Front. Surg.

Sec. Orthopedic Surgery

Volume 11 - 2024 | doi: 10.3389/fsurg.2024.1476173

Provisionally accepted

The final, formatted version of the article will be published soon.

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Objective: This retrospective study aimed to explore the relationship between intraoperative glucose (IG) and the length of hospital stay (LOS) in patients with femoral neck fractures via the Medical Information Mart for Intensive Care-IV(MIMIC-IV) database. Methods: A generalized additive model (GAM) was performed to explore the relationship between IG levels and LOS. Restricted cubic spline (RCS) curves were used to analyze the dose-response relationship between IG levels and prolonged LOS (or 7-day LOS). Threshold effect analysis was conducted to assess the key points influencing their association. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were performed to evaluate the predictive performance of IG levels for LOS. Results: A total of 743 patients with femoral neck fractures were collected from the MIMIC-IV database. We found that there was a nonlinear relationship between IG and the LOS (or prolonged LOS/ >7 days LOS). Moreover, their relationship was still significant even after adjusting for potential confounders. The threshold effect showed that IG was significantly related to the prolonged LOS when it > 137 mg/dL, and IG was significantly related to 7-days LOS when it>163 mg/dL. ROC showed that IG had a better function in predicting 7-day LOS in participants with IG >163 mg/dL than predicting the prolonged LOS among participants with IG > 137 mg/dL. Moreover, the DCA results showed that IG can obtain favorable net benefit in clinical in predicting 7-days LOS among participants with IG > 163 mg/dL. Conclusions: In summary, there was a nonlinear relationship between IG levels and LOS. In patients with IG levels >163 mg/dL, using IG content to predict > 7 days LOS had a good function.

Keywords: Femoral neck fracture, Length of hospital stay, Interoperative glucose, Influencing factors, Medical Information Mart for Intensive Care database

Received: 05 Aug 2024; Accepted: 29 Oct 2024.

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