Nintedanib vs pirfenidone in the management of COVID-19 lung fibrosis: A single-centre study.


Journal

The journal of the Royal College of Physicians of Edinburgh
ISSN: 2042-8189
Titre abrégé: J R Coll Physicians Edinb
Pays: England
ID NLM: 101144324

Informations de publication

Date de publication:
06 2022
Historique:
entrez: 23 9 2022
pubmed: 24 9 2022
medline: 28 9 2022
Statut: ppublish

Résumé

COVID-19 pneumonia is complicated with residual lung fibrosis, as evidenced by imaging and postmortem pathological findings. In addition to steroids, we compared the efficacy of nintedanib and pirfenidone in the management of COVID-19 lung fibrosis measured by CT severity score (CTSS). All cases of COVID-19 pneumonia diagnosed as COVID-19 positive by RT-PCR having SpO Out of 90 patients, 56 patients completed the study. Among three groups, 19 (33.9%) patients received steroids (control) only, 16 (28.6%) patients received steroids with pirfenidone and 21 (37.5%) patients received steroids with nintedanib. The study population had a mean (±SD) age of 52.5 ± 10.1 years, mean (±SD) C-reactive protein of 97.1 ± 102.2 mg/L (normal <6 mg/L), mean (±SD) serum ferritin 459.4 ± 305.5 ng/mL (normal <250 ng/mL), mean (±SD) serum d-dimer level 2.1 ± 2.6 μg/mL (normal <0.5 μg/mL) and mean (±SD) CTSS of 16.9 ± 4.3. There was significant improvement in CTSS in group receiving nintedanib compared to pirfenidone at 12 weeks (3.67 ± 1.21 vs 9.07 ± 1.12) with a Along with steroids in the treatment of COVID-19 lung fibrosis, there was a significant improvement in lung CTSS with nintedanib compared to pirfenidone.

Sections du résumé

BACKGROUND
COVID-19 pneumonia is complicated with residual lung fibrosis, as evidenced by imaging and postmortem pathological findings. In addition to steroids, we compared the efficacy of nintedanib and pirfenidone in the management of COVID-19 lung fibrosis measured by CT severity score (CTSS).
METHODS
All cases of COVID-19 pneumonia diagnosed as COVID-19 positive by RT-PCR having SpO
RESULTS
Out of 90 patients, 56 patients completed the study. Among three groups, 19 (33.9%) patients received steroids (control) only, 16 (28.6%) patients received steroids with pirfenidone and 21 (37.5%) patients received steroids with nintedanib. The study population had a mean (±SD) age of 52.5 ± 10.1 years, mean (±SD) C-reactive protein of 97.1 ± 102.2 mg/L (normal <6 mg/L), mean (±SD) serum ferritin 459.4 ± 305.5 ng/mL (normal <250 ng/mL), mean (±SD) serum d-dimer level 2.1 ± 2.6 μg/mL (normal <0.5 μg/mL) and mean (±SD) CTSS of 16.9 ± 4.3. There was significant improvement in CTSS in group receiving nintedanib compared to pirfenidone at 12 weeks (3.67 ± 1.21 vs 9.07 ± 1.12) with a
CONCLUSION
Along with steroids in the treatment of COVID-19 lung fibrosis, there was a significant improvement in lung CTSS with nintedanib compared to pirfenidone.

Identifiants

pubmed: 36146989
doi: 10.1177/14782715221103402
doi:

Substances chimiques

Indoles 0
Pyridones 0
C-Reactive Protein 9007-41-4
Ferritins 9007-73-2
Prednisolone 9PHQ9Y1OLM
pirfenidone D7NLD2JX7U
nintedanib G6HRD2P839

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

100-104

Auteurs

Pratima Singh (P)

Department of Pulmonary Medicine, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, Odisha, India.

Debasis Behera (D)

Department of Pulmonary Medicine, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, Odisha, India.

Saurabh Gupta (S)

Department of Pulmonary Medicine, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, Odisha, India.

Akash Deep (A)

Department of Pulmonary Medicine, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, Odisha, India.

Subhadra Priyadarshini (S)

Department of Research and Development, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, Odisha, India.

Prasanta Padhan (P)

Department of Clinical Immunology and Rheumatology, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, Odisha, India.

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Classifications MeSH