Reassessing the Need for Pre-Operative Transfusions in Sickle Cell Disease Patients with a High Baseline Hemoglobin
Notice bibliographique
Résumé
Abstract Background: Patients with sickle cell disease (SCD) are more likely to require surgical procedures, and to have post-operative complications compared to the general population. The TAPS trial demonstrated that pre-operative transfusion is associated with a 3.8-fold reduction in peri-operative complications in patients with SCD. Pre-operative exchange transfusion has not been shown to have benefit over simple top-up transfusion. Patients with SCD may have baseline hemoglobin levels higher than the usual 60-80 g/L for a variety of reasons including; non-hemoglobin SS genotype SCD, co-inheritance of deletion(s) in alpha globin genes, hereditary persistence fetal hemoglobin, and hydroxyurea (HU) use. It is less clear whether patients with pre-operative hemoglobin levels > 90 g/L would also benefit from pre-operative transfusions. Previous studies of pre-operative transfusions in SCD have largely not captured these patients, in part due to low HU uptake at the time of the study and exclusion of non-hemoglobin SS SCD. We conducted a retrospective cohort study to assess the role of pre-operative transfusion in patients with SCD and a high baseline hemoglobin. Methods: 1304 patients seen at The Hospital for Sick Children, Toronto between 2007 and 2017 were assessed for eligibility. Patients were included if they: had a baseline hemoglobin ≥ 90 g/L, were 1-18 years of age at the time of surgery, had a diagnosis of hemoglobin SS, SC, Sβ+-thalassemia or Sβ0-thalassemia SCD subtypes, and had a low or medium risk elective surgery under a general anesthetic. Surgeries were classified according to the Co-operative Study of Sickle Cell Disease. Post-operative complications were defined as one or more of the following within 30 days of surgery: fever, vaso-occlusive crisis (VOC), infection, bleeding requiring transfusion, acute chest syndrome (ACS), stroke, intensive care admission (ICU), emergency room visit after discharge, readmission to hospital after discharge, or death. The incidence of postoperative complications for those with a baseline hemoglobin ≥90 g/L was compared between those who received a transfusion and those who did not. To estimate the adjusted effect of pre-operative transfusion on the risk of developing post-operative complications, a multi-variable logistic regression model was fitted using the change-in-estimate procedure, where variables with the strongest influence on the crude (unadjusted) estimate were included as model covariates (i.e. key confounders). Results: 117 patients with a hemoglobin ≥90 g/L underwent a total of 137 procedures. The most frequent procedures included were: tonsillectomies/adenoidectomies (26), cholecystectomies (25), splenectomies (20), and umbilical hernia repairs (11). There were 22 procedures (16%) where a pre-operative transfusion was administered. All patients received simple top-up transfusions. Of these, 11 (50%) encountered at least one post-operative complication. In contrast, 22/115 (19.1%) procedures without a pre-operative transfusion experienced a post-operative complication. There was an increased risk of post-operative complications in the group that was transfused (p=0.003, OR=4.2, 95% CI 1.6-11). Adjusting for two key confounders identified during the modeling process (splenectomy and prior ACS), pre-operative transfusion was again found to be associated with an increased risk of post-operative complications (p=0.017, OR=3.6, 95% CI 1.2-9.2). The characteristics of these patients and the incidence and distribution of post-operative complications are shown in Table 1. Conclusion: Patients with SCD and a baseline hemoglobin ≥90 g/L who receive a pre-operative top-up transfusion have an increased risk of post-operative complications compared to those who are not transfused. In low and medium risk surgeries, a policy of withholding transfusions for such patients may be considered. Prospective studies validating these findings are needed. Disclosures No relevant conflicts of interest to declare.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 ».