Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

OBJECTIVE: To investigate the current status of long-term quality of life in patients with severe acute pancreatitis (SAP) who have been cured and discharged, and to analyze the influencing factors affecting long-term quality of life in SAP cured patients after discharge. METHODS: A retrospective collection was conducted. Patients who were received standardized treatment before being cured and discharged from the hospital admitted to the first department of critical care medcine of the Second Affiliated Hospital of Anhui Medical University from January 2017 to December 2023 were enrolled. According to the 36-item short form health survey scale (SF-36) score, patients were divided into high score group (high quality of life, the top 50% of patients with total SF-36 score) and low score group (low quality of life, the bottom 50% of patients with total SF-36 score). The gender, age, history of hypertension and diabetes, etiology of pancreatitis, acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), CT severity index (CTSI), laboratory indicators such as C-reactive protein (CRP), procalcitonin (PCT), blood glucose, and triglycerides upon admission, use of vasoactive drugs, non-invasive/high-flow ventilation, invasive ventilation, retroperitoneal puncture and drainage, open pancreatic surgery treatment and secondary infection during hospitalization were collected, as well as the retention of abdominal drainage tubes at discharge from hospital. Distribute follow-up questionnaires or telephone follow-up surveys through WeChat and Question Star programs to investigate the pancreatic secretion function, chronic abdominal pain, and recurrence of pancreatitis of patients after discharge. Multivariable Logistic regression was used to analyze the relevant factors affecting the long-term quality of life of cured patients with SAP. RESULTS: A total of 86 patients were ultimately enrolled. There were 43 patients in both the high and low score groups. Among 86 patients, 20 experienced acute pancreatitis recurrence, with a recurrence rate of 23.26%. Twenty-two (25.58%) experienced chronic abdominal pain after discharge, and 5 patients (5.81%) needed medication to relieve pain. Thirty-three patients (38.37%) had pancreatic exocrine dysfunction after discharge, characterized by abdominal distension, constipation or diarrhea. Twenty-two patients (25.58%) suffered from pancreatic endocrine dysfunction, and were diagnosed with diabetes. Univariate analysis showed that compared with the high score group, the low score group had more patients with hypertension, initial renal dysfunction, initial severe metabolic acidosis, initial serum calcium < 2.0 mmol/L, blood glucose > 11.1 mmol/L and cultured Gram positive bacteria (from blood/body fluid/pancreatic necrotic tissue) during treatment (48.84% vs. 16.28%, 60.47% vs. 32.56%, 18.60% vs. 4.65%, 88.37% vs. 62.79%, 55.81% vs. 30.23%, 34.88% vs. 13.95%), had higher CTSI score (6.60±1.61 vs. 5.77±1.32), lower hemoglobin level at discharge (g/L: 102.30±18.78 vs. 110.72±16.68), and a lower proportion of etiological interventions after discharge (34.88% vs. 67.44%), the differences were statistically significant (all P < 0.05). Multivariate Logistic regression analysis showed that hypertension [odds ratio (OR) = 4.814, 95% confidence interval (95%CI) was 1.196-19.378], initial serum calcium < 2.0 mmol/L (OR = 6.688, 95%CI was 1.321-33.873) and initial blood glucose > 11.1 mmol/L (OR = 6.473, 95%CI was 1.399-29.950) were risk factors for long-term quality of life in cured SAP patients (all P < 0.05), while post discharge prophylactic intervention was a protective factor for long-term quality of life (OR = 0.092, 95%CI was 0.020-0.425, P < 0.01). CONCLUSIONS Cured SAP patients have varying degrees of impaired secretion function and the possibility of recurrence of acute pancreatitis. Hypertension, initial serum calcium < 2.0 mmol/L and blood glucose > 11.1 mmol/L are independent influencing factors for low long-term quality of life in cured SAP patients. Prevention and intervention targeting the etiology of pancreatitis after discharge can improve the long-term quality of life of cured SAP patients.
Humans ; Quality of Life ; Retrospective Studies ; Pancreatitis/therapy* ; Patient Discharge ; Male ; Female ; Middle Aged ; APACHE ; Adult ; Acute Disease ; Aged

Objective:To explore the effect of sleep deprivation on hair growth cycle in mice.Methods:Seventy-two adult C57BL/6J mice were randomly divided into a control group of 36 mice and an experimental group of 36 mice using a lottery method. After hair removal, in the control the group the mice were subjected to routine feeding in a horizontal platform environment for 16 hours per day, while in the experimental group the mice were subjected to sleep deprivation using an improved water platform for 16 hours per day. On the 1st, 9th, and 19th day after the experiment, the skin tissue from the hair removal area of the two groups of mice was taken for HE staining. Then the mouse hair was staged and scored by observing hair follicle morphology under an optical microscope. The cycle and score of the hair was started from the telogen, which was set as 0 points; the anagen Ⅰ to V were set as 1-5 points; the anagen Ⅵ and catagen Ⅰ were set as 6 points; the catagen Ⅱ to Ⅷ were set at 7-13 points. Statistical analysis was conducted by SPSS 26.0. The hair cycle score was expressed as Mean±SD. Student’s t-test was used for comparison between groups at the same time point, and Welch-test was used for comparison of scores at different time points within the group. P<0.05 indicated a statistically significant difference. Results:On the 1st, 9th, and 19th day, the hair cycle scores of the control group were 1.00 ± 0.57, 5.04 ± 0.94, and 9.52 ± 0.87 points, while the hair cycle scores of the experimental group were 0.85 ± 0.62, 2.40 ± 0.50 and 6.08 ± 0.42 points. Inter group comparison showed that the hair cycle scores of the experimental group were lower than those of the control group at all three time points. There was no statistically significant difference on the 1st day ( t=1.03, P=0.307), while the differences were statistically significant on the 9th day ( t=13.38, P<0.001) and the 19th day ( t=16.41, P<0.001). Intragroup comparison showed that there was a statistically significant difference in hair cycle scores between the control group and the experimental group at different time points( P<0.01), and the scores increased over time. Conclusion:Sleep deprivation can cause a lag in the hair growth cycle of mice, but it does not cause a cessation of the hair growth cycle. The degree of lag gradually increases with the number of deprivation days.

Objective:To explore the effect of sleep deprivation on hair growth cycle in mice.Methods:Seventy-two adult C57BL/6J mice were randomly divided into a control group of 36 mice and an experimental group of 36 mice using a lottery method. After hair removal, in the control the group the mice were subjected to routine feeding in a horizontal platform environment for 16 hours per day, while in the experimental group the mice were subjected to sleep deprivation using an improved water platform for 16 hours per day. On the 1st, 9th, and 19th day after the experiment, the skin tissue from the hair removal area of the two groups of mice was taken for HE staining. Then the mouse hair was staged and scored by observing hair follicle morphology under an optical microscope. The cycle and score of the hair was started from the telogen, which was set as 0 points; the anagen Ⅰ to V were set as 1-5 points; the anagen Ⅵ and catagen Ⅰ were set as 6 points; the catagen Ⅱ to Ⅷ were set at 7-13 points. Statistical analysis was conducted by SPSS 26.0. The hair cycle score was expressed as Mean±SD. Student’s t-test was used for comparison between groups at the same time point, and Welch-test was used for comparison of scores at different time points within the group. P<0.05 indicated a statistically significant difference. Results:On the 1st, 9th, and 19th day, the hair cycle scores of the control group were 1.00 ± 0.57, 5.04 ± 0.94, and 9.52 ± 0.87 points, while the hair cycle scores of the experimental group were 0.85 ± 0.62, 2.40 ± 0.50 and 6.08 ± 0.42 points. Inter group comparison showed that the hair cycle scores of the experimental group were lower than those of the control group at all three time points. There was no statistically significant difference on the 1st day ( t=1.03, P=0.307), while the differences were statistically significant on the 9th day ( t=13.38, P<0.001) and the 19th day ( t=16.41, P<0.001). Intragroup comparison showed that there was a statistically significant difference in hair cycle scores between the control group and the experimental group at different time points( P<0.01), and the scores increased over time. Conclusion:Sleep deprivation can cause a lag in the hair growth cycle of mice, but it does not cause a cessation of the hair growth cycle. The degree of lag gradually increases with the number of deprivation days.

Objective:To investigate the correlation between the neoadjuvant rectal (NAR) score and long-term survival in patients with locally advanced rectal cancer who have undergone neoadjuvant chemoradiotherapy.Methods:Clinical and pathological data of 487 patients diagnosed with rectal adenocarcinoma from October 2004 to April 2014 at Sun Yat-sen University Cancer Center who had received neoadjuvant chemoradiotherapy were retrospectively analyzed and the impact of NAR score on prognosis studied. Disease-free-survival (DFS) was calculated by the Kaplan-Meier method and survivals compared using the log-rank test. Cox models were used for univariate and multivariate analyses. Receiver operating characteristic curves were utilized to evaluate the predictive capability of NAR and tumor regression grade scores for the risk of 10-year postoperative recurrence and metastasis. The Delong test was employed to compare the diagnostic performance of the two scores.Results:Of the 487 patients included in the study, 166 were men (34.1%). The median age was 56 years (interquartile range [IQR]: 46–63). All patients completed adequate preoperative chemoradiotherapy and underwent R0 resection.The median interval between the end of chemoradiotherapy and surgery was 51 days (IQR: 44–58). Post-chemoradiotherapy downstaging occurred in 329 patients (67.6%). Tumor regression grades (TRGs) were 1–2 in 246 patients (50.5%) and 3–4 in 241 patients (49.5%). A total of 394 patients (80.9%) received postoperative chemotherapy. NAR scores were <8 in 182 patients (37.4%), 8–16 in 180 (37.0%), and >16 in 125 (25.6%). The median follow-up time was 111.5 months (IQR: 70.7–133.7 months). One hundred and thirteen patients died of rectal cancer, among whom 13 patients developed local recurrence, 88 patients developed distant metastasis, and 12 patients had unknown recurrence patterns. The 10-year DFS and overall survival rate of f the whole group were 68.9% and 71.5% respectively. The 10-year DFS rates for patients with NAR scores <8, 8–16, and >16 were 85.1%, 80.5%, and 66.4%, respectively ( P<0.001). Multivariate analyses revealed that the Dixon operation (HR=0.606, 95%CI: 0.408–0.902, P=0.014), and >16 (HR=2.569, 95%CI: 1.559–4.233, P<0.001) were independent predictors of the 10-year DFS of patients with locally advanced rectal cancer ( P<0.05 for all). In the entire patient cohort, the AUC of the receiver operating characteristic curve for NAR score predicting 10-year recurrence and metastasis was 0.67 (95%CI: 0.62–0.72), whereas the AUC for TRG score was 0.54 (95%CI: 0.49–0.60). The two scores differed significantly in accuracy ( Z=-4.06, P<0.001), the NAR score being a significantly better predictor of risk of 10-year recurrence and metastasis than the TRG score. Conclusion:The NAR score is a reliable predictor of 10-year DFS in patients with locally advanced rectal cancer who have undergone neoadjuvant chemoradiotherapy followed by curative surgery.