Mortality and cardiovascular events in adults with kidney failure after major non-cardiac surgery: a population-based cohort study

Differences in Postoperative Disposition by Kidney Disease Severity: A Population-Based Cohort Study

RATIONALE & OBJECTIVE

People with advanced kidney disease undergo more noncardiac operations compared with the general population, with a higher risk of perioperative cardiac events and death. However, little is known about the associations between severity of preoperative kidney dysfunction with postoperative length of hospitalization and discharge disposition; these were the focus of this study.

STUDY DESIGN

Population-based retrospective cohort.

SETTING & PARTICIPANTS

Adults from Alberta, Canada, undergoing inpatient major noncardiac surgery between April 2005 and February 2019.

EXPOSURE

Categorical preoperative outpatient estimated glomerular filtration rate (eGFR) or kidney failure status.

OUTCOME

Length of stay (LOS), days alive at home after surgery within 30 and 90 days, and discharge disposition location.

ANALYTICAL APPROACH

Associations were estimated with unadjusted and adjusted generalized estimating equation models.

RESULTS

We identified 927,560 inpatient surgeries in 666,770 people (55.9% female; median age, 57.4 years). People receiving dialysis had the longest LOS (11 days [95% CI, 6-29]), 2 times greater than that among people with normal kidney function (adjusted incidence rate ratio [IRR], 2.21 [95% CI, 2.10-2.32]). This group also had the fewest days alive at home within the first 30 days after surgery, with an IRR of 0.69 (95% CI, 0.67-0.70) compared with people with normal eGFR. The majority of people (82.8%) were discharged home without nursing support after surgery, though people receiving dialysis were discharged to a facility with 24-hour nursing care nearly 4 times more often. There were graded increases in risks of these outcomes with lower levels of kidney function.

LIMITATIONS

Many people did not have preoperative kidney function assessed, reflecting standard clinical practice in the general population.

CONCLUSIONS

After major surgery, people with kidney disease spend more time recovering in hospital and have less independence from postdischarge nursing supports than otherwise similar patients who have normal or near normal kidney function. These differences were more pronounced for those with the most severe stages of kidney disease.

PLAIN-LANGUAGE SUMMARY

People with kidney disease have surgery more frequently, with worse outcomes, compared with others in the general population. However, little is known about how long they spend in hospital afterward and whether they will be discharged home or to other facilities. To understand this more, we examined nearly 1 million surgeries performed in Alberta, Canada. Compared with people who have normal kidney function and are undergoing surgery, people with the most advanced kidney disease spent more than 2 times longer in hospital and were more likely to be discharged to long-term care facilities instead of being discharged to their homes. Future research is needed to understand the factors that predict who will experience prolonged hospitalization and to develop interventions to enable earlier discharge for people with kidney disease.

Preoperative estimated glomerular filtration rate to predict cardiac events in major noncardiac surgery: a secondary analysis of two large international studies

BACKGROUND

Optimised use of kidney function information might improve cardiac risk prediction in noncardiac surgery.

METHODS

In 35,815 patients from the VISION cohort study and 9219 patients from the POISE-2 trial who were ≥45 yr old and underwent nonurgent inpatient noncardiac surgery, we examined (by age and sex) the association between continuous nonlinear preoperative estimated glomerular filtration rate (eGFR) and the composite of myocardial injury after noncardiac surgery, nonfatal cardiac arrest, or death owing to a cardiac cause within 30 days after surgery. We estimated contributions of predictive information, C-statistic, and net benefit from eGFR and other common patient and surgical characteristics to large multivariable models.

RESULTS

The primary composite occurred in 4725 (13.2%) patients in VISION and 1903 (20.6%) in POISE-2; in both studies cardiac events had a strong, graded association with lower preoperative eGFR that was attenuated by older age (Pinteraction<0.001 for VISION; Pinteraction=0.008 for POISE-2). For eGFR of 30 compared with 90 ml min-1 1.73 m-2, relative risk was 1.49 (95% confidence interval 1.26-1.78) at age 80 yr but 4.50 (2.84-7.13) at age 50 yr in female patients in VISION. This differed modestly (but not meaningfully) in men in VISION (Pinteraction=0.02) but not in POISE-2 (Pinteraction=0.79). eGFR contributed the most predictive information and mean net benefit of all predictors in both studies, most C-statistic in VISION, and third most C-statistic in POISE-2.

CONCLUSIONS

Continuous preoperative eGFR is among the best cardiac risk predictors in noncardiac surgery of the large set examined. Along with its interaction with age, preoperative eGFR would improve risk calculators.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov NCT00512109 (VISION) and NCT01082874 (POISE-2).

Prediction of major postoperative events after non-cardiac surgery for people with kidney failure: derivation and internal validation of risk models

BACKGROUND

People with kidney failure often require surgery and experience worse postoperative outcomes compared to the general population, but existing risk prediction tools have excluded those with kidney failure during development or exhibit poor performance. Our objective was to derive, internally validate, and estimate the clinical utility of risk prediction models for people with kidney failure undergoing non-cardiac surgery.

DESIGN, SETTING, PARTICIPANTS, AND MEASURES

This study involved derivation and internal validation of prognostic risk prediction models using a retrospective, population-based cohort. We identified adults from Alberta, Canada with pre-existing kidney failure (estimated glomerular filtration rate [eGFR] < 15 mL/min/1.73m² or receipt of maintenance dialysis) undergoing non-cardiac surgery between 2005-2019. Three nested prognostic risk prediction models were assembled using clinical and logistical rationale. Model 1 included age, sex, dialysis modality, surgery type and setting. Model 2 added comorbidities, and Model 3 added preoperative hemoglobin and albumin. Death or major cardiac events (acute myocardial infarction or nonfatal ventricular arrhythmia) within 30 days after surgery were modelled using logistic regression models.

RESULTS

The development cohort included 38,541 surgeries, with 1,204 outcomes (after 3.1% of surgeries); 61% were performed in males, the median age was 64 years (interquartile range [IQR]: 53, 73), and 61% were receiving hemodialysis at the time of surgery. All three internally validated models performed well, with c-statistics ranging from 0.783 (95% Confidence Interval [CI]: 0.770, 0.797) for Model 1 to 0.818 (95%CI: 0.803, 0.826) for Model 3. Calibration slopes and intercepts were excellent for all models, though Models 2 and 3 demonstrated improvement in net reclassification. Decision curve analysis estimated that use of any model to guide perioperative interventions such as cardiac monitoring would result in potential net benefit over default strategies.

CONCLUSIONS

We developed and internally validated three novel models to predict major clinical events for people with kidney failure having surgery. Models including comorbidities and laboratory variables showed improved accuracy of risk stratification and provided the greatest potential net benefit for guiding perioperative decisions. Once externally validated, these models may inform perioperative shared decision making and risk-guided strategies for this population.

Using the Revised Cardiac Risk Index to Predict Major Postoperative Events for People With Kidney Failure: An External Validation and Update

Background

People with kidney failure have high risk of postoperative morbidity and mortality. Although the revised cardiac risk index (RCRI) is used to estimate the risk of major postoperative events, it has not been validated in this population. We aimed to externally validate the RCRI and determine whether updating the model improved predictions for people with kidney failure.

Methods

We derived a retrospective, population-based cohort of adults with kidney failure (maintenance dialysis or sustained estimated glomerular filtration rate < 15 mL/min per 1.73 m2) who had surgery in Alberta, Canada between 2005 and 2019. We categorized participants based on RCRI variables and assigned risk estimates of death or major cardiac events, and then estimated predictive performance. We re-estimated the coefficients for each RCRI variable and internally validated the updated model. Net benefit was estimated with decision curve analysis.

Results

After 38,541 surgeries, 1204 events (3.1%) occurred. The estimated C-statistic for the original RCRI was 0.64 (95% confidence interval: 0.62, 0.65). Examination of calibration revealed significant risk overestimation. In the re-estimated RCRI model, discrimination was marginally different (C-statistic 0.67 [95% confidence interval: 0.66, 0.69]), though calibration was improved. No net benefit was observed when the data were examined with decision curve analysis, whereas the original RCRI was associated with harm.

Conclusions

The RCRI performed poorly in a Canadian kidney failure cohort and significantly overestimated risk, suggesting that RCRI use in similar kidney failure populations should be limited. A re-estimated kidney failure-specific RCRI may be promising but needs external validation. Novel perioperative models for this population are urgently needed.