Mortality associated with warm autoimmune hemolytic anemia among Medicare beneficiaries
Notice bibliographique
Résumé
Abstract INTRODUCTION: Warm autoimmune hemolytic anemia (wAIHA) is a rare, autoimmune-mediated hematologic disorder associated with significant morbidity and mortality and may occur as a primary condition or secondary to an underlying disorder. It is the most common subtype of autoimmune hemolytic anemia (AIHA), accounting for 75-80% of AIHA cases. Older adults with wAIHA are particularly vulnerable, as they often have multiple comorbidities and are already at elevated risk of death. This study aimed to assess mortality associated with wAIHA. METHODS: Adults with wAIHA (wAIHA cohort) and without AIHA (non-AIHA cohort) were identified from the 100% Medicare Fee-for-Service database (10/01/2019–12/31/2023). Evidence of wAIHA was defined as one of the following: 1) a primary wAIHA diagnosis (International Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM]: D59.11) in the inpatient setting (first instance of wAIHA diagnosis defined the index date), 2) ≥2 wAIHA diagnosis in any setting ≥30 days apart (second instance of wAIHA diagnosis defined the index date), or 3) a wAIHA diagnosis preceded ≥30 days by any AIHA diagnosis (ICD-10-CM: D59.10, D59.19, D59.8, D59.9; first instance of wAIHA diagnosis defined the index date). Patients in the wAIHA cohort were excluded if they had a diagnosis for cold or mixed-type AIHA (ICD-10-CM: D59.12, D59.13) during the baseline period (12 months before index). The non-AIHA cohort had no diagnoses for any AIHA during the study period; a random index date during continuous Medicare eligibility was selected and patients were matched 1:10 with the wAIHA cohort based on age on index date. Using overlap weighting, age-matched cohorts were further weighted on sex, race, region, index year, and baseline comorbidities associated with mortality, excluding conditions defining secondary wAIHA. Mortality during the follow-up period was evaluated between the weighted cohorts using the Kaplan-Meier method and Cox proportional hazard models. Patients whose death was not observed were censored at the earlier of the end of continuous Medicare eligibility or data availability. RESULTS: 3,112 and 31,120 patients were included in the wAIHA and non-AIHA cohorts, respectively. After weighting, among the wAIHA vs non-AIHA cohorts, mean [standard deviation; SD] age was 74.4 [11.6] vs 74.6 [11.2] years, the proportion of female were 56.1% vs 56.1%, mean [SD] Quan-CCI without secondary wAIHA-defining conditions was 1.9 [2.0] vs 1.9 [2.1], and mean [SD] follow-up time was 17.2 [11.7] vs 14.9 [11.4] months, respectively. In addition, 53.7% of the wAIHA cohort had secondary wAIHA. The most common secondary wAIHA-defining conditions were autoimmune and inflammatory diseases (wAIHA cohort: 27.8%; non-AIHA cohort: 11.0%), hematologic and lymphoproliferative disorders (wAIHA cohort: 23.8%; non-AIHA cohort: 1.3%), and solid tumors (wAIHA cohort: 16.8%; non-AIHA cohort: 12.6%). The most common comorbidities for both cohorts were hypertension (wAIHA cohort: 77.4%; non-AIHA cohort: 78.3%) and dyslipidemia (wAIHA cohort: 72.2%; non-AIHA cohort: 74.7%). Survival rates in the wAIHA and non-AIHA cohorts were 80.3% vs 84.0% at 12 months, 70.7% vs 77.6% at 24 months, and 63.7% vs 73.1% at 36 months, respectively (all p<0.001). Patients with wAIHA were at 20%, 27%, and 30% higher risk of death at 12, 24, and 36 months, respectively, compared to patients without AIHA (hazard ratios: 1.20, 1.27, and 1.30; all p<0.001). CONCLUSIONS: This large retrospective study is the first to assess real-world incremental mortality associated with wAIHA among Medicare beneficiaries. Patients with wAIHA were at significantly greater risk of death following the initial diagnosis. These results may point to potential gaps in early diagnosis and effective disease management, which could contribute to increased mortality. Future research should focus on specific subgroups within the wAIHA cohort to identify differences in mortality as well as characteristics that may be associated with death.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».