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Enregistrement W3209533924 · doi:10.1182/blood-2021-154182

Perioperative Anemia Management in Women Undergoing Gynecologic Procedures: A 10 Year Multisite Study

2021· article· en· W3209533924 sur OpenAlexaffabout
Nadia Gabarin, Emily Sirotich, Yang Liu, Menaka Pai, Lea Luketic, Donald M. Arnold, Michelle P. Zeller

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueBlood transfusion and management
Établissements canadiensCanadian Blood ServicesMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicinePerioperativeAnemiaBlood transfusionRetrospective cohort studyIntensive care unitBlood managementEmergency medicinePediatricsSurgeryIntensive care medicineInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background Preoperative anemia is a known risk factor for adverse patient outcomes. In women undergoing gynecologic surgery, preoperative anemia is independently associated with increased 30-day mortality, surgical complications, and hospital re-admission. Women with abnormal uterine bleeding and women undergoing gynecologic surgery remain under-studied and over-transfused. Patient blood management (PBM) initiatives are emerging from growing awareness of adverse outcomes associated with preoperative anemia. PBM efforts involve optimizing red cell mass and limiting unnecessary red blood cell (RBC) transfusions, with the goal of improving outcomes. Iron deficiency is a common cause of anemia in women with gynecologic sources of blood loss, and early identification and repletion of iron stores is an important component of PBM. Our research evaluated perioperative RBC utilization and intravenous (IV) iron use in women undergoing gynecologic procedures at three large academic hospitals. Methods This retrospective cohort study used data from the Transfusion Registry for Utilization Surveillance and Tracking database, a multihospital database network in Ontario, Canada. Canadian Classification of Health Interventions codes were used to identify women aged 15 and older who underwent gynecologic surgery with a hospital admission between January 1, 2010 and December 31, 2019 at three academic hospitals. Patients undergoing gynecologic surgery with malignant and non-malignant conditions were included. Patients who were pregnant and immediately postpartum were excluded. Collected data included patient demographics, laboratory investigations, RBC utilization, IV iron use, hospital length of admission, intensive care unit (ICU) admission, and in-hospital mortality. Data was collected from 90 days prior to gynecologic surgery to 30 days post gynecologic surgery. Only the first gynecologic surgery per patient was included in the analysis. Patients with an underlying malignancy were analyzed separately from patients without a malignancy diagnosis. Results A total of 4,822 patients with a gynecologic surgery were identified during the study period, with 4,842 hospital admissions. 3,687 patients had a malignancy diagnosis. We identified that 27.3% of all gynecologic surgery patients were anemic (hemoglobin (Hb) <120 g/L) on preoperative bloodwork. In the malignancy group, 798 patients (21.6%) received at least 1 unit RBC in the perioperative period, with 2.9% transfused in the 90 days prior to surgery, 12.6% transfused on the day of surgery, and 13.0% transfused within 30 days post-surgery. Of the non-malignancy patients, 58 patients (5.1%) had at least 1 unit RBC in the perioperative period, with 0.8% transfused in the 90 days prior to surgery, 1.9% transfused on the day of surgery, and 3.4% transfused within 30 days post-surgery (Table 1). Only 0.6% of patients in the malignancy group and 0.4% of patients in the non-malignancy group received IV iron in the perioperative period. Patients with a preoperative Hb< 120 g/L had an increased rate of ICU admission and longer hospital admission compared to patients with a preoperative Hb > 120 g/L; adverse outcomes were higher in patients with Hb< 80 g/L (Table 2). A logistic regression model adjusting for baseline characteristics demonstrated an association between preoperative anemia and ICU admission compared to non-anemic patients: for Hb 80-120 g/L, odds ratio (OR) 1.53, 95% CI 1.27-1.85, P <.0001; for Hb<80 g/L, OR 2.81, 95% CI 1.45-5.46, P=.0022. There was no significant change in transfusion rates from 2010 to 2019 (Figure 1). Conclusion Our retrospective cohort study of women undergoing gynecologic surgery is consistent with the findings of previous studies demonstrating that preoperative anemia is associated with adverse clinical outcomes in this population. IV iron was under-utilized in our study cohort; increased use of IV iron may have reduced unnecessary perioperative transfusions. 1 in 6 women in our study were transfused in the perioperative period. The appropriateness of these transfusions and the potential for preventing RBC transfusion in this patient population warrant further investigation. In contrast to other surgical specialties, transfusion rates in the gynecologic surgery population have been static over the past decade, suggesting a need for further PBM initiatives in this group. Figure 1 Figure 1. Disclosures Zeller: Canadian Blood Services: Consultancy, Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Canadian Insitutes of Health Research: Research Funding; American Society of Hematology: Honoraria.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,056
Score d'incertitude au seuil0,112

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,011
Tête enseignante GPT0,262
Écart entre enseignants0,251 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission2
Résumé présentoui

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