Blood Loss Due to Laboratory Testing in Critical Care Patients: A Retrospective Cohort Study
Notice bibliographique
Résumé
Abstract Background: Anemia and red blood cell (RBC) transfusions occur frequently in intensive care unit (ICU) patients and are associated with morbidity and mortality. Observational data suggest that anemia (nadir hemoglobin ≤ 9 g/dL) in ICU patients is associated with an increased risk of death within 30 days (OR 1.54, 95% confidence interval [CI] 1.12-2.12). Although anemia in this population is likely multifactorial, phlebotomy for laboratory testing is substantial (up to 41 mL/day) and may be a modifiable contributor as only 10% of the blood collected is required for analysis. This study aims to (i) characterize the blood volume taken for laboratory testing in ICU patients, and (ii) explore the effect of blood taken for testing on rates of RBC transfusion and anemia in a contemporary cohort of ICU patients. Methods: We conducted a retrospective cohort study of consecutive adult patients, age ≥18 years, admitted to a medical-surgical ICU for ≥48 hours in Hamilton, Ontario between November 1, 2012 to October 1, 2015. We extracted data from previously validated administrative databases. The primary outcome was estimated volume of blood drawn for laboratory testing during index ICU admission calculated using the number of unique blood specimens drawn and known sampling tube volumes. Secondary outcomes included: incidence of severe anemia (hemoglobin ≤9 g/dL), discharge hemoglobin adjusted for RBC transfusion (1.0 g/dL subtracted for each RBC transfusion administered), proportion of patients receiving RBC transfusion, number of RBC units transfused per patient, duration of ICU admission and ICU mortality. Categorical data are reported as counts and proportions. Continuous data are reported as means with standard deviations (SD) or medians with interquartile range (IQR). Predictors of RBC transfusion were examined using Cox regression analysis. P-values <0.05 were considered statistically significant. Results: We included 7,273 ICU patients. The median age was 66 years (IQR 54-76 years) and 40.8% of patients were female. Most responsible diagnosis was circulatory (33.3%), followed by injury/poisoning (15.9%), respiratory (12.8%), and gastrointestinal (9.2%). The ICU mortality rate was 13.8% and the median ICU length of stay was 5 days (IQR 3-10 days). On ICU admission, median hemoglobin value was 9.7 g/dL (IQR 8.2-11.6 g/dL) and 39.6% of patients had hemoglobin ≤ 9.0 g/dL. Median blood loss due to laboratory testing was 25 mL per patient per day (IQR 14-43 mL) and 213 mL per patient for the ICU admission (IQR 133-382 mL). On ICU discharge, median hemoglobin was 8.4 g/dL (IQR 5.8-10.5 g/dL), and 67.0% of patients had hemoglobin ≤ 9.0 g/dL while in ICU. After adjusting for RBC transfusions, the median decrease in hemoglobin from ICU admission to discharge was 1.2 g/dL (IQR 0-2.9 g/dL). RBC transfusions were administered to 47.5% of patients while in the ICU with 37.3% of these patients receiving 5 or more units. The median number of RBC units received in transfused patients was 3 (IQR 2-7). Additional blood drawn for laboratory testing of 150 mL from day 2 to day 7 of ICU admission (hazard ratio [HR] 2.3, 95%CI 2.1-2.5), hematologic diagnosis vs. other (HR 1.5, 95%CI 1.2-2.0), and RBC transfusion prior to ICU admission vs. none (HR 1.5, 95%CI 1.2-1.9) were associated with a higher risk of RBC transfusion in the ICU. Conclusions: Anemia and RBC transfusions are frequent in ICU patients with two-thirds of patients developing severe anemia (hemoglobin <9.0 g/dL) and 47.5% receiving RBC transfusion, respectively. Our results suggest that blood loss for laboratory testing remains substantial in contemporary medical-surgical ICU patients and is associated with the need for RBC transfusion. Strategies to reduce blood loss from laboratory testing represent an area for further prospective investigation. Disclosures Siegal: BMS-Pfizer: Honoraria; Bayer: Honoraria; Portola Pharmaceuticals: Honoraria.
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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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| 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 | 0,000 | 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 ».