Dataset Information

Assessment of the Addition of Hypoalbuminemia to ACS-NSQIP Surgical Risk Calculator in Colorectal Cancer.

ABSTRACT: The aim of this study was to evaluate the benefit of adding hypoalbuminemia to the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) Surgical Risk Calculator when predicting postoperative outcomes in colorectal cancer patients.The ACS-NSQIP Surgical Risk Calculator offers qualified risk evaluation in surgical decision-making and informed patient consent. To date, malnutrition defined as hypoalbuminemia, an important independent surgical risk factor in colorectal cancer, is not included.This is a retrospective, multi-institutional study of ACS-NSQIP patients (n?=?18,532) who received colorectal surgery from 2009 to 2012. Models were constructed for predicting postoperative mortality and morbidity using the risk factors of the ACS-NSQIP Surgical Risk Calculator before and after adding hypoalbuminemia as a risk factor. The 2 models' performance was then compared using c-statistics and Brier scores. The ACS-NSQIP database in 2008 was used for validation of the created models.The prevalence of hypoalbuminemia (27.8%) is higher in colorectal cancer, when compared with other most common cancers. In univariate analyses, hypoalbuminemia was significantly associated with postoperative mortality and morbidity in colorectal cancer patients. In multivariate logistic regression analyses, 15 postoperative complications, including mortality and serious morbidities, were significantly predicted by hypoalbuminemia. Most of the models with hypoalbuminemia showed better performance and validation in predicting postoperative complications than those without hypoalbuminemia.In colorectal cancer, hypoalbuminemia, with levels below 3.5?g/dL, serves as an excellent assessment tool and preoperative predictor of postoperative outcomes. When combined with hypoalbuminemia as a risk factor, the ACS-NSQIP Surgical Risk Calculator offers more accurate information and estimation of surgical risks to patients and surgeons when choosing treatment options.

SUBMITTER: Hu WH

PROVIDER: S-EPMC4998893 | biostudies-other | 2016 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Assessment of the Addition of Hypoalbuminemia to ACS-NSQIP Surgical Risk Calculator in Colorectal Cancer.

Hu Wan-Hsiang WH Chen Hong-Hwa HH Lee Ko-Chao KC Liu Lin L Eisenstein Samuel S Parry Lisa L Cosman Bard B Ramamoorthy Sonia S

Medicine 20160301 10

The aim of this study was to evaluate the benefit of adding hypoalbuminemia to the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) Surgical Risk Calculator when predicting postoperative outcomes in colorectal cancer patients.The ACS-NSQIP Surgical Risk Calculator offers qualified risk evaluation in surgical decision-making and informed patient consent. To date, malnutrition defined as hypoalbuminemia, an important independent surgical risk factor in colorec ...[more]

PMID: 26962812

Similar Datasets

Project description:OBJECTIVE:The study objective was to validate the National Surgical Quality Improvement Program (NSQIP) Risk Calculator in stratifying risk estimates for patients who received surgery or stereotactic body radiation therapy for clinical stage I non-small cell lung cancer. METHODS:A retrospective analysis of patients with clinical stage I non-small cell lung cancer undergoing surgery (N = 279) or stereotactic body radiation therapy (N = 206) from 2009 to 2012 was performed. NSQIP complication risk estimates were calculated for both surgical and stereotactic body radiation therapy cases using the NSQIP Surgical Risk Calculator. NSQIP complication risk estimates were compared as continuous variables and by quartile ranges. RESULTS:Compared with patients undergoing video-assisted thoracoscopic surgery wedge resection, patients receiving stereotactic body radiation therapy were older, had larger tumors, had lower forced expiratory volume (FEV1) in 1 second and diffusing capacity of the lungs (DLCO) for carbon monoxide values, had higher American Society of Anesthesiologists scores, had higher rates of dyspnea, and had higher NSQIP serious complication risk estimates (all P < .05). Compared with patients undergoing video-assisted thoracoscopic surgery lobectomy, patients receiving stereotactic body radiation therapy had similar disparities, along with higher Adult Comorbidity Evaluation-27 (ACE) scores comorbidity scores, higher rates of cardiac comorbidities, and worse functional status (all P < .05). Variables associated with receiving stereotactic body radiation therapy treatment, rather than wedge resection, included increasing age, higher Adult Comorbidity Evaluation (ACE)-27 comorbidity score, dyspnea status, and decreasing FEV1 in 1 second and DLCO for carbon monoxide, but NSQIP serious complication risk score. In addition, surgical patients' actual serious complication rate (16.6% vs 8.8%) and pneumonia rate (6.0% vs 3.2%) were significantly higher than the NSQIP risk calculator predicted (all P < .05). CONCLUSIONS:The National Surgical Quality Improvement Program risk calculator does not effectively classify or stratify risk in patients with stage I non-small cell lung cancer. Continued efforts are needed to assess risk in this population and develop more tailored treatment decision aids.

Project description:Study designA retrospective study at a single academic institution.ObjectiveThe purpose of this study is to utilize machine learning to predict hospital length of stay (LOS) and discharge disposition following adult elective spine surgery, and to compare performance metrics of machine learning models to the American College of Surgeon's National Surgical Quality Improvement Program's (ACS NSQIP) prediction calculator.Summary of background dataA total of 3678 adult patients undergoing elective spine surgery between 2014 and 2019, acquired from the electronic health record.MethodsPatients were divided into three stratified cohorts: cervical degenerative, lumbar degenerative, and adult spinal deformity groups. Predictive variables included demographics, body mass index, surgical region, surgical invasiveness, surgical approach, and comorbidities. Regression, classification trees, and least absolute shrinkage and selection operator (LASSO) were used to build predictive models. Validation of the models was conducted on 16% of patients (N=587), using area under the receiver operator curve (AUROC), sensitivity, specificity, and correlation. Patient data were manually entered into the ACS NSQIP online risk calculator to compare performance. Outcome variables were discharge disposition (home vs. rehabilitation) and LOS (days).ResultsOf 3678 patients analyzed, 51.4% were male (n=1890) and 48.6% were female (n=1788). The average LOS was 3.66 days. In all, 78% were discharged home and 22% discharged to rehabilitation. Compared with NSQIP (Pearson R2 =0.16), the predictions of poisson regression ( R2 =0.29) and LASSO ( R2 =0.29) models were significantly more correlated with observed LOS ( P =0.025 and 0.004, respectively). Of the models generated to predict discharge location, logistic regression yielded an AUROC of 0.79, which was statistically equivalent to the AUROC of 0.75 for NSQIP ( P =0.135).ConclusionThe predictive models developed in this study can enable accurate preoperative estimation of LOS and risk of rehabilitation discharge for adult patients undergoing elective spine surgery. The demonstrated models exhibited better performance than NSQIP for prediction of LOS and equivalent performance to NSQIP for prediction of discharge location.

Dataset Information

Assessment of the Addition of Hypoalbuminemia to ACS-NSQIP Surgical Risk Calculator in Colorectal Cancer.

Publications

Assessment of the Addition of Hypoalbuminemia to ACS-NSQIP Surgical Risk Calculator in Colorectal Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets