POS0026 Risk of pneumonia-related hospitalisation in patients with giant cell arteritis and small vessel vasculitis: a nationwide population-based cohort study
Notice bibliographique
Résumé
Background: Patients with giant cell arteritis (GCA) and small vessel vasculitis (SVV) are treated with potent immunosuppressant drugs putting them at higher risk of infections and hospitalization compared to the general population [1, 2]. Much of existing literature focuses on overall infection risk, however, pneumonias are often reported as the most common infection [1, 2]. Thus, further describing and exploring the risk of pneumonia-related hospitalizations in patients with GCA and SVV are of importance. Objectives: This study aimed to assess the risk of hospitalization with pneumonia (HP) including Pneumocystis jirovecii pneumonia (PJP) among patients with vasculitis. Methods: This study was conducted as a nationwide population-based matched cohort study. It included patients diagnosed with GCA and SVV between 2000 to 2021 using the Danish National Patient Registry. Patients with GCA were identified using a validated algorithm [3], and patients with SVV were identified by using a modified version of two validated algorithms [4, 5] creating two separate cohorts (GCA and SVV). Each patient from the two cohorts was matched with 10 controls based on sex and year of birth. Using the pseudo-observation method, we calculated the cumulative incidence proportion (CIP), risk difference (RD) and relative risk (RR) for HP at one-, two- and five-years follow-up. The Aalen-Johansen estimator was used to plot the cumulative incidence of HP at 5 years of follow-up. Furthermore, we carried out two separate nested case-control analyses using a conditional logistic regression for the multivariable analyses, including all comorbidities and treatments as exposure variables. This was performed exclusively for patients diagnosed after December 31, 2009. In these nested case-control analyses, each patient with GCA or SVV hospitalized with pneumonia was matched on sex, year of birth, and time of diagnosis with two patients with GCA or SVV not being hospitalized with pneumonia. Results: The CIP of HP for 9307 patients with GCA was 6.0% (5.5;6.5), 9.4% (8.8;10.0), and 17.6% (16.8;18.4) after one, two, and five years of follow-up, respectively. The RD compared to matched controls was 3.0% (2.6;3.5), 3.8% (3.2;4.4), and 5.3% (4.5;6.1) after one, two, and five years of follow-up, respectively. Meanwhile, the RR decreased from 2.2 (2.0;2.4) after one year, 1.8 (1.7;1.9) after two years, and 1.5 (1.4;1.6) after five years of follow-up. For the 2401 patients with SVV, the CIP rose from 12.6% (11.2;13.9), to 17.9% (16.3;19.5), and 28.3% (26.4;30.3) during the follow-up period. The RD compared to the matched controls increased from 10.1% (8.8;11.5), 14.8% (12.3;15.4) and 20.4% (17.9;21.8) after one, two and five years of follow-up. Similar to patients with GCA, the RR declined from 7.2 (6.2;8.4), to 5.6 (4.9;6.3), and 3.9 (3.6;4.3). Figure 1 displays the five-year unadjusted CIP. The nested case-control analyses are presented in Table 1. In patients with GCA, all included variables were associated with HP. This included comorbidities, methotrexate treatment, and a cumulative prednisolone intake of more than 1000mg in the six months prior to hospitalization. For patients with SVV, chronic kidney disease, chronic lung disease, previous pneumonia, and obesity were associated with HP. Additionally, mycophenolate and rituximab were also associated with HP. Pneumonia in patients with GCA mainly involved common non-opportunistic bacterial pathogens, similar to the matched controls. In contrast, patients with SVV were more likely to develop opportunistic infections, such as Pseudomonas (3.2% vs 1.3% compared to matched controls) and PJP (6.0% vs 0.0% compared to matched controls). Conclusion: Patients with GCA and SVV demonstrated an increased risk of HP compared to their matched controls. The risk was highest during the early stages of the diseases, likely due to combination of intensive immunosuppressive treatments and the inflammatory burden early on. The greatest risk was observed in patients with SVV, where opportunistic infections were also demonstrated. Patient with recent immunosuppressive therapy and comorbidities were at an increased risk of HP. These findings highlight the need for preventative initiatives, particularly for patients receiving high-dose immunosuppressive therapy. REFERENCES: [1] Faurschou M. et al. Long-term risk and outcome of infection-related hospitalization in granulomatosis with polyangiitis: a nationwide population-based cohort study. Scandinavian Journal of Rheumatology. 2018, Vol. 47, pp. 475-80. [2] Wu J. et al. Incidence of infections associated with oral glucocorticoid dose in people diagnosed with polymyalgia rheumatica or giant cell arteritis: a cohort study in England. Canadian Medical Association Journal. Jun 2019, Vol. 191, 25, pp. 680-8. [3] Hjort PE. et al. Positive Predictive Value of the Giant Cell Arteritis Diagnosis in the Danish National Patient Registry: A Validation Study. Clinical Epidemiology. 2020, pp. 731-36. [4] Nelveg-Kristensen KE. et al. Increasing incidence and improved survival in ANCA-associated vasculitis: A Danish nationwide study. Nephrology Dialysis Transplantation. January 2022, Vol. 37, 1, pp. 63-71. [5] Sreih AG. et al. Development and validation of case-finding algorithms for the identification of patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in large healthcare administrative databases. Pharmacoepidemiology and Drug Safety. 2016, Vol. 25, pp. 1368-74. Acknowledgements: NIL . Disclosure of Interests: Mads Engell Refstrup Sørensen: None declared, René Lindholm Cordtz RC is employed by Novo Nordisk outside of the present study and is a former employee of IQVIA, Kirsten S. Duch: None declared, Maria Kristina Stilling-Vinther: None declared, Lene Dreyer LD has received research grant (paid to her institution) from BMS and AbbVie outside the current manuscript. She is member of the steering committee of the Danish Rheumatology Quality Registry (DANBIO, DRQ), which receives public funding from the hospital owners and funding from pharmaceutical companies, Karina Frahm Kirk: None declared, Mette Holland-Fischer: None declared, Salome Kristensen: None declared. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| 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 ».