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    A simple risk score to predict in-hospital mortality after pancreatic resection for cancer

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    Authors
    Hill, Joshua S.
    Zhou, Zheng
    Simons, Jessica P.
    Ng, Sing Chau
    McDade, Theodore P.
    Whalen, Giles F.
    Tseng, Jennifer F.
    UMass Chan Affiliations
    Department of Surgery
    Document Type
    Journal Article
    Publication Date
    2010-07-16
    Keywords
    Aged
    Aged, 80 and over
    Cohort Studies
    Comorbidity
    Female
    Hospital Mortality
    Humans
    Inpatients
    Male
    Middle Aged
    *Pancreatectomy
    Pancreatic Neoplasms
    Risk Assessment
    Risk Factors
    Survival Rate
    Treatment Outcome
    Surgery
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    Link to Full Text
    http://dx.doi.org/10.1245/s10434-010-0947-x
    Abstract
    BACKGROUND: Pancreatectomy for cancer continues to have substantial perioperative risk, and the factors affecting mortality are ill defined. An integer-based risk score based on national data might help clarify the risk of in-hospital mortality in patients undergoing pancreatic resection. METHODS: Records with the diagnosis of pancreatic cancer were queried from the Nationwide Inpatient Sample for 1998-2006. Procedures were categorized as proximal, distal, or nonspecified pancreatectomies on the basis of ICD-9 codes. Logistic regression and bootstrap methods were used to create an integer risk score for estimating the risk of in-hospital mortality using patient demographics, comorbidities (Charlson comorbidity score), procedure, and hospital type. A random sample of 80% of the cohort was used to create the risk score with a 20% internal validation set. RESULTS: A total of 5715 patient discharges were identified. Composite in-hospital mortality was 5.8%. Predictors used for the final model were age group, Charlson score, sex, type of pancreatectomy, and hospital volume status (low-, medium-, or high-volume center). Integer values were assigned to these characteristics and then used for calculating an additive score. Three clinically useful score groups were defined to stratify the risk of in-hospital mortality (mortality was 2.0, 6.2, and 13.9%, respectively; P < 0.0001), with a 6.95-fold difference between the low- and high-risk groups. There was sufficient discrimination of both the derivation set and the validation set, with c statistics of 0.71 and 0.72, respectively. CONCLUSIONS: An integer-based risk score can be used to accurately predict in-hospital mortality after pancreatectomy and may be useful for preoperative risk stratification and patient counseling.
    Source
    Ann Surg Oncol. 2010 Jul;17(7):1802-7. Epub 2010 Feb 13. Link to article on publisher's site
    DOI
    10.1245/s10434-010-0947-x
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/49794
    PubMed ID
    20155401
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1245/s10434-010-0947-x
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    UMass Chan Faculty and Researcher Publications

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