2017 and June 2023 were systematically collected. The cohort was randomly divided into a training set (70%, n=632) and a validation set (30%, n=268) for model development and validation, respectively. Univariate and multivariate logistic regression analyses were conducted to identify the independent risk factors associated with UTIs. Based on the results of the multivariate analysis, a UTI nomogram prediction model was developed and evaluated in the training and validation sets using the C-index, ROC curve, calibration curve, and decision curve analysis to assess discrimination, calibration, and clinical utility, respectively. RESULTS: Out of the 900 participants, 24.6% were diagnosed with UTIs. The nomogram was developed based on 9 predictors that were found to be independently associated with UTI. The area under the curve (AUC) for predicting UTI in geriatric patients with hip fractures was 0.829 in the training set and 0.803 in the validation set. Following internal verification, the modified C-index remained at 0.829. Furthermore, the nomogram's calibration plot and decision curve analysis demonstrated good performance in both the training and validation sets. CONCLUSIONS: The established and validated nomogram provides a reliable and convenient tool for predicting UTI risk in geriatric patients with hip fractures. This model facilitates the early identification of high-risk patients and offers guidance for implementing targeted preventive interventions.

Development and validation of preoperative proximal and distal lower limb deep vein thrombosis nomograms in geriatric hip fracture patients.

OBJECTIVE: This study aimed to develop and validate a risk nomogram for preoperative proximal and distal deep vein thrombosis (DVT) in geriatric patients with hip fractures. PATIENTS AND METHODS: The 970 collected geriatric hip fracture patients were randomly divided into a training set (70%, n=682) and a validation set (30%, n=288). Multivariate logistic regression analyses were used to optimize the predictive risk variables for proximal and distal preoperative lower extremity DVT in the training set, respectively, and the selected variables were finally incorporated to establish preoperative DVT nomogram prediction models. Receiver operating characteristic curves (ROC), calibration plots, and decision curve analysis (DCA) were performed to validate the nomograms in the training and validation sets, respectively. RESULTS: Among the 970 patients, 125 (12.88%) were diagnosed with preoperative DVT. The area under the curve (AUC) for predicting preoperative proximal DVT was 0.888 in the training and 0.792 in the validation sets. The AUC for predicting preoperative distal DVT was 0.907 in the training and 0.790 in the validation sets. The calibration plots and decision curve analysis for preoperative proximal DVT performed well in the training set and slightly worse in the validation set. The calibration plots and decision curve analysis for preoperative distal DVT performed well in both the training and validation sets. CONCLUSIONS: To construct nomograms for predicting the risk of proximal and distal preoperative lower extremity DVT in geriatric hip fracture patients. For patients at high risk, as assessed by this model, clinicians should intervene and treat them promptly before surgery.

Is the Carotid Body a Metabolic Monitor?

The carotid body is a multi-modal sensor and it has been debated if it senses low glucose. We have hypothesized that the carotid body is modified by some metabolic factors other than glucose and contributes to whole body glucose metabolism. This study examined the roles of insulin, leptin and transient receptor potential (TRP) channels on carotid sinus nerve (CSN) chemoreceptor discharge. In agreement with other studies, CSN activity was not modified by low glucose. Insulin did not affect the CSN hypoxic response. Leptin significantly augmented the CSN response to hypoxia and nonspecific Trp channel blockers (SKF96365, 2-APB) reversed the effect of leptin. Gene expression analysis showed high expression of Trpm3, 6, and 7 channels in the carotid body and petrosal ganglion. The results suggest that the adult mouse carotid body does not sense glucose levels directly. The carotid body may contribute to neural control of glucose metabolism via leptin receptor-mediated TRP channel activation.

Hydroxymethylation as a Novel Environmental Biosensor.

Beyond the genome, epigenetics has become a promising approach in understanding the interactions between the gene and the environment. Epigenetic regulation includes DNA methylation, histone modifications, and non-coding RNAs. Among these, DNA methylation, which is the addition of a methyl group to the fifth base of cytosine to produce 5-methylcytosine (5-mC), is most commonly studied. Epigenetic regulation has changed given the discovery of 5-hydroxymethylcytosine (5-hmC), considered the "sixth base", and the nature of TET proteins to catalyze 5-mC oxidation to 5-hmC. 5-hydroxymethylation has been proposed to be a stable intermediate between methylation and demethylation and has raised questions about the functions of 5-hmC in gene regulation in cells, tissues, and organs in response to environmental exposure. Herein, we have provided an introduction to the chemistry of 5-hydroxymethylation, and the techniques for detection of 5-hydroxymethylation. In addition, we have reviewed current reports describing how 5-hmC responds to environmental factors, leading to the development of disease. And finally, we have discussed the potential use of 5-hmC in the study of disease development. All in all, it is our goal to provide innovative and convincing epigenetic studies for understanding the etiology of environmentally-related human disease, and translate these epigenetic findings into lifestyle recommendations and clinical practices to prevent and cure disease.

Measurement of GSTP1 promoter methylation in body fluids may complement PSA screening: a meta-analysis.

BACKGROUND: Prostate-specific antigen (PSA) screening has low specificity. Assessment of methylation status in body fluids may complement PSA screening if the test has high specificity. METHOD: The purpose of this study was to conduct a meta-analysis of the sensitivity and specificity for prostate cancer detection of glutathione-s-transferase-π (GSTP1) methylation in body fluids (plasma, serum, whole blood, urine, ejaculate, and prostatic secretions). We conducted a comprehensive literature search on Medline (Pubmed). We included studies if they met all four of the following criteria: (1) measurement of DNA methylation in body fluids; (2) a case-control or case-only design; (3) publication in an English journal; and (4) adult subjects. Reviewers conducted data extraction independently using a standardised protocol. Twenty-two studies were finally included in this paper. Primer sequences and methylation method in each study were summarised and evaluated using meta-analyses. This paper represents a unique cross-disciplinary approach to molecular epidemiology. RESULTS: The pooled specificity of GSTP1 promoter methylation measured in plasma, serum, and urine samples from negative-biopsy controls was 0.89 (95% CI, 0.80-0.95). Stratified analyses consistently showed a high specificity across different sample types and methylation methods (include both primer sequences and location). The pooled sensitivity was 0.52 (95% CI, 0.40-0.64). CONCLUSIONS: The pooled specificity of GSTP1 promoter methylation measures in plasma, serum, and urine was excellent and much higher than the specificity of PSA. The sensitivity of GSTP1 was modest, no higher than that of PSA. These results suggest that measurement of GSTP1 promoter methylation in plasma, serum, or urine samples may complement PSA screening for prostate cancer diagnosis.