Mediation of smoking-associated postoperative mortality by perioperative complications in veterans undergoing elective surgery: data from Veterans Affairs Surgical Quality Improvement Program (VASQIP)--a cohort study

OBJECTIVE: To assess the mediation of smoking-associated postoperative mortality by postoperative complications. DESIGN: Observational cohort study. SETTING: Using data from the Veterans Affairs (VA) Surgical Quality Improvement Programme, a quality assurance programme for major surgical procedures in the VA healthcare system, we assessed the association of current smoking at the time of the surgery with 6-month and 1-year mortality. PRIMARY AND SECONDARY OUTCOME MEASURES: Using mediation analyses, we calculated the relative contribution of each smoking-associated complication to smoking-associated postoperative mortality, both unadjusted and adjusted for age, race/ethnicity, work relative value unit of the operation, surgeon specialty, American Society of Anesthesiologists class and year of surgery. Smoking-associated complications included surgical site infection (SSI), cardiovascular complications (myocardial infarction, cardiac arrest and/or stroke) and pulmonary complications (pneumonia, failure to wean and/or reintubation). RESULTS: There were 186 632 never smokers and 135 741 current smokers. The association of smoking and mortality was mediated by smoking-related complications with varying effects. In unadjusted analyses, the proportions of mediation of smoking to 6-month mortality explained by the complications were as follows: SSIs 22%, cardiovascular complications 12% and pulmonary complications 89%. In adjusted analyses, the per cents mediated by each complication were as follows: SSIs 2%, cardiovascular complications 4% and pulmonary complications 22%. In adjusted analyses for 1-year mortality, respective per cents mediated were 2%, 3% and 16%. CONCLUSIONS: Pulmonary complications, followed by cardiovascular complications and SSIs were mediators of smoking-associated 6-month and 1-year mortality. Interventions targeting smoking cessation and prevention and early treatment of pulmonary complications has the likelihood of reducing postoperative mortality after elective surgery

Alabama Veterans Rural Health Initiative: A Preliminary Evaluation of Unmet Health Care Needs

The Alabama Veterans Rural Health Initiative aims to better understand the health care needs, health status, and barriers to care for rural veterans. Following extensive community outreach, Veteran Community Outreach Health Workers assessed 203 veterans residing in rural counties of Alabama who either: 1) had never enrolled in VA health services, or 2) had not used those services in at least two years. While 71.4 percent of participants reported having utilized non-VHA primary care within the past year, 33.5 percent reported an inability or delay in obtaining needed health care for one or more services: primary care, specialty care, mental health care, addictions treatment, dental care, or prescription medication. The most commonly cited barrier was cost. Among all participants, 56 percent screened positive for at least one Axis I mental disorder. Rurally residing, non-VHA utilizing veterans appear to have fairly good access to primary care, but need dental care, prescription medication, and mental health care

Development and validation of a predictive model for American Society of Anesthesiologists Physical Status

Abstract Background The American Society of Anesthesiologists Physical Status (ASA-PS) classification system was developed to categorize the fitness of patients before surgery. Increasingly, the ASA-PS has been applied to other uses including justification of inpatient admission. Our objectives were to develop and cross-validate a statistical model for predicting ASA-PS; and 2) assess the concurrent and predictive validity of the model by assessing associations between model-derived ASA-PS, observed ASA-PS, and a diverse set of 30-day outcomes. Methods Using the 2014 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Participant Use Data File, we developed and internally cross-validated multinomial regression models to predict ASA-PS using preoperative NSQIP data. Accuracy was assessed with C-Statistics and calibration plots. We assessed both concurrent and predictive validity of model-derived ASA-PS relative to observed ASA-PS and 30-day outcomes. To aid further research and use of the ASA-PS model, we implemented it into an online calculator. Results Of the 566,797 elective procedures in the final analytic dataset, 8.9% were ASA-PS 1, 48.9% were ASA-PS 2, 39.1% were ASA-PS 3, and 3.2% were ASA-PS 4. The accuracy of the 21-variable model to predict ASA-PS was C = 0.77 +/− 0.0025. The model-derived ASA-PS had stronger association with key indicators of preoperative status including comorbidities and higher BMI (concurrent validity) compared to observed ASA-PS, but less strong associations with postoperative complications (predictive validity). The online ASA-PS calculator may be accessed at https://s-spire-clintools.shinyapps.io/ASA_PS_Estimator/ Conclusions Model-derived ASA-PS better tracked key indicators of preoperative status compared to observed ASA-PS. The ability to have an electronically derived measure of ASA-PS can potentially be useful in research, quality measurement, and clinical applications.https://deepblue.lib.umich.edu/bitstream/2027.42/152155/1/12913_2019_Article_4640.pd

4th Annual Lady Grace Revere Osler Lecture: Evaluation of the Surgical Care Improvement Project: Lessons Learned and Future Directions

Presentation: 54 minute