Prediction of Postoperative Length of Hospital Stay Based on Differences in Nursing Narratives in Elderly Patients with Epithelial Ovarian Cancer.

 The current study sought to evaluate whether nursing narratives can be used to predict postoperative length of hospital stay (LOS) following curative surgery for ovarian cancer.  A total of 33 patients, aged over 65 years, underwent curative surgery for newly diagnosed ovarian cancer between 2008 and 2012. Based on the median postoperative LOS, patients were divided into two groups: long-stay (>12 days;  The median postoperative LOS was 18 days (interquartile range [IQR]: 16-24 days) in the long-stay group and 9.5 days (IQR: 8-11.25 days) in the short-stay group. In the long-stay group, surgery duration was longer. Overall, patients in the long-stay group showed a higher volume of nursing narratives compared with patients in the short-stay group (SN: 68 vs. 46,  Statistical tests showed that nursing narratives that utilized the words "urination," "food supply," "bowel mobility," or "pain" were related to hospital stay in elderly females with ovarian cancer. Additionally, machine learning effectively predicted LOS.  The current study sought to determine whether elements of nursing narratives could be used to predict postoperative LOS among elderly ovarian cancer patients. Results indicated that nursing narratives that used the words "urination," "food supply," "bowel mobility," and "pain" significantly predicted postoperative LOS in the study population. Additionally, it was found that machine learning could effectively predict LOS based on quantitative characteristics of nursing narratives.

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Georg Thieme Verlag KG Stuttgart · New York.

Déclaration de conflit d'intérêts

None declared.