Although deviations in intraoperative blood pressure are assumed to be associated with postoperative mortality, critical blood pressure thresholds remain undefined. Therefore, the authors estimated ...the intraoperative thresholds of systolic blood pressure (SBP), mean blood pressure (MAP), and diastolic blood pressure (DBP) associated with increased risk-adjusted 30-day mortality.
This retrospective cohort study combined intraoperative blood pressure data from six Veterans Affairs medical centers with 30-day outcomes to determine the risk-adjusted associations between intraoperative blood pressure and 30-day mortality. Deviations in blood pressure were assessed using three methods: (1) population thresholds (individual patient sum of area under threshold AUT or area over threshold 2 SDs from the mean of the population intraoperative blood pressure values), (2). absolute thresholds, and (3) percent change from baseline blood pressure.
Thirty-day mortality was associated with (1) population threshold: systolic AUT (odds ratio, 3.3; 95% CI, 2.2 to 4.8), mean AUT (2.8; 1.9 to 4.3), and diastolic AUT (2.4; 1.6 to 3.8). Approximate conversions of AUT into its separate components of pressure and time were SBP < 67 mmHg for more than 8.2 min, MAP < 49 mmHg for more than 3.9 min, DBP < 33 mmHg for more than 4.4 min. (2) Absolute threshold: SBP < 70 mmHg for more than or equal to 5 min (odds ratio, 2.9; 95% CI, 1.7 to 4.9), MAP < 49 mmHg for more than or equal to 5 min (2.4; 1.3 to 4.6), and DBP < 30 mmHg for more than or equal to 5 min (3.2; 1.8 to 5.5). (3) Percent change: MAP decreases to more than 50% from baseline for more than or equal to 5 min (2.7; 1.5 to 5.0). Intraoperative hypertension was not associated with 30-day mortality with any of these techniques.
Intraoperative hypotension, but not hypertension, is associated with increased 30-day operative mortality.
Purpose In early-stage non-small cell lung cancer (NSCLC), post-treatment mortality may influence the comparative effectiveness of surgery and stereotactic body radiotherapy (SBRT), with implications ...for shared decision making among high-risk surgical candidates. We analyzed early mortality after these interventions using the National Cancer Database. Patients and Methods We abstracted patients with cT1-T2a, N0, M0 NSCLC diagnosed between 2004 and 2013 undergoing either surgery or SBRT. Thirty-day and 90-day post-treatment mortality rates were calculated and compared using Cox regression and propensity score-matched analyses. Results We identified 76,623 patients who underwent surgery (78% lobectomy, 20% sublobar resection, 2% pneumonectomy) and 8,216 patients who received SBRT. In the unmatched cohort, mortality rates were moderately increased with surgery versus SBRT (30 days, 2.07% v 0.73% absolute difference (Δ), 1.34%; P < .001; 90 days, 3.59% v 2.93% Δ, 0.66%; P < .001). Among the 27,200 propensity score-matched patients, these differences increased (30 days, 2.41% v 0.79% Δ, 1.62%; P < .001; 90 days, 4.23% v 2.82% Δ, 1.41%; P < .001). Differences in mortality between surgery and SBRT increased with age, with interaction P < .001 at both 30 days and 90 days (71 to 75 years old: 30-day Δ, 1.87%; 90-day Δ, 2.02%; 76 to 80 years old: 30-day Δ, 2.80%; 90-day Δ, 2.59%; > 80 years old: 30-day Δ, 3.03%; 90-day Δ, 3.67%; all P ≤ .001). Compared with SBRT, surgical mortality rates were higher with increased extent of resection (30-day and 90-day multivariate hazard ratio for mortality: sublobar resection, 2.85 and 1.37; lobectomy, 3.65 and 1.60; pneumonectomy, 14.5 and 5.66; all P < 0.001). Conclusion Differences in 30- and 90-day post-treatment mortality between surgery and SBRT increased as a function of age, with the largest differences in favor of SBRT observed among patients older than 70 years. These representative mortality data may inform shared decision making among patients with early-stage NSCLC who are eligible for both interventions.
To use factor analysis to cluster the 18 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) perioperative complications into a reproducible, smaller number of ...clinically meaningful groups of postoperative complications, facilitating and streamlining future study and application in live clinical settings.
The ACS NSQIP collects and reports on eighteen 30-day postoperative complications (excluding mortality), which are variably grouped in published analyses using ACS NSQIP data. This hinders comparison between studies of this widely used quality improvement dataset.
Factor analysis was used to develop a series of complication clusters, which were then analyzed to identify a parsimonious, clinically meaningful grouping, using 2,275,240 surgical cases in the ACS NSQIP Participant Use File (PUF), 2005 to 2012. The main outcome measures are reproducible, data-driven, clinically meaningful clusters of complications derived from factor solutions.
Factor analysis solutions for 5 to 9 latent factors were examined for their percent of total variance, parsimony, and clinical interpretability. Applying the first 2 of these criteria, we identified the 7-factor solution, which included clusters of pulmonary, infectious, wound disruption, cardiac/transfusion, venous thromboembolic, renal, and neurological complications, as the best solution for parsimony and clinical meaningfulness. Applying the last (clinical interpretability), we combined the wound disruption with the infectious clusters resulting in 6 clusters for future clinical applications.
Factor analysis of ACS NSQIP postoperative complication data provides 6 clinically meaningful complication clusters in lieu of 18 postoperative morbidities, which will facilitate comparisons and clinical implementation of studies of postoperative morbidities.
To develop accurate preoperative risk prediction models for multiple adverse postoperative outcomes applicable to a broad surgical population using a parsimonious common set of risk variables and ...outcomes.
Currently, preoperative assessment of surgical risk is largely based on subjective clinician experience. We propose a paradigm shift from the current postoperative risk adjustment for cross-hospital comparison to patient-centered quantitative risk assessment during the preoperative evaluation.
We identify the most common and important predictor variables of postoperative mortality, overall morbidity, and 6 complication clusters from previously published prediction analyses that used forward selection stepwise logistic regression. We then refit the prediction models using only the 8 most common and important predictor variables, and compare the discrimination and calibration of these models to the original full-variable models using the c-index, Hosmer-Lemeshow analysis, and Brier scores.
Accurate risk models for 30-day outcomes of mortality, overall morbidity, and 6 clusters of complications were developed using a set of 8 preoperative risk variables. C-indexes of the 8 variable models are between 97.9% and 99.2% of those of the full models containing up to 28 variables, indicating excellent discrimination using fewer predictor variables. Hosmer-Lemeshow analyses showed observed to expected event rates to be nearly identical between parsimonious models and full models, both showing good calibration.
Accurate preoperative risk assessment of postoperative mortality, overall morbidity, and 6 complication clusters in a broad surgical population can be achieved with as few as 8 preoperative predictor variables, improving feasibility of routine preoperative risk assessment for surgical patients.
To develop parsimonious prediction models for postoperative mortality, overall morbidity, and 6 complication clusters applicable to a broad range of surgical operations in adult patients.
...Quantitative risk assessment tools are not routinely used for preoperative patient assessment, shared decision making, informed consent, and preoperative patient optimization, likely due in part to the burden of data collection and the complexity of incorporation into routine surgical practice.
Multivariable forward selection stepwise logistic regression analyses were used to develop predictive models for 30-day mortality, overall morbidity, and 6 postoperative complication clusters, using 40 preoperative variables from 2,275,240 surgical cases in the American College of Surgeons National Surgical Quality Improvement Program data set, 2005 to 2012. For the mortality and overall morbidity outcomes, prediction models were compared with and without preoperative laboratory variables, and generic models (based on all of the data from 9 surgical specialties) were compared with specialty-specific models. In each model, the cumulative c-index was used to examine the contribution of each added predictor variable. C-indexes, Hosmer-Lemeshow analyses, and Brier scores were used to compare discrimination and calibration between models.
For the mortality and overall morbidity outcomes, the prediction models without the preoperative laboratory variables performed as well as the models with the laboratory variables, and the generic models performed as well as the specialty-specific models. The c-indexes were 0.938 for mortality, 0.810 for overall morbidity, and for the 6 complication clusters ranged from 0.757 for infectious to 0.897 for pulmonary complications. Across the 8 prediction models, the first 7 to 11 variables entered accounted for at least 99% of the c-index of the full model (using up to 28 nonlaboratory predictor variables).
Our results suggest that it will be possible to develop parsimonious models to predict 8 important postoperative outcomes for a broad surgical population, without the need for surgeon specialty-specific models or inclusion of laboratory variables.
Although some studies have compared esophagectomy outcomes by technique or approach, there is opportunity to strengthen our knowledge surrounding these outcomes. We aimed to perform a comprehensive ...comparison of esophagectomy postoperative complications.
We retrospectively reviewed the American College of Surgeons National Surgical Quality Improvement Program database (2007-2018). Esophagectomies were identified using Current Procedural Terminology codes and grouped by operative technique (Ivor Lewis, transhiatal, McKeown) and surgical approach (minimally invasive vs open esophagectomy). Twelve postoperative complications were compared. Significant complications underwent risk adjustment using multivariate logistic regression.
Analysis was performed on 13,457 esophagectomies: 11,202 (83.2%) open and 2255 (16.8%) minimally invasive. There were 7611 (56.6%) Ivor Lewis, 3348 (24.9%) transhiatal, and 2498 (18.6%) McKeown procedures. There were significant differences among the surgical techniques in 6 of 12 risk-adjusted complications. When comparing the outcomes of minimally invasive techniques, there were only significant differences in 2 of 12 complications: overall morbidity (minimally invasive Ivor Lewis 30.5%, minimally invasive transhiatal 43.4%, minimally invasive McKeown 40.3%, P = .0009) and infections (minimally invasive Ivor Lewis 15.4%, minimally invasive transhiatal 26.0%, minimally invasive McKeown 25.3%, P = .0003). Patients who underwent minimally invasive surgery were less likely to have overall morbidity (odds ratio, 0.68; 95% confidence interval, 0.62-0.75), respiratory complications (odds ratio, 0.77; 95% confidence interval, 0.68-0.87), urinary tract infection (odds ratio, 0.61; 95% confidence interval, 0.43-0.88), renal complications (odds ratio, 0.52; 95% confidence interval, 0.34-0.81), bleeding complications (odds ratio, 0.36; 95% confidence interval, 0.30-0.43), and nonhome discharge (odds ratio, 0.54; 95% confidence interval, 0.45-0.64), and had shorter length of stay (9.7 vs 13.2 days, P < .0001).
Patients undergoing minimally invasive esophagectomy have lower rates of postoperative complications regardless of esophagectomy techniques. The minimally invasive approach was associated with reduced complication variance among 3 common esophagectomy techniques.
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Stroke remains a potentially devastating complication of aortic arch intervention. The value of neurophysiologic intraoperative monitoring (NIOM) in the early identification of stroke is unclear. We ...evaluated the utility of NIOM for early stroke detection in aortic arch surgery.
Across 8 years at our institution, 365 patients underwent aortic arch surgery with hypothermic circulatory arrest, and 224 cases utilized NIOM. One patient was excluded for intraoperative death. In the remaining cohort, we reviewed the incidence, timing, and location of strokes, and the incidence and nature of NIOM alerts.
Hemiarch was performed in 154 patients and total arch replacement in 69 patients. Stroke occurred in 6.3% of all cases (14 out of 223), 15.9% of total arches (11 out of 69), and 2.0% of hemiarches (3 out of 154). There were 33 NIOM alerts (14.8%), and 9 patients had both alerts and stroke. Of these, NIOM deficits plausibly correlated with imaging findings in 7 cases (78%). Of the 5 stroke patients without NIOM alerts, 2 developed neurologic symptoms 3 days or more postoperatively, and infarcts in 3 patients did not result in sensory or motor deficits. Excluding 2 patients with late stroke, the sensitivity of NIOM for stroke detection was 75%, specificity was 88.5%, positive predictive value was 27.3%, and negative predictive value was 97.4%.
Despite a low positive predictive value requiring a high level of discrimination when interpreting abnormal findings, NIOM has high sensitivity and specificity for the early stroke detection. Furthermore, its high negative predictive valve is reassuring for low risk of stroke in the absence of alerts.
Neuromonitoring during aortic arch surgery has high sensitivity and specificity for early detection of stroke, despite a low positive predictive value for permanent neurologic deficits, alerts can correspond to correctable intraoperative abnormalities as well as stroke. Intraoperative identification of neurologic deficits can lead to intraoperative interventions to reverse deficits, and earlier postprocedural neurologic imaging and catheter-based interventions if indicated. Furthermore, the high negative predictive value of neuromonitoring means that patients without neuromonitoring alerts are very unlikely to have a postoperative stroke. Display omitted
Neighborhood measures of social vulnerability encompassing multiple sociodemographic factors can be used to quantify disparities in outcomes. We hypothesize patients with high Social Vulnerability ...Index (SVI) are at increased risk of morbidity following colectomy.
We used local 2012–2017 National Surgical Quality Improvement Program (NSQIP) data to study colectomy patients, examining associations between SVI and postoperative outcomes.
We included 976 patients from five hospitals. High SVI (>75th percentile) was associated with increased postoperative morbidity on unadjusted analysis (OR 1.84, 95% CI 1.35–2.52, p < 0.001); this association persisted after adjusting for demographics and comorbidities (OR 1.63, 95% CI 1.15–2.31, p = 0.005). The association with SVI was not significant after adjusting for perioperative risk modifiers such as emergent presentation (OR 1.37, 95% CI 0.95–1.98, p = 0.10).
High social vulnerability is associated with increased postoperative complications. This effect appears mediated by perioperative risk factors, suggesting potential to improve outcomes by facilitating timely surgical intervention.
•The Social Vulnerability Index (SVI) is associated with surgical outcomes.•Patients undergoing colectomy at five hospitals were examined.•Postoperative morbidity was higher for patients with high SVI.•This effect appears to be mediated by perioperative/intraoperative risk factors.•This suggests potential to improve outcomes by facilitating timely surgical intervention.
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.
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 χ
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.
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.
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.
Prior publications about the association between participation in the American College of Surgeons National Surgical Quality Improvement Program and improved postoperative outcomes have reported ...mixed results. We aimed to perform a comprehensive analysis of preoperative characteristics and unadjusted and risk-adjusted postoperative complication rates over time in the American College of Surgeons National Surgical Quality Improvement Program dataset.
We used the American College of Surgeons National Surgical Quality Improvement Program database, 2005 to 2018, to analyze preoperative patient characteristics and unadjusted and risk-adjusted rates of adverse postoperative outcomes by year. Expected events were calculated using multiple logistic regression, with each complication as the dependent variable and the 28 non-laboratory preoperative American College of Surgeons National Surgical Quality Improvement Program variables as the independent variables. Annual observed-to-expected ratios for each outcome were used to risk-adjust outcomes over time.
The analytic cohort included 7,474,298 operations across 9 surgical specialties. Both the preoperative patient risk and the unadjusted rate of postoperative complications decreased over time. While the observed-to-expected ratio for mortality remained around 1, the observed-to-expected ratios for the other outcomes decreased over time from 2005 to 2018, except for the following cardiac complications: overall morbidity 1.11 (95% confidence interval: 1.10–1.13) to 0.97 (0.96–0.98); pulmonary 1.18 (1.15–1.21) to 0.91 (0.89–0.92); infection 1.19 (1.16–1.21) to 1.01 (1.00–1.01); urinary tract infection 1.29 (1.23–1.34) to 0.87 (0.86–0.89); venous thromboembolism 1.10 (1.03–1.16) to 0.92 (0.90–0.94) ; cardiac 0.76 (0.70–0.81) to 1.04 (1.01–1.07); renal 1.14 (1.08–1.21) to 0.96 (0.93–0.99); stroke 1.12 (1.00–1.25) to 0.98 (0.94–1.03); and bleeding 1.35 (1.33–1.36) to 0.80 (0.79–0.81).
Hospitals participating in the American College of Surgeons National Surgical Quality Improvement Program have experienced a decrease in risk-adjusted postoperative surgical complications over time in all areas except for mortality and cardiac complications.
