RESUMO
OBJECTIVE: We sought to evaluate how implementing a thoracic enhanced recovery after surgery (ERAS) protocol impacted surgical outcomes after elective anatomic lung resection. BACKGROUND: The effect of implementing the ERAS Society/European Society of Thoracic Surgery thoracic ERAS protocol on postoperative outcomes throughout an entire health care system has not yet been reported. METHODS: This was a prospective cohort study within one health care system (January 2019-March, 2023). A thoracic ERAS protocol was implemented on May 1, 2021 for elective anatomic lung resections, and postoperative outcomes were tracked using the electronic health record and Vizient data. The primary outcome was overall morbidity; secondary outcomes included individual complications, length of stay, opioid use, chest tube duration, and total cost. Patients were grouped into pre-ERAS and post-ERAS cohorts. Bivariable comparisons were performed using independent t -test, χ 2 , or Fisher exact tests, and multivariable logistic regression was performed to control for confounders. RESULTS: There were 1007 patients in the cohort; 450 (44.7%) were in the post-ERAS group. Mean age was 66.2 years; most patients were female (65.1%), white (83.8%), had a body mass index between 18.5 and 29.9 (69.7%), and were ASA class 3 (80.6%). Patients in the postimplementation group had lower risk-adjusted rates of any morbidity, respiratory complication, pneumonia, surgical site infection, arrhythmias, infections, opioid usage, ICU use, and shorter postoperative length of stay (all P <0.05). CONCLUSIONS: Postoperative outcomes were improved after the implementation of an evidence-based thoracic ERAS protocol throughout the health care system. This study validates the ERAS Society/European Society of Thoracic Surgery guidelines and demonstrates that simultaneous multihospital implementation can be feasible and effective.
Assuntos
Recuperação Pós-Cirúrgica Melhorada , Pneumonectomia , Complicações Pós-Operatórias , Humanos , Feminino , Masculino , Idoso , Estudos Prospectivos , Pneumonectomia/métodos , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/prevenção & controle , Pessoa de Meia-Idade , Protocolos Clínicos , Tempo de Internação/estatística & dados numéricosRESUMO
BACKGROUND: Thirty-day mortality after outpatient surgery is unexpected and undesired. We investigated preoperative risk factors, operative variables, and postoperative complications associated with 30-day death after outpatient surgery. METHODS: Using the 2005 to 2018 American College of Surgeons National Surgical Quality Improvement Program database, we evaluated 30-day mortality rate trends over time after outpatient operations. We analyzed associations between 37 preoperative variables, operation time, hospital length of stay, and 9 postoperative complications with mortality rate using χ2 analyses for categorical data and tests for continuous data. We used forward selection logistic regression models to determine the best predictors of mortality preoperatively and postoperatively. We also separately analyzed mortality by age group. RESULTS: A total of 2,822,789 patients were included. The 30-day mortality rate did not change significantly over time (P = .34, Cochran-Armitage trend test), remaining steady at around 0.06%. The most significant preoperative predictors of mortality included the patient having disseminated cancer, decreased functional health status, increased American Society of Anesthesiology Physical Status classification, increased age, and ascites, accounting for 95.8% (0.837/0.874) of the full model c-index. The most significant postoperative complications associated with increased risk of mortality included having cardiac (26.95% yes vs 0.04% no), pulmonary (10.25% vs 0.04%), stroke (9.22% vs 0.06%), and renal (9.33% vs 0.06%) complications. Postoperative complications conferred a greater risk for mortality than preoperative variables. Mortality risk increased incrementally with age, particularly past age 80. CONCLUSION: The operative mortality rate after outpatient surgery has not changed over time. Patients over 80 years with disseminated cancer, decreased functional health status, or increased ASA class should generally be considered for inpatient surgery. However, there might be some circumstances where outpatient surgery could be considered.
Assuntos
Procedimentos Cirúrgicos Ambulatórios , Pacientes Internados , Humanos , Estados Unidos/epidemiologia , Idoso de 80 Anos ou mais , Procedimentos Cirúrgicos Ambulatórios/efeitos adversos , Fatores de Risco , Modelos Logísticos , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/etiologia , Melhoria de Qualidade , Estudos RetrospectivosRESUMO
BACKGROUND: Present at the time of surgery (PATOS) is an important measure to collect in postoperative complication surveillance systems because it may affect a patient's risk of a subsequent complication and the estimation of postoperative complication rates attributed to the healthcare system. The American College of Surgeons (ACS) NSQIP started collecting PATOS data for 8 postoperative complications in 2011, but no one has used these data to quantify how this may affect unadjusted and risk-adjusted postoperative complication rates. STUDY DESIGN: This study was a retrospective observational study of the ACS NSQIP database from 2012 to 2018. PATOS data were analyzed for the 8 postoperative complications of superficial, deep, and organ space surgical site infection; pneumonia; urinary tract infection; ventilator dependence; sepsis; and septic shock. Unadjusted postoperative complication rates were compared ignoring PATOS vs taking PATOS into account. Observed to expected ratios over time were also compared by calculating expected values using multiple logistic regression analyses with complication as the dependent variable and the 28 nonlaboratory preoperative variables in the ACS NSQIP database as the independent variables. RESULTS: In 5,777,108 patients, observed event rates for each outcome were reduced by between 6.1% (superficial surgical site infection) and 52.5% (sepsis) when PATOS was taken into account. The observed to expected ratios were similar each year for all outcomes, except for sepsis and septic shock in the early years. CONCLUSIONS: Taking PATOS into account is important for reporting unadjusted event rates. The effect varied by type of complication-lowest for superficial surgical site infection and highest for sepsis and septic shock. Taking PATOS into account was less important for risk-adjusted outcomes (observed to expected ratios), except for sepsis and septic shock.
Assuntos
Sepse , Choque Séptico , Humanos , Infecção da Ferida Cirúrgica/epidemiologia , Infecção da Ferida Cirúrgica/etiologia , Choque Séptico/epidemiologia , Choque Séptico/complicações , Estudos Retrospectivos , Bases de Dados Factuais , Sepse/epidemiologia , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/etiologia , Fatores de RiscoRESUMO
BACKGROUND: Emerging literature suggests that measures of social vulnerability should be incorporated into surgical risk calculators. The Social Vulnerability Index (SVI) is a measure designed by the CDC that encompasses 15 socioeconomic and demographic variables at the census tract level. We examined whether adding the SVI into a parsimonious surgical risk calculator would improve model performance. STUDY DESIGN: The eight-variable Surgical Risk Preoperative Assessment System (SURPAS), developed using the entire American College of Surgeons (ACS) NSQIP database, was applied to local ACS-NSQIP data from 2012 to 2018 to predict 12 postoperative outcomes. Patient addresses were geocoded and used to estimate the SVI, which was then added to the model as a ninth predictor variable. Brier scores and c-indices were compared for the models with and without the SVI. RESULTS: The analysis included 31,222 patients from five hospitals. Brier scores were identical for eight outcomes and improved by only one to two points in the fourth decimal place for four outcomes with addition of the SVI. Similarly, c-indices were not significantly different (p values ranged from 0.15 to 0.96). Of note, the SVI was associated with most of the eight SURPAS predictor variables, suggesting that SURPAS may already indirectly capture this important risk factor. CONCLUSION: The eight-variable SURPAS prediction model was not significantly improved by adding the SVI, showing that this parsimonious tool functions well without including a measure of social vulnerability.