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The multisystemic effects of COVID-19 may continue for a longer time period following the acute phase, depending on the severity of the disease. However, long-term systemic transcriptomic changes associated with COVID-19 disease and the impact of disease severity are not fully understood. We aimed to investigate the impact of COVID-19 and its severity on transcriptomic alterations in peripheral blood mononuclear cells (PBMCs) following 1 year of the disease. PBMCs were isolated from the peripheral blood of healthy control donors who did not have COVID-19 (C; n = 13), from COVID-19 patients without pneumonia (NP; n = 11), and from COVID-19 patients with severe pneumonia (SP; n = 10) after 1-year of follow-up. Following RNA isolation from PBMCs, high-quality RNAs were sequenced after creating a library. Differentially expressed genes (DEGs) and differentially expressed long non-coding RNAs (DElncRNAs) were identified using Benjamini–Hochberg correction and they were analysed for hierarchical clustering and principal component analysis (PCA). Intergroup comparisons (C vs. NP, C vs. SP, and NP vs. SP) of DEGs and DElncRNAs were performed and hub genes were determined. Functional enrichment analyses of DEGs and DElncRNAs were made using Metascape (v3.5.20240101) and the first version of NCPATH. The RNA sequencing analysis revealed 4843 DEGs and 1056 DElncRNAs in “C vs. NP”, 1651 DEGs and 577 DElncRNAs in “C vs. SP”, and 954 DEGs and 148 DElncRNAs in “NP vs. SP”, with 291 DEGs and 70 DElncRNAs shared across all groups, respectively. We identified 14 hub genes from 291 DEGs, with functional enrichment analysis showing upregulated DEGs mainly linked to inflammation and osteoclast differentiation and downregulated DEGs to viral infections and immune responses. The analysis showed that 291 common and 14 hub genes were associated with pneumonia and that these genes could be regulated by the transcription factors JUN and NFκB1 carrying the NFκB binding site. We also revealed unique immune cell signatures across DEG categories indicating that the upregulated DEGs were associated with neutrophils and monocytes, while downregulated DEGs were associated with CD4 memory effector T cells. The comparative transcriptomic analysis of NP and SP groups with 52 gene signatures suggestive of IPF risk showed a lower risk of IPF in the SP group than the NP patients. Our findings suggest that COVID-19 may cause long term pathologies by modulating the expression of various DEGs, DeLncRNAs, and hub genes at the cellular level.

Objective: To determine post-discharge mortality and associated factors of the first-wave multicenter Turkish Thoracic Society (TTD)-TURCOVID study. Methods: In this retrospective cohort study, we analyzed the data of 18 of 26 centers included in the first TTD-TURCOVID study, and 1 112 cases diagnosed with COVID-19 between 11 March and 31 July 2020 participated in the study. All causes of death after COVID-19 discharge were recorded. Results: The mean age of the patients was (51.07±16.93) years, with 57.6% male patients. In the cohort group, 89.1% of COVID-19 treatment locations were hospital wards, 3.6% were intensive care units (ICUs), and 7.2% were community outpatients. In the longterm follow-up, the in-hospital mortality rate was 3.6% (95% CI 2.64.8), the post-discharge mortality rate was 2.8% (95% CI 1.9-3.9), and the total mortality was 6.3% (95% CI 5.0-7.8). After discharge, 63.3% of mortality overall occurred during the first six months. Mortality rates in post-discharge follow-ups were 12.7% (95% CI 8.0-30.6) in cancer patients, 10.8% (95% CI 6.3-22.9) in chronic obstructive pulmonary disease patients, 11.1% (95% CI 4.4-22.7) in heart failure patients, 7.8 (95% CI 3.8-14.3) in atherosclerotic heart disease patients, and 2.3% (95% CI 0.8-5.6) in diabetes mellitus patients. In smokers/ex-smokers, the all-mortality rates were higher than in non-smokers. Conclusions: This multicenter study showed that patients over 65 years of age, males, former/active smoker, ICU stay, lung, heart disease, and malignancy should be followed up for at least the first six months after discharge due to COVID-19.

Objective: To evaluate long-term effects of COVID-19, and to determine the risk factors in long-COVID in a cohort of the Turkish Thoracic Society (TTS)-TURCOVID multicenter registry. Methods: Thirteen centers participated with 831 patients; 504 patients were enrolled after exclusions. The study was designed in three-steps: (1) Phone questionnaire; (2) retrospective evaluation of the medical records; (3) face-to-face visit. Results: In the first step, 93.5% of the patients were hospitalized; 61.7% had a history of pneumonia at the time of diagnosis. A total of 27.1% reported clinical symptoms at the end of the first year. Dyspnea (17.00%), fatigue (6.30%), and weakness (5.00%) were the most prevalent long-term symptoms. The incidence of long-term symptoms was increased by 2.91 fold (95% CI 1.04-8.13, P=0.041) in the presence of chronic obstructive pulmonary disease and by 1.84 fold (95% CI 1.10-3.10, P=0.021) in the presence of pneumonia at initial diagnosis, 3.92 fold (95% Cl 2.29-6.72, P=0.001) of dyspnea and 1.69 fold (95% Cl 1.02-2.80, P=0.040) fatigue persists in the early-post-treatment period and 2.88 fold (95% Cl 1.52- 5.46, P=0.001) in the presence of emergency service admission in the post COVID period. In step 2, retrospective analysis of 231 patients revealed that 1.4% of the chest X-rays had not significantly improved at the end of the first year, while computed tomography (CT) scan detected fibrosis in 3.4%. In step 3, 138 (27.4%) patients admitted to face-to-face visit at the end of first year; at least one symptom persisted in 49.27% patients. The most common symptoms were dyspnea (27.60%), psychiatric symptoms (18.10%), and fatigue (17.40%). Thorax CT revealed fibrosis in 2.4% patients. Conclusions: COVID-19 symptoms can last for extended lengths of time, and severity of the disease as well as the presence of comorbidities might contribute to increased risk. Long-term clinical issues should be regularly evaluated after COVID-19.

Background and objectivesAlthough several repurposed antiviral drugs have been used for the treatment of COVID-19, only a few such as remdesivir and molnupiravir have shown promising effects. The objectives of our study were to investigate the association of repurposed antiviral drugs with COVID-19 morbidity.MethodsPatients admitted to 26 different hospitals located in 16 different provinces between March 11–July 18, 2020, were enrolled. Case definition was based on WHO criteria. Patients were managed according to the guidelines by Scientific Board of Ministry of Health of Turkey. Primary outcomes were length of hospitalization, intensive care unit (ICU) requirement, and intubation.ResultsWe retrospectively evaluated 1,472 COVID-19 adult patients; 57.1% were men (mean age = 51.9 ± 17.7years). A total of 210 (14.3%) had severe pneumonia, 115 (7.8%) were admitted to ICUs, and 69 (4.7%) were intubated during hospitalization. The median (interquartile range) of duration of hospitalization, including ICU admission, was 7 (5–12) days. Favipiravir (n = 328), lopinavir/ritonavir (n = 55), and oseltamivir (n = 761) were administered as antiviral agents, and hydroxychloroquine (HCQ, n = 1,382) and azithromycin (n = 738) were used for their immunomodulatory activity. Lopinavir/ritonavir (β [95% CI]: 4.71 [2.31–7.11]; p = 0.001), favipiravir (β [95% CI]: 3.55 [2.56–4.55]; p = 0.001) and HCQ (β [95% CI]: 0.84 [0.02–1.67]; p = 0.046) were associated with increased risk of lengthy hospital stays. Furthermore, favipiravir was associated with increased risks of ICU admission (OR [95% CI]: 3.02 [1.70–5.35]; p = 0.001) and invasive mechanical ventilation requirement (OR [95% CI]: 2.94 [1.28–6.75]; p = 0.011).ConclusionOur findings demonstrated that antiviral drugs including lopinavir, ritonavir, and favipiravir were associated with negative clinical outcomes such as increased risks for lengthy hospital stay, ICU admission, and invasive mechanical ventilation requirement. Therefore, repurposing such agents without proven clinical evidence might not be the best approach for COVID-19 treatment.