COVID-19 sonrası hastalarda akciğer sekelini baştan tahmin edebilir miyiz?

Year 2023, Volume: 14 Issue: 4, 760 - 776, 30.12.2023

Dorina Esendağlı , Ece Koç , Nilsu Buket Ercan , Buse Tekşam , Begüm Eda Türkay , Zehra Dilek Yağcı

https://doi.org/10.18663/tjcl.1385126

Abstract

Amaç: COVID-19 pnömonisi ile hastaneye yatırılan hastalar, uzun süreli standart tedavi veya antienflamatuar rejim uygulansa bile enfeksiyon sonrası akciğer fibrozisine ilerleyebilir. Hangi hasta grubunun ilerleyici akciğer hastalığına sahip olacağını tahmin etmek zordur. Bu çalışma enfeksiyonun başlangıcından itibaren daha sonra akciğer fibrozisini öngörebilecek olası biyobelirteçleri tanımlamayı amaçlamaktadır.
Gereç ve Yöntemler: Ocak-Aralık 2020 tarihleri arasında COVID-19 pnömonisi nedeniyle yatan ve PCR pozitif olan hastalar çalışmaya alındı. COVID-19 sonrası semptomlar ve akciğer sekel oluşumu açısından hastalar 12 ay boyunca takip edildi.
Bulgular: Çalışmaya ortanca yaşı 62 (R: 17-93) olan toplam 64 hasta dahil edildi ve %42.2 kadındı (n=27). 35 hastada (%54.7) COVID sonrası semptomlar mevcuttu, 8 hasta (%12.5) kaybedildi ve 22’si (%34.4) yeniden hastaneye yatırıldı. Hastaların %76.6'sının klinik seyri iyiydi ancak hastaların %54.7'sinde enfeksiyon sonrası sekel gelişti. Pnömoni skoru, kan oksijen satürasyon düzeyi, CRP ve başvuru sırasındaki troponin düzeyleri sekel gelişimi ile anlamlı olarak ilişkiliydi (p<0.05). Erkek cinsiyet, ileri yaş, hastanede yatış süresi, kötü klinik prognoz ve yoğun bakım ünitesine yatış ile birlikte hipertansiyon varlığı ve post-COVID semptomları sekel oluşumu ile korelasyon gösterdi (p<0.05). Yaş 63.5'in üzerinde, CRP'nin 24.1'den yüksek olması ve pnömoni skorunun 0.15'in üzerinde olması akciğer sekel tahmini için anlamlı bulundu.
Sonuç: Bu çalışma, COVID-19 enfeksiyonu sonrası akciğer sekellerinin enfeksiyonun başlangıcından itibaren tahmin edilebileceğini ve sonrasında önlem alınabileceğini göstermektedir.

Keywords

Biyobelirteçler, COVID-19, akciğer sekelleri, monitorizasyon

Ethical Statement

This study was performed in accordance with the Declaration of Helsinki. This human study was approved by the institutional review board on 18/02/2022 by No: KA22/92.

Supporting Institution

The authors declared that they did not receive any financial support during the research and authoring of this article.

Project Number

KA22/92.

Thanks

Thank you to Eylem Gül Ateş for giving a support to statistical analysis and interpretation.

Can we predict lung sequelae in post-COVID-19 patients?

Abstract

Aim: Patients hospitalized with COVID-19 pneumonia can progress to lung fibrosis after the infection even though given the standard treatment or the anti-inflammatory regimen for the long term. It is hard to predict which group of patients is going to have a progressive lung disease thus this study aims to define possible biomarkers at the acute onset of infections that might predict lung fibrosis afterwards.
Material and Methods: Patients hospitalized between January - December 2020 with pneumonia and a positive PCR for COVID-19 infection were included in the study. They were followed up for 12 months for post-COVID-19 symptoms and lung sequelae formation.
Results: A total of 64 patients were included with a median age of 62 (R: 17-93) and 42.2% were women (n=27). 35 patients (54.7%) had post-COVID symptoms, 8 (12.5%) of them died and 22 (34.4%) were re-hospitalized. 76.6% had a good clinical course but 54.7% of the patients developed sequelae after infection. The pneumonia score, blood oxygen saturation level, CRP, and troponin levels at admission were significantly related to sequelae development (p<0.05). Male gender, elderly age, hospitalization period duration, bad clinical prognosis, and intensive care unit admission together with the presence of Hypertension and post-COVID symptoms were correlated with sequelae formation (p<0.05). Age above 63.5, CRP higher than 24.1 and pneumonia score greater than 0.15 were significant cut-off values for lung sequelae prediction.
Conclusion: This study shows that lung sequelae after COVID-19 infection can be predicted from the start of infection and measures might be taken afterwards.

Keywords

Biomarkers, COVID-19, lung sequelae, monitoring

Project Number

KA22/92.

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