key: cord-0984100-4fsubvu1 authors: Acat, Murat; Yildiz Gulhan, Pinar; Oner, Serkan; Turan, Muhammed Kamil title: Comparison of pirfenidone and corticosteroid treatments at the COVID‐19 pneumonia with the guide of artificial intelligence supported thoracic computed tomography date: 2021-10-17 journal: Int J Clin Pract DOI: 10.1111/ijcp.14961 sha: 427f6c3b4904911ab67898bc7e2e84e3d5f48d33 doc_id: 984100 cord_uid: 4fsubvu1 AIM: We aimed to investigate the effect of short‐term pirfenidone treatment on prolonged COVID‐19 pneumonia. METHOD: Hospital files of patients hospitalised with a diagnosis of critical COVID‐19 pneumonia from November 2020 to March 2021 were retrospectively reviewed. Chest computed tomography images taken both before treatment and 2 months after treatment, demographic characteristics and laboratory parameters of patients receiving pirfenidone + methylprednisolone (n = 13) and only methylprednisolones (n = 9) were recorded. Pulmonary function tests were performed after the second month of the treatment. CT involvement rates were determined by machine learning. RESULTS: A total of 22 patients, 13 of whom (59.1%) were using methylprednisolone + pirfenidone and 9 of whom (40.9%) were using only methylprednisolone were included. When the blood gas parameters and pulmonary function tests of the patients were compared at the end of the second month, it was found that the FEV1, FEV1%, FVC and FVC% values were statistically significantly higher in the methylprednisolone + pirfenidone group compared with the methylprednisolone group (P = .025, P = .012, P = .026 and P = .017, respectively). When the rates of change in CT scans at diagnosis and second month of treatment were examined, it was found that the involvement rates in the methylprednisolone + pirfenidone group were statistically significantly decreased (P < .001). CONCLUSION: Antifibrotic agents can reduce fibrosis that may develop in the future. These can also help dose reduction and/or non‐use strategy for methylprednisolone therapy, which has many side effects. Further large series and randomised controlled studies are needed on this subject. syndromes could be helpful in the treatment of the emerging COVID-19 outbreak. 2, 3 The SARS-CoV-2 infection has infected more than 50 million people around the world. SARS-CoV-2 infection, in the most severe cases, can cause tissue hyperinflammation, fibrosis and scarring, lung collapse, multi-organ dysfunction and death. Severely affected survivors have a trail of devastating pulmonary fibrosis, which physicians will need to urgently address and manage. While fibrosis is a physiologic response to any pulmonary infection, chest physicians across the globe are encountering vast numbers of patients who have recovered from their acute COVID-19 pneumonia only to be left with severe residual lung fibrosis and oxygen dependence. 4, 5 The presence of pulmonary fibrosis is probably a consequence of the cytokine storm. Some of these biological and pathological characteristics are shared with idiopathic pulmonary fibrosis (IPF) such as chronic inflammatory fibrotic lung disease caused by the synthesis and release of pro-inflammatory cytokines, including tumour necrosis factor alpha (TNFα) and interleukin-1-beta (IL-1β). Antifibrotic therapy with pirfenidone, a drug indicated for the treatment of IPF, could therefore play a key role in preventing serious or fatal lung complications. However, antifibrotic therapy could play an even more important role in combined regimens, once identified, with effective anti-inflammatory treatments. Combination therapy could act on the main anti-inflammatory and antifibrotic pathways in a synergistic way, mitigating the consequences of pulmonary fibrosis. 6 Pirfenidone was approved as an anti-fibrotic in China in December 2013 for the treatment of IPF. The reduction in the overexpression of transforming growth factor β (TGFβ), connective tissue growth factor (CTGF), platelet-derived growth factors (PDGF) and TNFα in inflammatory diseases plays a key role in the anti-fibrotic activity of pirfenidone. 7 Currently, there is no clear evidence as to which treatment is effective for improving prognosis in patients infected with SARS-CoV-2. To date, a large number of clinical trials have been conducted for drugs showing in vitro efficacy. In this study, we aimed to demonstrate the results of short-term (2 months) pirfenidone treatment in prolonged COVID-19 pneumonia, which has no effective treatment yet. In this study, the information of patients hospitalised with a diagnosis of critical COVID-19 pneumonia from November 2020 to March 2021 were retrospectively obtained from the hospital system. Chest CT images were taken both before treatment and 2 months after treatment, demographic characteristics and laboratory parameters of patients receiving pirfenidone + methylprednisolone (n = 13) and only methylprednisolones (n = 9) were recorded. Mild, moderate, and severe cases were not included. Additioally, we excluded the patients under 18 years of age and pregnant womens. Patients were classified according to the WHO classification system (WHO/2019-nCoV/clinical/2021.1). Patients who received pirfenidone treatment 2 weeks after the diagnosis of COVID-19 were included. Favipiravir, 3 days of high dose methylprednisolone (250 mg) followed by 0.5 mg/kg/d, and anticoagulant treatment were administered to all patients. The pirfenidone treatment was increased to a maximum of 2400 mg with weekly dose increments. Pulmonary function tests were performed in the second month of the treatment. The tests were performed using a standard spirometer (Spirolab ® -2) according to American Thoracic Society criteria while the patients were at rest and seated in the upright position. Chest CT scans were conducted with a 16-detector spiral CT scanner (Toshiba Alexion, Otawara, Japan) in the full inspiration phase in the supine position. Patients were instructed to hold their breath to minimise motion artefacts. CT images were created by taking axial sections with 256 × 256 matrix size and 3 mm reconstructed 5 mm section thickness. Tube voltage was 120 kVp, rotation time was 0.75 seconds, and pitch was 1 mm. The low-dose CT protocol available in the scanner was used in the standard setting for the • The SARS-CoV-2 infection has infected more than 50 million people around the world. • Severely affected survivors have a trail of devastating pulmonary fibrosis, which physicians will need to urgently address and manage. • Post-COVID fibrosis, may continue to be a challenge for physicians even after the pandemic. • Antifibrotic agents can reduce fibrosis that may develop in the future. • Also, these can help dose reduction and/or non-use strategy for methylprednisolone therapy, which has many side effects. scans (AIDR3D, Canon Medical Systems, Ōtawara, Japan). Average CTDIvol was 3.3 mGy (range: 2.2-4.9 mGy). Implementation of appropriate infection prevention and control measures were arranged in all suspected CT cases, consisting of prompt sanitation of CT facility and patient's isolation. Each patient had varying degrees of CT findings for COVID-19 pneumonia identified in previous studies 8, 9 such as ground-glass opacities, consolidation, crazy-paving pattern, reticular pattern, air bronchogram, vascular enlargement in the lesion, centrilobular nod- Images are transformed into soft tissue window to obtain the ROI of lungs. Therefore, pixel values of lungs are normalised to window minimum. Minimum filter is applied on soft tissue window and lungs are obtained on binary images. Hilar area, bronchi, bronchiolar, and pulmonary vessels are classified as lungs by filling blanks on binary images. Median filter is applied to remove small noises and artefacts. As a result, a mask is obtained for lungs. After, a sectional image view is taken into lung window and multiplied with mask values. As a result, the obtained image is a lung image that has suitable conditions to process. Sample images obtained after these processes are shown in Figure 1 . All possible threshold values were calculated with randomised cascade mean filter to enhance lung images that have suitable conditions to process in terms of contrast. In this study, length parameter was specified as 20 and repetition number parameter was specified as 10% of mask area. Randomised selected lines on images were generated using these parameters. These lines have pixel values on images. The mean of sequential two-pixel values on the lines were taken until only one value was obtained. The obtained value was assigned as the threshold value. 10, 11 Lung images were converted to binary images using all possible threshold values. Then, all binary images were added on themselves. As a result, lung images with suitable conditions to process were enhanced in terms of contrast. A sample is shown in Figure 2 . Images whose ROIs were segmented were classified by radiologists and chest disease specialists using a developed graphical user interface. Three classes were used in this study. The first class includes ground-glass opacities. The second class includes COVID lesions seen such as consolidation, air bronchogram, vascular enlargement in the lesion, centrilobular nodules, subpleural curvilinear line or reticular pattern. The third class includes vessels and bronchi. Sample images belonging to these classes are shown in 1890 ROIs were obtained using all CT images in this study. Specialists classified the obtained ROIs on CT images. Feature extraction was done based on parameters from Gray Level Cooccurrence Matrix (GLCM). Therefore, input vector was obtained for machine learning algorithms. Four difference angles of 0, π/2, π and 3π/4 were used while calculating the GLCM parameters of contrast, dissimilarity, homogeneity, angular second moment (ASM), energy and correlation. These parameters were calculated for each angle value 12, 13 . Besides, minimum, maximum, The patients were given an informed consent form and their written consent was obtained. (1) Acc = TP TP + FN + FP + TN (2) Sen = TP TP + FN (3) Spe = TN TN + FP (4) Mcc = TP ⋅ TN − FP ⋅ FN √ (TP + FP) ⋅ (TP + FN) ⋅ (TN + FP) ⋅ (TN + FN) F I G U R E 2 A sample image, (A) A total of 22 patients, 13 of whom (59.1%) were using methylprednisolone + pirfenidone and 9 of whom (40.9%) were using only methylprednisolone were included. All patients in both groups received methylprednisolone, high-dose methylprednisolone and favipiravir treatment during their hospitalisation. None of our patients received tocilizumab treatment (Table 1) . When patients' baseline laboratory parameters and hospitalisation periods were compared, it was found that the two groups were similar to each other (P > .05) ( Table 2) . Comparing blood gas values at the time of discharge, the pH value of the group receiving methylprednisolone + pirfenidone was found to be statistically significantly lower (P = .003). Other blood gas parameters were found to be similar between the two groups (P > .05) ( Table 3) . When the blood gas parameters and pulmonary function tests of the patients were compared at the end of the second month, it was found that the HCO3, FEV1, FEV1%, FVC and FVC% values were statistically significantly higher in the group receiving methylprednisolone + pirfenidone compared with the group receiving only methylprednisolone (P = .049, P = .025, P = .012, P = .026 and P = .017, respectively). The second month pH, pO2, pCO2, saturation and MEF values were found to be similar between the groups (P > .05). Table 4 shows the comparison of the groups in terms of blood gas and pulmonary function tests in the second month after discharge. The involvement rates in CT scans at diagnosis and second month of treatment were similar among the groups (P = .073 and P = .477, respectively). However, when the rates of change in CT scans at diagnosis and second month of treatment were examined, it was found that the involvement rates in the methylprednisolone + pirfenidone group were statistically significantly decreased (P < .001) ( Figure 5 ). The comparison of the involvement rates between the groups at diagnosis and second month of treatment are presented in Table 5 and the sample patients are presented in Figures 6 and 7 . The comparison of the change in the involvement rates of the groups is shown in Figure 1 . The performance of the decision system has been tested on the sections that were not shown to the system during training and reserved for testing, and the overall Acc value was calculated as 0.953. The performance metrics of the proposed method to make a final decision are shown in Table 6 . We found a significant difference in the percentages of pulmonary parenchymal involvement between the patients hospitalised with the diagnosis of critical COVID-19 pneumonia using only methylprednisolone and using methylprednisolone and pirfenidone. There was no difference in pre-treatment pulmonary involvement between the groups. Parenchymal involvement after two months The aetiology of pulmonary fibrosis is multifactorial and de- Comparison of the groups in terms of blood gas and pulmonary function tests at 2 mo after discharge Comparison of the before treatment and 2nd month involvement rates of the groups F I G U R E 6 A male patient on methylprednisolone therapy; There is a slight decrease in the rates of lung involvement in CT images passing at the same level before (A) and after treatment (B) predisposition. 14, 15 No statistically significant difference was found between the ages of the patients included in this study. In fibrosis in COVID-19 infection, inflammatory mediators such as transforming growth factor (TGF-beta), vascular endothelial growth factor (VEGF), interleukin 6 (IL-6) and tumour TNFα are likely to occur because of the initiation of the fibrotic cascade. Moreover, vascular dysfunction causes the progression of fibrosis. 16 pneumonia, as in our study. In a recent study, Umemura et al investigated the efficacy of nintedanib, an intracellular inhibitor of tyrosine kinases, in COVID-19 patients. They compered 30 patients who received nintedanib and 30 who did not. They did not find any significant difference in 28-day mortality but the lengths of MV were significantly shorter than the control group. CT scans were not different between two groups at baseline. However, the follow-up CT scan after leaving MV showed that percentages of high-attenuation areas were significantly lower in the nintedanib group. They stated that using an antifibrotic agent may be beneficial. 36 The involvement rates in CT scans at diagnosis and second month of treatment were similar. However, when the rates of change were examined, it was found that the involvement rates in the methylprednisolone + pirfenidone group were statistically significantly decreased (P < .001) ( Figures 6 and 7) . Although there is only one case series 12 One limitation of our study was the small patient population. Patients who received methylprednisolone treatment were taken as the control group and we had no placebo group that did not receive any treatment. Regarding pulmonary function tests, the diffusing capacity of the lung for carbon monoxide (DLCO) could not be evaluated. In conclusion, it is too early to reliably define long-term outcomes in patients recovering from a severe COVID-19 pneumonia. However, it is possible that the long-term complications of the COVID-19 pandemic, which affects millions, such as PC-fibrosis, may continue to be a challenge for physicians even after the pandemic. Antifibrotic agents can reduce fibrosis that may develop in the future. Also, these can help dose reduction and/or non-use strategy for methylprednisolone therapy, which has many side effects. Further large series and randomised controlled studies are needed on this subject. 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