Metabolic Acidosis and Adverse Outcomes and Costs in CKD: An Observational Cohort Study
Notice bibliographique
Résumé
Rationale & ObjectiveMetabolic acidosis is a risk factor for progression of chronic kidney disease (CKD), but little is known about its effect on health care costs and resource utilization. We describe the associations between metabolic acidosis, adverse kidney outcomes, and health care costs in patients with CKD stages G3-G5 and not receiving dialysis.Study DesignRetrospective cohort study.Setting & ParticipantsAn integrated claims-clinical data set of US patients with CKD stages G3-G5, with serum bicarbonate values of 12 to <22 mEq/L (metabolic acidosis group) or 22 to 29 mEq/L (normal serum bicarbonate level group).PredictorThe primary exposure variable was the baseline serum bicarbonate level.OutcomesThe primary clinical outcome was the composite of all-cause mortality, maintenance dialysis, kidney transplant, or a decline in the estimated glomerular filtration rate of ≥40% (DD40). The primary cost outcome was all-cause predicted per-patient per-year cost, assessed over a 2-year outcome period.Analytical ApproachLogistic and generalized linear regression models, adjusted for key covariates such as age, sex, race, kidney function, comorbidities, and pharmacy insurance coverage, were used to assess serum bicarbonate levels as a predictor of DD40 and health care costs, respectively.Results51,558 patients qualified. The metabolic acidosis group experienced higher rates of DD40 (48.3% vs. 16.7%, P < 0.001) and higher all-cause yearly costs ($65,172 vs. $24,681, P < 0.001). Two-year adjusted odds ratio of DD40 per 1-mEq/L increase in serum bicarbonate levels was 0.873 (95% CI, 0.866-0.879); the parameter estimate (±SE) for costs was −0.070 ± 0.0075 (P < 0.001).LimitationsPossible residual confounding.ConclusionsPatients with CKD and metabolic acidosis had higher costs and rates of adverse kidney outcomes compared with patients with normal serum bicarbonate levels. Each 1-mEq/L increase in serum bicarbonate levels was associated with a 13% decrease in 2-year DD40 events and a 7% decrease in per-patient per-year cost. Metabolic acidosis is a risk factor for progression of chronic kidney disease (CKD), but little is known about its effect on health care costs and resource utilization. We describe the associations between metabolic acidosis, adverse kidney outcomes, and health care costs in patients with CKD stages G3-G5 and not receiving dialysis. Retrospective cohort study. An integrated claims-clinical data set of US patients with CKD stages G3-G5, with serum bicarbonate values of 12 to <22 mEq/L (metabolic acidosis group) or 22 to 29 mEq/L (normal serum bicarbonate level group). The primary exposure variable was the baseline serum bicarbonate level. The primary clinical outcome was the composite of all-cause mortality, maintenance dialysis, kidney transplant, or a decline in the estimated glomerular filtration rate of ≥40% (DD40). The primary cost outcome was all-cause predicted per-patient per-year cost, assessed over a 2-year outcome period. Logistic and generalized linear regression models, adjusted for key covariates such as age, sex, race, kidney function, comorbidities, and pharmacy insurance coverage, were used to assess serum bicarbonate levels as a predictor of DD40 and health care costs, respectively. 51,558 patients qualified. The metabolic acidosis group experienced higher rates of DD40 (48.3% vs. 16.7%, P < 0.001) and higher all-cause yearly costs ($65,172 vs. $24,681, P < 0.001). Two-year adjusted odds ratio of DD40 per 1-mEq/L increase in serum bicarbonate levels was 0.873 (95% CI, 0.866-0.879); the parameter estimate (±SE) for costs was −0.070 ± 0.0075 (P < 0.001). Possible residual confounding. Patients with CKD and metabolic acidosis had higher costs and rates of adverse kidney outcomes compared with patients with normal serum bicarbonate levels. Each 1-mEq/L increase in serum bicarbonate levels was associated with a 13% decrease in 2-year DD40 events and a 7% decrease in per-patient per-year cost.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».