Association of an Acute Kidney Injury Follow-up Clinic With Patient Outcomes and Care Processes: A Cohort Study

RATIONALE & OBJECTIVE

To determine whether attendance at an acute kidney injury (AKI) follow-up clinic is associated with reduced major adverse kidney events.

STUDY DESIGN

Propensity-matched cohort study.

SETTING & PARTICIPANTS

Patients hospitalized with AKI in Ontario, Canada, from February 1, 2013, through September 30, 2017, at a single clinical center, who were not receiving dialysis when discharged.

EXPOSURE

Standardized assessment by a nephrologist.

OUTCOMES

Time to a major adverse kidney event, defined as death, initiation of maintenance dialysis, or incident/progressive chronic kidney disease.

ANALYTICAL APPROACH

Propensity scores were used to match each patient who attended an AKI follow-up clinic to 4 patients who received standard care. Cox proportional hazards models were fit to assess the association between the care within an AKI follow-up clinic and outcomes. To avoid immortal time bias, we randomly assigned index dates to the comparator group.

RESULTS

We matched 164 patients from the AKI follow-up clinic to 656 patients who received standard care. During a mean follow-up of 2.2±1.3 (SD) years, care in the AKI follow-up clinic was not associated with a reduction in major adverse kidney events relative to standard care (22.1 vs 24.7 events per 100 patient-years; HR, 0.91 [95% CI, 0.75-1.11]). The AKI follow-up clinic was associated with a lower risk of all-cause mortality (HR, 0.71 [95% CI, 0.55-0.91]). Patients aged at least 66 years who attended the AKI follow-up clinic were more likely to receive β-blockers (HR, 1.34 [95% CI, 1.02-1.77]) and statins (HR, 1.35 [95% CI, 1.05-1.74]), but not angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (HR, 1.21 [95% CI, 0.94-1.56]).

LIMITATIONS

Single-center study and residual confounding.

CONCLUSIONS

Specialized postdischarge follow-up for AKI survivors was not associated with a lower risk of major adverse kidney events but was associated with a lower risk of death and increased prescriptions for some cardioprotective medications.

The Impact of Angiotensin-Converting Enzyme Inhibitors or Angiotensin II Receptor Blockers on Clinical Outcomes of Acute Kidney Disease Patients: A Systematic Review and Meta-Analysis

Background: Acute kidney injury (AKI) may increase the risk of chronic kidney disease (CKD), development of end-stage renal disease (ESRD), and mortality. However, the impact of exposure to angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker (ACEi/ARB) in patients experiencing AKI/acute kidney disease (AKD) is still unclear. Methods: In this systematic review, we searched all relevant studies from PubMed, Embase, Cochrane, Medline, Collaboration Central Register of Controlled Clinical Trials, Cochrane Systematic Reviews, and ClinicalTrials.gov until July 21, 2020. We evaluated whether the exposure to ACEi/ARB after AKI onset alters recovery paths of AKD and impacts risks of all-cause mortality, recurrent AKI, or incident CKD. We rated the certainty of evidence according to Cochrane methods and the GRADE approach. Results: A total of seven articles, involving 70,801 patients, were included in this meta-analysis. The overall patient mortality rate in this meta-analysis was 28.4%. Among AKI patients, all-cause mortality was lower in ACEi/ARB users than in ACEi/ARB nonusers (log odds ratio (OR) -0.37, 95% confidence interval (CI): -0.42--0.32, p < 0.01). The risk of recurrent adverse kidney events after AKI was lower in ACEi/ARB users than in nonusers (logOR -0.25, 95% CI: -0.33--0.18, p < 0.01). The risk of hyperkalemia was higher in ACEi/ARB users than in nonusers (logOR 0.43, 95% CI: 0.27-0.59, p < 0.01). Patients with continued use of ACEi/ARB after AKI also had lower mortality risk than those prior ACEi/ARB users but who did not resume ACEi/ARB during AKD (logOR -0.36, 95% CI: -0.4--0.31, p < 0.01). Conclusions: Exposure to ACEi/ARB after AKI is associated with lower risks of all-cause mortality, recurrent AKI, and progression to incident CKD. Patients with AKI may have a survival benefit by continued use of ACEi/ARB; however, a higher incidence of hyperkalemia associated with ACEi/ARB usage among these patients deserves close clinical monitoring.

Validation of Risk Prediction Models to Inform Clinical Decisions After Acute Kidney Injury

Rationale & Objective

There is limited evidence to guide follow-up after acute kidney injury (AKI). Knowledge gaps include which patients to prioritize, at what time point, and for mitigation of which outcomes. In this study, we sought to compare the net benefit of risk model–based clinical decisions following AKI.

Study Design

External validation of 2 risk models of AKI outcomes: the Grampian -Aberdeen (United Kingdom) AKI readmissions model and the Alberta (Canada) kidney disease risk model of chronic kidney disease (CKD) glomerular (G) filtration rate categories 4 and 5 (CKD G4 and G5). Process mining to delineate existing care pathways.

Setting & Participants

Validation was based on data from adult hospital survivors of AKI from Grampian, 2011-2013.

Predictors

KDIGO-based measures of AKI severity and comorbidities specified in the original models.

Outcomes

Death or readmission within 90 days for all hospital survivors. Progression to new CKD G4-G5 for patients surviving at least 90 days after AKI.

Analytical Approach

Decision curve analysis to assess the “net benefit” of use of risk models to guide clinical care compared to alternative approaches (eg, prioritizing all AKI, severe AKI, or only those without kidney recovery).

Results

26,575 of 105,461 hospital survivors in Grampian (mean age, 60.9 ± 19.8 [SD] years) were included for validation of the death or readmission model, and 9,382 patients (mean age, 60.9 ± 19.8 years) for the CKD G4-G5 model. Both models discriminated well (area under the curve [AUC], 0.77 and 0.86, respectively). Decision curve analysis showed greater net benefit for follow up of all AKI than only severe AKI in most cases. Both original and refitted models provided net benefit superior to any other decision strategy. In process mining of all hospital discharges, 41% of readmissions and deaths occurred among people recovering after AKI. 1,464 of 3,776 people (39%) readmitted after AKI had received no intervening monitoring.

Limitations

Both original models overstated risks, indicating a need for regular updating.

Conclusions

Follow up after AKI has potential net benefit for preempting readmissions, death, and subsequent CKD progression. Decisions could be improved by using risk models and by focusing on AKI across a full spectrum of severity. The current lack of monitoring among many with poor outcomes indicates possible opportunities for implementation of decision support.