#1163 Baseline estimated GFR and the prognostic impact of rapid increases in serum creatinine after major elective surgery: a multicohort study
Notice bibliographique
Résumé
Abstract Background and Aims Acute kidney injury (AKI) is common after major surgery and is associated with increased mortality. Currently, the Kidney Disease: Improving Global Outcomes (KDIGO) criteria define AKI as an absolute creatinine increase ≥0.3 mg/dl within 48 hours, a relative creatinine increase ≥50% known or presumed to have occurred within 7 days, or a urine output <0.5 ml/kg/h for at least 6 hours. However, it remains contested whether small absolute creatinine increases should be viewed as equivalent to relative creatinine increases—especially for low baseline estimated glomerular filtration rate (eGFR) where such creatinine changes relate to smaller eGFR changes. Here, we used a multinational collaboration to investigate this uncertainty. Method We conducted a multinational population-based cohort study including adult patients from Denmark, Alberta (Canada), Grampian, and Tayside & Fife (United Kingdom) undergoing major elective surgery. The inclusion of patients undergoing major elective surgery allowed for accurate assessment of baseline eGFR and postoperative changes in creatinine. This is because it is standard practice in all the included cohorts to have a recent outpatient creatinine measurement before surgery and to monitor creatinine levels in the days following surgery. We ascertained the most recent outpatient eGFR before surgery using the 2009 creatinine-based Chronic Kidney Disease Epidemiology Collaboration equation. We determined both the highest relative increase in creatinine within 7 days and the highest absolute increase in creatinine within 2 days during the first 7 days after the day of surgery. The outcome of interest was death within 90 days after surgery. Logistic regressions were performed to construct heatmaps depicting age-, sex-, year-, and surgery type-standardized 90-day mortality according to absolute and relative creatinine increases across pre-operative baseline eGFR levels. Results We identified 314,136 surgical procedures (172,544 procedures from Denmark, 124,119 from Alberta, 9891 from Grampian, and 7582 from Tayside & Fife) performed in 276,988 patients with 13,906 deaths within 90 days. Across the populations, the median age ranged from 66 to 70 years, and 40 to 44% were female. Absolute creatinine increases: Compared to no change in creatinine, an absolute increase of 0.3 mg/dl (26.5 µmol/l) within 2 days was associated with a consistent 2.5–3.5 percentage point (%p) absolute increase in mortality for eGFR between 15 and 90 ml/min/1.73 m2 (Figs 1 and 2). The increase in mortality was >3.5%p at eGFR >90 mL/min/1.73 m² and <2.5%p at eGFR <15 mL/min/1.73 m², although the precision of these estimates was low. These absolute increases in mortality corresponded to a relative increase in mortality of 25% for a baseline eGFR of 15 ml/min/1.73 m2, 160% for a baseline eGFR of 90 ml/min/1.73 m2, and 244% for an eGFR of 120 ml/min/1.73 m2. Relative creatinine increases: The absolute increases in mortality between a 50% relative creatinine increase and no change within 7 days decreased with eGFR from 9.6%p for a baseline eGFR of 15 ml/min/1.73 m2 to 3.5%p for a baseline eGFR of 90 ml/min/1.73 m2 (Figs 1 and 2). After this point, it increased to 5.3%p for a baseline eGFR of 120 ml/min/1.73 m2. The corresponding relative increases in mortality rose from 134% for a baseline eGFR of 15 ml/min/1.73 m2 to 255% for a baseline eGFR of 60 ml/min/1.73 m2, after which it remained at the same level. Conclusion Across baseline eGFR levels >15 ml/min/1.73 m2, both an absolute creatinine increase of 0.3 mg/dl and a relative increase of 50% were associated with a considerably higher mortality than no change. Yet, the magnitude of the increase in risk was substantially higher for a 50% increase compared with a 0.3 mg/dl increase at low baseline eGFR. This distinction should be emphasized in future guidelines to improve the consistency of clinical interpretations.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».