Kidney Function and Potassium Monitoring After Initiation of Renin-Angiotensin-Aldosterone System Blockade Therapy and Outcomes in 2 North American Populations
Bibliographic record
Abstract
BACKGROUND: Clinical practice guidelines recommend routine kidney function and serum potassium testing within 30 days of initiating ACE (angiotensin-converting enzyme) inhibitor or angiotensin II receptor blocker therapy. However, evidence is lacking about whether follow-up testing reduces therapy-related adverse outcomes. METHODS AND RESULTS: We conducted 2 population-based retrospective cohort studies in Kaiser Permanente Northern California and Ontario, Canada. Patients with outpatient serum creatinine and potassium tests in the 30 days after starting ACE inhibitor or angiotensin II receptor blocker therapy were matched 1:1 to patients without follow-up tests. We evaluated the association of follow-up testing with 30-day all-cause mortality and hospitalization with acute kidney injury or hyperkalemia using Cox regression. We also developed and externally validated a risk score to identify patients at risk of having abnormally high serum creatinine and potassium values in follow-up. We identified 75 251 matched pairs initiating ACE inhibitor or angiotensin II receptor blocker therapy between January 1, 2007, and December 31, 2017, in Kaiser Permanente Northern California. Follow-up testing was not significantly associated with 30-day all-cause mortality in Kaiser Permanente Northern California (hazard ratio, 0.75 [95% CI, 0.54-1.06]) and was associated with higher mortality in 84 905 matched pairs in Ontario (hazard ratio, 1.32 [95% CI, 1.07-1.62]). In Kaiser Permanente Northern California, follow-up testing was significantly associated with higher rates of hospitalization with acute kidney injury (hazard ratio, 1.66 [95% CI, 1.10-2.22]) and hyperkalemia (hazard ratio, 3.36 [95% CI, 1.08-10.41]), as was observed in Ontario. The risk score for abnormal potassium provided good discrimination (area under the curve [AUC], 0.75) and excellent calibration of predicted risks, while the risk score for abnormal serum creatinine provided moderate discrimination (AUC, 0.62) but excellent calibration. CONCLUSIONS: Routine laboratory monitoring after ACE inhibitor or angiotensin II receptor blocker initiation was not associated with a lower risk of 30-day mortality. We identified patient subgroups in which targeted testing may be effective in identifying therapy-related changes in serum potassium or kidney function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".