Association of Serum Bicarbonate with Incident Gout in Patients with Advanced CKD
Bibliographic record
Abstract
Background: Patients with CKD are at increased risk for gout and alkalinization solubilizes uric acid. We sought to determine if baseline bicarbonate or change in bicarbonate was an independent predictor of incident gout in patients with CKD stages 3-5. Methods: Optum's de-identified Integrated Claims-Clinical dataset of US patients (2007-2019) was queried to identify patients with non-dialysis CKD stages 3-5 with 2 consecutive serum bicarbonate values 12 to <30 mEq/L, 28-365 days apart, with data ≥1 year prior and ≥2 years of post-index or death within 2 years. Patients without pre-existing gout were followed for up to 11.5 years for diagnosed incident gout (ICD-9 or ICD-10 diagnosis codes 274.** excluding 274.11, M10.* or M1A). Cox proportional hazards models were used to examine predictors of incident gout, controlling for demographic characteristics as well as BMI, time-dependent change in serum bicarbonate; and baseline covariates eGFR, serum bicarbonate, hypertriglyceridemia, hypercholesterolemia, hyperuricemia, high c-reactive protein, hypertension, diabetes, obstructive sleep apnea, irritable bowel syndrome, inflammatory bowel disease, Charlson Comorbidity score, and prescriptions for thiazide diuretics or metoprolol. Death was similarly evaluated as a competing risk. Results: 125,551/136,067 patients (92%) had no evidence of gout during the pre-index period. During the period up to 11.5-years of follow-up (median 4.2 years), the following covariates were most strongly associated with incident gout: male sex (HR 1.69, 95% CI:1.63-1.76), Black or Asian race (HR 1.52, 95% CI:1.44-1.60 and HR 1.47, CI:1.23-1.75), and hyperuricemia (HR 1.40, 95% CI:1.27-1.55). Hispanic ethnicity (HR 0.82, 95% CI:0.73-0.92), low-income status (HR 0.90, 95% CI:0.85-0.94), higher baseline eGFR (HR 0.98, 95% CI:0.979-0.983, and lower overall comorbidity burden (HR 0.98, 95% CI:0.97-0.99) were associated with a lower risk of gout. Baseline serum bicarbonate and time-dependent change in serum bicarbonate were not associated with incident gout. Conclusions: In this longitudinal analysis of patients with CKD, serum bicarbonate was not associated with the development of gout. Funding: Commercial Support - Tricida, Inc.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".