Cancers · 2026
The Prediction of Extended Hospital Length of Stay in Patients After Endoscopic Endonasal Transsphenoidal Surgery for the Resection of Non-Functioning Pituitary Adenomas: A Dual-Center Retrospective Analysis.
СтатьяНазвание и аннотация: Перевод в очереди
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Gao Bibo, Dai Junjian, Yu Xiao, Cao Shilong, Wu Congcong, Zhu Changsen, Li Bingchan, Shang Anquan, Wang Ning, Meng Jianguo
Аннотация
BACKGROUND: Prolonged hospitalization after endoscopic endonasal transsphenoidal surgery for non-functioning pituitary adenomas increases costs and complications. Early identification of high-risk patients is crucial for optimizing perioperative management.
METHODS: In this dual-center retrospective study of 368 patients, a predictive model was developed using a training cohort (n = 268). Prolonged length of stay was defined as ≥75th percentile (≥16 days). LASSO regression selected features from clinical, radiological, and perioperative variables. Independent predictors from multivariable logistic regression were dichotomized via ROC analysis and integrated into a nomogram. Model performance was assessed internally and validated externally (n = 100).
RESULTS: Six independent predictors were identified: age > 50 years, vertical tumor diameter > 17.8 mm, anteroposterior diameter > 20.5 mm, transverse diameter > 17.8 mm, anesthesia duration > 194 min, and systolic blood pressure > 119 mmHg. The nomogram showed moderate but reproducible discrimination (AUC = 0.762 in training; 0.750 in validation). Calibration and decision curve analysis confirmed good fit and clinical utility.
CONCLUSION: We developed and validated a practical nomogram predicting prolonged hospitalization risk using readily available perioperative variables. This tool may assist individualized risk stratification and perioperative planning in comparable clinical settings, with potential implications for patient flow and resource utilization.
METHODS: In this dual-center retrospective study of 368 patients, a predictive model was developed using a training cohort (n = 268). Prolonged length of stay was defined as ≥75th percentile (≥16 days). LASSO regression selected features from clinical, radiological, and perioperative variables. Independent predictors from multivariable logistic regression were dichotomized via ROC analysis and integrated into a nomogram. Model performance was assessed internally and validated externally (n = 100).
RESULTS: Six independent predictors were identified: age > 50 years, vertical tumor diameter > 17.8 mm, anteroposterior diameter > 20.5 mm, transverse diameter > 17.8 mm, anesthesia duration > 194 min, and systolic blood pressure > 119 mmHg. The nomogram showed moderate but reproducible discrimination (AUC = 0.762 in training; 0.750 in validation). Calibration and decision curve analysis confirmed good fit and clinical utility.
CONCLUSION: We developed and validated a practical nomogram predicting prolonged hospitalization risk using readily available perioperative variables. This tool may assist individualized risk stratification and perioperative planning in comparable clinical settings, with potential implications for patient flow and resource utilization.