Objectives. Hypothermia is highly common in patients undergoing gynecological surgeries under general anesthesia, so the length of hospitalization and even the risk of mortality are substantially increased. Our aim was to develop a simple and practical model to preoperatively identify gynecological surgery patients at risk of intraoperative hypothermia. Methods. In this retrospective study, we collected data from 802 patients who underwent gynecological surgery at three medical centers from June 2022 to August 2023. We further allocated the patients to a training group, an internal validation group, or an external validation group. The preliminary predictive factors for intraoperative hypothermia in gynecological patients were determined using the least absolute shrinkage and selection operator (LASSO) method. The final predictive factors were subsequently identified through multivariate logistic regression analysis, and a nomogram for predicting the occurrence of hypothermia was established. Results. A total of 802 patients were included, with 314 patients in the training cohort (mean age 48.5 +/- 12.6 years), 130 patients in the internal validation cohort (mean age 49.9 +/- 12.5 years), and 358 patients in the external validation cohort (mean age 47.6 +/- 14.0 years). LASSO regression and multivariate logistic regression analyses indicated that body mass index, minimally invasive surgery, baseline heart rate, baseline body temperature, history of previous surgery, and aspartate aminotransferase level were associated with intraoperative hypothermia in gynecological surgery patients. This nomogram was constructed based on these six variables, with a C-index of 0.712 for the training cohort.

Purpose: T helper cells play essential roles in anti-tumor immune response. However, the postoperative changes of peripheral T cell subsets and their clinical significance in breast cancer patients remain largely unknown. Methods: We evaluated the perioperative changes of T lymphocyte subsets in invasive breast cancer (IBC) patients and breast fibroadenoma (BF) patients preoperatively (preop) and 6, 24, 72 hours postoperatively (POH6, POH24, and POH72). Proportions of CD3, CD4, CD8, T helper (Th) 1, Th2, Th17 cells, regulatory T cells (Treg), and CD4⁺/CD8⁺, Th1/Th2 ratio were detected by flow cytometry. Changes in T helper cell quantity were correlated to clinicopathological parameters. Furthermore, we explored the association between the perioperative variations of T cell subsets and disease-free survival (DFS) of IBC patients. Results: In IBC patients, Th1 cells diminished while Tregs elevated in postoperative 72 hours in the peripheral blood. In contrast, no significant perioperative changes of T cell subsets were observed in BF patients. Postoperative lower Th1 cells at POH 72 of IBC patients were correlated with greater tumor burden, HER2 positive and Ki67 positive. The increased Tregs at POH 72 of IBC patients were correlated with larger tumor size and HER2 positive. Th1 cell decline and Treg increment were both associated with shorter DFS in IBC patients. Conclusions: The variations of peripheral T helper cell subsets showed postoperative immunosuppression and were associated with poor prognosis in IBC patients.

Long noncoding RNAs have emerged as key players in the progression of head and neck squamous cell carcinoma (HNSC). Among them, ZEB1-AS1 was identified as

Intraoperative hypothermia is a prevalent complication that may significant clinical and economic burdens. Previous risk assessment models have demonstrated limitations in accurately predicting intraoperative hypothermia, particularly in diverse surgical populations. This study aims to develop and validate a model in adult surgical patients to improve outcomes. This retrospective cohort study utilized data extracted from electronic medical records and anaesthesia information management systems between June 2022 and August 2023. The analysis included information of 3,405 adult surgical patients from three independent centres in China who underwent elective surgical procedures with body temperature monitoring. Intraoperative hypothermia was defined as a core temperature below 36 °C during surgery. The Least Absolute Shrinkage and Selection Operator (LASSO) regression employed to select optimal features and multivariate logistic regression was used to identify independent predictors of intraoperative hypothermia and then built the risk assessment model. We further evaluated the discriminative ability, calibration curves, and clinical utility of the predictive model. The total incidences of intraoperative hypothermia in adult surgical patients were 42.5%. The predictors in the intraoperative hypothermia model included: age, BMI, baseline HR, baseline temperature, minimally invasive surgery, smoking, previous surgery and serum creatine level. In the training cohort, the model demonstrated strong discriminatory ability, with C-index values of 0.721 (95% CI 0.697-0.744). Internal and external validation further confirmed the model's robustness and generalizability. These findings suggest that our model may help us more accurately identify patients at risk of intraoperative hypothermia. China Clinical Trial Registration Center (ChiCTR2300071859), Date registered May/26/2023.