Objective:To construct a nomogram model for predicting the occurrence of acute kidney injury (AKI) in patients with cardiac arrest (CA) after cardiopulmonary resuscitation (CPR), and to verify its validity for early prediction.Methods:The study retrospectively included patients aged 18 years and older who received CPR for CA and were admitted to the emergency room of Tianjin Medical University General Hospital from February 2016 to September 2023. The general information, underlying diseases, resuscitation related indicators, and first laboratory test results of patients were collected. The patients were randomly divided into training and validation groups at a ratio of 7:3. AKI diagnosis was based on the diagnostic criteria of the Kidney Disease Improving Global Outcomes. Univariate and multivariate logistic regression models were used to identify independent risk factors for AKI in patients with cardiac arrest, and a nomogram was constructed on the basis of the independent risk factors. The predictive performance was evaluated by the area under the curve (AUC) of the receiver operating characteristic. The calibration curve, decision curve and clinical impact curve were used to evaluate the model. Bootstrap and cross validation methods were used for internal validation.Results:A total of 527 patients with cardiac arrest were included in the study, 230 patients developed AKI, with an AKI incidence of 43.6%. There was no statistically significant difference in clinical baseline data between the training and validation groups (all P>0.05), indicating comparability between the two groups of data. Multivariate logistic analysis revealed that age ( OR=1.346, 95% CI: 1.197-1.543, P<0.001), CA to CPR time ( OR=2.214, 95% CI: 1.512-3.409, P=0.016), adrenaline dosage ( OR=1.921, 95% CI: 1.383-2.783, P=0.004), APACHE-Ⅱ score ( OR=1.531, 95% CI: 1.316-1.820, P<0.001), baseline creatinine ( OR=1.137, 95% CI: 1.090-1.196, P<0.001), and lactate ( OR=2.558, 95% CI: 1.680-4.167, P<0.001) were the independent risk factors for AKI in patients with cardiac arrest. Initial defibrillable rhythm ( OR=0.214, 95% CI: 0.051-0.759, P=0.023) was a protective factor for AKI in patients with cardiac arrest. A nomogram prediction model was constructed based on the above variables. The AUC of the training group was 0.943 (95% CI: 0.921-0.965) and that of the validation group was 0.917 (95% CI: 0.874-0.960). This prediction model demonstrated good discrimination, calibration and clinical applicability. Conclusions:A nomogram predictive model was constructed on the basis of age, CA to CPR time, initial defibrillable rhythm, adrenaline dosage, the APACHE-Ⅱ score, and baseline creatinine and lactate levels. This nomogram has good predictive value for the early occurrence of AKI in patients with cardiac arrest after cardiopulmonary resuscitation, which can provide new strategies for the early identification of AKI and precise intervention.

Objective:To develop and validate an interactive network dynamic nomogram for early prediction of poor neurological prognosis in patients with post-cardiac arrest brain injury (PCABI).Methods:A retrospective study was conducted on hospitalized patients who achieved return of spontaneous circulation after cardiac arrest at Tianjin Medical University General Hospital between January 2020 and April 2024. Patients were classified into favorable and poor prognosis groups based on the Glasgow-Pittsburgh Cerebral Performance Category at discharge. Eligible patients were randomly assigned to a training cohort and an internal validation cohort in a 7:3 ratio. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of poor neurological outcomes in PCABI, which were subsequently used to develop a nomogram prediction model. The predictive performance of the nomogram was evaluated by comparing its area under the curve (AUC) of receiver operating characteristic with those of individual predictors using the DeLong test. Model calibration and clinical utility were assessed using calibration curves and decision curve analysis, respectively. Internal validation was conducted, and an interactive dynamic nomogram was developed using web-based visualization techniques.Results:A total of 276 PCABI patients were enrolled (training set: 196; validation set: 80), with 82 cases (29.7%) classified as poor prognosis. Multivariate logistic regression analysis identified age ( OR=1.071, 95% CI: 1.021-1.124, P=0.005), APACHEⅡ score ( OR=1.746, 95% CI: 1.393-2.190, P<0.001), initial shockable rhythm ( OR=0.142, 95% CI: 0.025-0.819, P=0.029), defibrillation ( OR=0.228, 95% CI: 0.060-0.869, P=0.030), cardiopulmonary resuscitation duration ( OR=2.116, 95% CI: 1.487-3.010, P<0.001), and lactate level ( OR=1.392, 95% CI: 1.005-1.927, P=0.047) as independent predictors of poor neurological outcomes in PCABI. A nomogram prediction model was developed based on these factors, achieving an AUC of 0.965 (95% CI: 0.939-0.989) in the training cohort and 0.987 (95% CI: 0.967-1.000) in the internal validation cohort. The nomogram demonstrated significantly superior predictive performance compared to individual predictors ( P<0.001) and exhibited excellent discrimination, calibration, and clinical net benefit. The interactive dynamic nomogram, developed through web-based visualization, further enhanced its applicability in clinical practice. Conclusions:The interactive network dynamic nomogram, developed based on age, APACHEⅡ score, initial shockable rhythm, defibrillation, cardiopulmonary resuscitation duration, and lactate level, demonstrated favorable predictive value for poor neurological outcomes in PCABI. This tool facilitates clinical application and offers a novel strategy for early identification and targeted interventions in high-risk patients.

Objective To explore depression and anxiety in nasopharyngeal carcinoma (NPC) patients in Chaoshan region and investigate their influencing factors. Methods Two hundred and one patients newly diagnosed with NPC were included in this study. The status of depression and anxiety during their hospital stay were evaluated using the self-rating depression scale (SDS) and the self-rating anxiety scale (SAS). Data including sex, age, education, history of smoking, course of disease, sleeping quality and oral pain were also collected and their relationships with depression and anxiety were analyzed as well. Results They had significantly higher mean SAS score (36.41 ± 7.41) and SDS score (48.42 ± 7.19), as compared with the healthy population. Single factor analysis indicated that age, education, history of smoking, course of disease, sleeping quality, and oral pain had significant impact on the scores of SAS and SDS. Multivariate logistics regression analysis indicated that age, education, history of smoking, course of disease, sleeping quality, and oral pain had significant impact on their anxiety and depression. Conclusions Depression and anxiety are common psychological problems in NPC patients. Patients at the middle to elderly age and with low education, history of smoking, bad sleeping quality and oral pain are more susceptible to depression and anxiety.

Objective To investigate the differences of clinicopathologic characteristics and prognosis between young and old age patients with rectal cancer. Methods From January 1996 to January 2006, 85 young patients(age≤40 years) and 155 older patients(age≥65 years)with rectal cancer were surgically treated. The clinicopathological and follow-up data of them were retrospectively analyzed and compared by survival analysis and COX regression multivariate analysis. Results Rectal cancer under peritoneal in young group were higher than that in older group (69.41 % vs 52.90 %, P =0.013). The young group had significantly higher frequencies of pooly differentiated carcinoma (31.76 % vs 18.71 %, P =0.023) and more mucinous adenocarcinoma as well as signet-ring cell carcinoma (22.35 % vs 8.39 %, P =0.007), There were more lymphatic metastasis in young group than that in old group (N_1+N_2: 63.53 % vs 47.10 %, P =0.015). The overall 5-year survival rates were 48.2 % and 55.7 % in young and old patients respectively, which was not significantly different (P =0.176). COX regression showed that radical operation, tumor infiltration depth,lymph node metastasis and TNM stage were independent prognostic factors. Conclusion As compared to the old age patients, more malignancy and more advanced stage are common in young patients with rectal cancer.However the efficacy of young patients is similar to the older counters by early detection and radical operation combined radiotherapy as well as chemotherapy.