Dataset Information

A validated risk model to predict 90-day VTE events in postsurgical patients.

ABSTRACT: Background: VTE is the proximate cause of 100,000 deaths in the United States each year. Perioperative VTE risk among surgical patients varies by 20-fold, which highlights the importance of risk stratification to identify high-risk patients, in whom chemoprophylaxis can decrease VTE risk, and low-risk patients, for whom the risk-benefit relationship of prophylaxis may be unfavorable.

Methods: We used data from a statewide surgical quality collaborative for surgical procedures performed between 2010 and 2012. Regression-based techniques identified predictors of 90-day VTE while adjusting for procedural complexity and comorbid conditions. A weighted risk index was created and was validated subsequently in a separate, independent dataset.

Results: Data were available for 10,344 patients, who were allocated randomly to a derivation or validation cohort. The 90-day VTE rate was 1.4%; 66.2% of the derivation cohort and 65.5% of the validation cohort received chemoprophylaxis. Seven risk factors were incorporated into a weighted risk index: personal history of VTE, current cancer, sepsis/septic shock/systemic inflammatory response syndrome, age?60 years, BMI?40 kg/m2, male sex, and family history of VTE. Prediction for 90-day VTE was similar in the derivation and validation cohorts (areas under the receiver operator curve, 0.72 and 0.70, respectively). An 18-fold variation in 90-day VTE rate was identified.

Conclusions: A weighted risk index quantifies 90-day VTE risk among surgical patients and identifies an 18-fold variation in VTE risk among the overall surgical population.

SUBMITTER: Pannucci CJ

PROVIDER: S-EPMC4502716 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A validated risk model to predict 90-day VTE events in postsurgical patients.

Pannucci Christopher J CJ Laird Sandra S Dimick Justin B JB Campbell Darrell A DA Henke Peter K PK

Chest 20140301 3

<h4>Background</h4>VTE is the proximate cause of 100,000 deaths in the United States each year. Perioperative VTE risk among surgical patients varies by 20-fold, which highlights the importance of risk stratification to identify high-risk patients, in whom chemoprophylaxis can decrease VTE risk, and low-risk patients, for whom the risk-benefit relationship of prophylaxis may be unfavorable.<h4>Methods</h4>We used data from a statewide surgical quality collaborative for surgical procedures perfor ...[more]

PMID: 24091567

Similar Datasets

Project description:ObjectivesTo test new cardiovascular (CV) risk models in very old adults with and without a history of CV disease (CVD), based on traditional risk factors and biomarkers.DesignCross-validated prospective cohort study. The models were tested in the BELFRAIL Study and externally validated in the Leiden 85-plus Study.SettingGeneral practice, Belgium and The Netherlands.ParticipantsThe BELFRAIL cohort consisted of 266 patients aged 80 years or older without a history of CVD and 260 with a history of CVD. The Leiden 85-plus Study consisted of 264 patients aged 85 years without a history of CVD and 282 with a history of CVD.Outcome measuresThe model with traditional risk factors and biomarkers, as well as the model using only biomarkers, was compared with the model with only traditional risk factors to predict 3-year CV morbidity and mortality. A competing-risk analysis was performed, and the continuous net reclassification improvement (NRI), integrated discrimination improvement (IDI) and net benefit were used to compare the predictive value of the different models.ResultsTraditional risk factors poorly predicted CV mortality and morbidity. In participants without a history of CVD, adding N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) improved the prediction (NRI 0.56 (95% CI 0.16 to 0.99) and relative IDI 4.01 (95% CI 2.19 to 6.28)). In participants with a history of CVD, the NRI with the addition of NT-pro-BNP and high-sensitivity C reactive protein was 0.38 (95% CI 0.09 to 0.70), and the relative IDI was 0.53 (95% CI 0.23 to 0.90). Moreover, in participants without a history of CVD, NT-pro-BNP performed well as a stand-alone predictor (NRI 0.32 (95% CI -0.12 to 0.74) and relative IDI 3.44 (95% CI 1.56 to 6.09)).ConclusionsThis study tested new risk models to predict CV morbidity and mortality in very old adults. Especially, NT-pro-BNP showed a strong added predictive value. This opens perspectives for clinicians who are in need of an easily applicable strategy for CV risk prediction in very old adults.

Dataset Information

A validated risk model to predict 90-day VTE events in postsurgical patients.

Publications

A validated risk model to predict 90-day VTE events in postsurgical patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets