RESUMO
OBJECTIVE: Our aims were to assess North American trends in the management of patients undergoing pancreatoduodenectomy (PD) and distal pancreatectomy (DP), and to quantify the delivery of optimal pancreatic surgery. BACKGROUND: Morbidity after pancreatectomy remains unacceptably high. Recent literature suggests that composite measures may more accurately define surgical quality. METHODS: The 2013 to 2017 American College of Surgeons National Surgical Quality Improvement Program Participant Use Files were queried to identify patients undergoing PD (N = 16,222) and DP (N = 7946). Patient, process, procedure, and 30-day postoperative outcome variables were analyzed over time. Optimal pancreatic surgery was defined as the absence of postoperative mortality, serious morbidity, percutaneous drainage, and reoperation while achieving a length of stay equal to or less than the 75th percentile (12 days for PD and 7 days for DP) with no readmissions. Risk-adjusted time-trend analyses were performed using logistic regression, and the threshold for statistical significance was Pâ≤â0.05. RESULTS: The use of minimally invasive PD did not change over time, but robotic PD increased (2.5 to 4.2%; P < 0.001) and laparoscopic PD decreased (5.8% to 4.3%; P < 0.02). Operative times decreased (P < 0.05) and fewer transfusions were administered (P < 0.001). The percentage of patients with a drain fluid amylase checked on postoperative day 1 increased (P < 0.001), and a greater percentage of surgical drains were removed by postoperative day 3 (P < 0.001). Overall morbidity (P < 0.02), mortality (P < 0.05), and postoperative length of stay (P = 0.002) decreased. Finally, the rate of optimal pancreatic surgery increased for PD (53.7% to 56.9%; P < 0.01) and DP (53.3% to 58.5%; P < 0.001), and alspo for patients with pancreatic cancer (P < 0.01). CONCLUSIONS: From 2013 to 2017, pre, intra, and perioperative pancreatectomy processes have evolved, and multiple postoperative outcomes have improved. Thus, in 4 years, optimal pancreatic surgery in North America has increased by 3% to 5%.
Assuntos
Laparoscopia/efeitos adversos , Pancreatectomia/efeitos adversos , Neoplasias Pancreáticas/cirurgia , Pancreaticoduodenectomia/efeitos adversos , Complicações Pós-Operatórias/epidemiologia , Procedimentos Cirúrgicos Robóticos/efeitos adversos , Adulto , Idoso , Feminino , Hospitalização , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Duração da Cirurgia , Neoplasias Pancreáticas/mortalidade , Neoplasias Pancreáticas/patologia , Melhoria de Qualidade , Estudos Retrospectivos , Estados UnidosRESUMO
OBJECTIVE: The goal of this project was to first address barriers to implementation of the Risk Analysis Index (RAI) within a large, multi-hospital, integrated healthcare delivery system, and to subsequently demonstrate its utility for identifying at-risk surgical patients. BACKGROUND: Prior studies demonstrate the validity of the RAI for evaluating preoperative frailty, but they have not demonstrated the feasibility of its implementation within routine clinical practice. METHODS: Implementation of the RAI as a frailty screening instrument began as a quality improvement initiative at the University of Pittsburgh Medical Center in July 2016. RAI scores were collected within a REDCap survey instrument integrated into the outpatient electronic health record and then linked to information from additional clinical datasets. NSQIP-eligible procedures were queried within 90 days following the RAI, and the association between RAI and postoperative mortality was evaluated using logistic regression and Cox proportional hazards models. Secondary outcomes such as inpatient length of stay and readmissions were also assessed. RESULTS: RAI assessments were completed on 36,261 unique patients presenting to surgical clinics across five hospitals from July 1 to December 31, 2016, and 8,172 of these underwent NSQIP-eligible surgical procedures. The mean RAI score was 23.6 (SD 11.2), the overall 30-day and 180-day mortality after surgery was 0.7% and 2.6%, respectively, and the median time required to collect the RAI was 33 [IQR 23-53] seconds. Overall clinic compliance with the recommendation for RAI assessment increased from 58% in the first month of the study period to 84% in the sixth and final month. RAI score was significantly associated with risk of death (HR=1.099 [95% C.I.: 1.091 - 1.106], p < 0.001). At an RAI cutoff of ≥37, the positive predictive values for 30- and 90-day readmission were 14.8% and 26.2%, respectively, and negative predictive values were 91.6% and 86.4%, respectively. CONCLUSIONS: The RAI frailty screening tool can be efficiently implemented within multi-specialty, multi-hospital healthcare systems. In the context of our findings and given the value of the RAI in predicting adverse postoperative outcomes, health systems should consider implementing frailty screening within surgical clinics.
Assuntos
Fragilidade/classificação , Período Pré-Operatório , Medição de Risco/métodos , Idoso , Idoso de 80 Anos ou mais , Feminino , Hospitais , Humanos , Masculino , Programas de Rastreamento/métodos , Pessoa de Meia-Idade , Pennsylvania , Estudos Prospectivos , Melhoria de QualidadeRESUMO
OBJECTIVE: This study aimed to develop risk predictive models of 30-day mortality, morbidity, and major adverse limb events (MALE) after bypass surgery for aortoiliac occlusive disease (AIOD) and to compare their performances with a 5-Factor Frailty Index. METHODS: The American College of Surgeons National Surgical Quality Improvement Program 2012-2017 Procedure Targeted Aortoiliac (Open) Participant Use Data Files were queried to identify all patients who had elective bypass for AIOD: femorofemoral bypass, aortofemoral bypass, and axillofemoral bypass (AXB). Outcomes assessed included mortality, major morbidity, and MALE within 30 days postoperatively. Major morbidity was defined as pneumonia, unplanned intubation, ventilator support for >48 hours, progressive or acute renal failure, cerebrovascular accident, cardiac arrest, or myocardial infarction. Demographics, comorbidities, procedure type, and laboratory values were considered for inclusion in the risk predictive models. Logistic regression models for mortality, major morbidity and MALE were developed. The discriminative ability of these models (C-indices) were compared with that of the 5-Factor Modified Frailty Index (mFI-5): a general frailty tool determined from diabetes, functional status, history of chronic obstructive pulmonary disease, history of congestive heart failure, and hypertension. Calculators were derived using the most significant variables for each of the three risk predictive models. RESULTS: A total of 2612 cases (mean age 65.0, 60% male) were identified, of which 1149 (44.0%) were femorofemoral bypass, 1138 (43.6%) were aortofemoral bypass, and 325 (12.4%) were axillofemoral bypass. Overall, the rates of mortality, major morbidity, and MALE were 2.0%, 8.5%, and 4.9%, respectively. Twenty preoperative risk factors were considered for incorporation in the risk tools. Apart from procedure type, age was the most statistically significant predictor of both mortality and morbidity. Preoperative anemia and critical limb ischemia were the most significant predictors of MALE. All three constructed models demonstrated significantly better discriminative ability (P < .001) on the outcomes of interest as compared with the mFI-5. CONCLUSIONS: Our models outperformed the mFI-5 in predicting 30-day mortality, major morbidity, and adverse limb events in patients with AIOD undergoing elective bypass surgery. Calculators were created using the most statistically significant variables to help calculate individual patient's postoperative risks and allow for better informed consent and risk-adjusted comparison of provider outcomes.