FC 100ASSOCIATION OF SINGLE AND SERIAL MEASURES OF SERUM PHOSPHORUS WITH ADVERSE OUTCOMES IN PATIENTS ON PERITONEAL DIALYSIS: RESULTS FROM THE INTERNATIONAL PDOPPS
Notice bibliographique
Résumé
Abstract Background and Aims While it has been established that high serum phosphorus is associated with mortality in hemodialysis (HD) patients, there is limited evidence in the peritoneal dialysis (PD) setting. We evaluated the association of serum phosphorus with mortality and major adverse cardiovascular events (MACE) in patients on PD, and investigated various parameterizations using single and serial measurements of serum phosphorus. Method We utilized data from 7 countries in phase 1 (2014-2017) of the Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS): Australia, Canada, Japan, New Zealand, Thailand, the UK, and the US. We investigated the association of serum phosphorus and 3 outcomes: all-cause mortality, cardiovascular (CV) mortality, and MACE (CV mortality + non-fatal angina, myocardial infarction, stroke, and heart failure). We parameterized serum phosphorus using 4 different methods: (1) single measurement of baseline serum phosphorus [most recent measurement during 6-month run-in period]; (2) mean serum phosphorus over a 6-month run-in period; (3) number of months (over the past 6 months) with serum phosphorus above the target range (>4.5 mg/dL); (4) mean area-under-the-curve (AUC), calculated as the average amount of time spent with serum phosphorus >4.5 mg/dL multiplied by the extent to which this threshold was exceeded over 6 months. Cox regression was used to estimate the association between each of these 4 exposures with the time-to-event outcomes, in models thoroughly adjusted for possible confounders. Follow-up began after the 6-month run-in period and continued until the outcome occurred, 7 days after leaving the facility due to transfer or change in kidney replacement therapy modality, loss to follow-up, or end of study phase (whichever event occurred first). Results Our sample consisted of 5904 patients who were on PD. Those with higher serum phosphorus levels were younger and had lower hemoglobin levels. Compared to patients with serum phosphorus ≥3.5 to <4.5 mg/dL, we found an all-cause mortality hazard ratio (HR) of 1.62 (95% CI: 1.19, 2.20) for patients with serum phosphorus ≥ 7 mg/dL. Strong associations were also observed using serial phosphorus measures [Table]. For example, compared to the reference group of AUC=0, the HR (95% CI) of death was 1.49 (1.10, 2.00) for AUC >1 to 2; and 1.67 (1.15, 2.41) for AUC >2. Akaike Information Criteria (AIC) results showed that, among the 4 exposures, AUC was the strongest predictor of all-cause mortality, and the single phosphorus measure was the weakest predictor. Associations between serum phosphorus and adverse outcomes were generally stronger for CV death and MACE than for all-cause mortality [Table]. Conclusion As seen in HD patients, this analysis demonstrates that serum phosphorus is a strong predictor of adverse outcomes in patients on PD. When considering serial measurements of serum phosphorus, rates of adverse events began to rise at phosphorus levels >4.5 mg/dL. As recommended by KDIGO guidelines, serial measurements that consider a history of serum phosphorus excursions >4.5 mg/dL should be considered when assessing risks of adverse outcomes.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».