4.5 Article

Predictors for Perioperative Outcomes following Total Laryngectomy: A University HealthSystem Consortium Discharge Database Study

期刊

OTOLARYNGOLOGY-HEAD AND NECK SURGERY
卷 151, 期 1, 页码 81-86

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/0194599814528451

关键词

UHC; total laryngectomy; outcomes; academic; mortality; complications

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ObjectiveThe University HealthSystem Consortium (UHC) database collects discharge information on patients treated at academic health centers throughout the United States. We sought to use this database to identify outcome predictors for patients undergoing total laryngectomy. A secondary end point was to assess the validity of the UHC's predictive risk mortality model in this cohort of patients. Study DesignRetrospective review. SettingAcademic medical centers (tertiary referral centers) and their affiliate hospitals in the United States. Subjects and MethodsUsing the UHC discharge database, we retrieved and analyzed data for 4648 patients undergoing total laryngectomy who were discharged between October 2007 and January 2011 from all of the member institutions. Demographics, comorbidities, institutional data, and outcomes were retrieved. ResultsThe length of stay and overall costs were significantly higher among female patients (P <. 0001), while age was a predictor of intensive care unit stay (P =. 014). The overall complication rate was higher among Asians (P =. 019) and in patients with anemia and diabetes compared with other comorbidities. The average institutional case load was 1.92 cases/mo; we found an inverse correlation (R = -0.47) between the institutional case load and length of stay (P <. 0001). The UHC admit mortality risk estimator was found to be an accurate predictor not only of mortality (P <. 0002) but also of intensive care unit admission and complication rate (P <. 0001). ConclusionThis study provides an overview of laryngectomy outcomes in a contemporary cohort of patients treated at academic health centers. UHC admit mortality risk is an excellent outcome predictor and a valuable tool for risk stratification in these patients.

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