A randomized controlled trial examining the impact of low vs. moderate-intensity aerobic training in post-discharge COVID-19 older subjects.

OBJECTIVE: Post-COVID-19 patients complained of pain, fatigue, breathlessness, and reduction in quality of life which required planned intervention. This study aimed to compare the impact of 10 weeks of low vs. moderate-intensity aerobic training on physical fitness, psychological status, and quality of life in post-COVID-19 older subjects. PATIENTS AND METHODS: 72 patients were randomized into 3 equal groups, moderate-intensity exercise (MIG, n = 24), low-intensity exercise (LIG, n = 24), and control group (CG, n = 24). The exercise was done 40 min/4 times per week for 10 weeks. We measured exercise capacity using the six-minute walking test, 1 min sit-to-stand test, post-COVID-19 functional scale (PCFS), and quality of life using the SF-36 questionnaire and HAMILTON Anxiety and Depression Scale (HADS). RESULTS: There was no difference between groups regarding the demographic and most clinical characteristics of the subjects. Compared with CG there were statistically significant improvements in studying groups (MIG and LIG) with (p < 0.05) in most outcomes and the improvement was higher in MIG than in LIG in most outcomes. CONCLUSIONS: 10-week moderate-intensity and low-intensity aerobic training programs are effective with superior effect to moderate-intensity. Moderate-intensity aerobic exercise is more effective and feasible in post-discharge COVID-19 older subjects regarding exercise capacity, quality of life, and psychological status than low-intensity aerobic exercise.

Association of immature granulocytes (IG) with prognosis in severe COVID-19 patients Immature granulocytes and COVID-19

Aim: Recent research have shown that immature granulocytes (IG) can be utilized to predict severe infection, inflammation, and sepsis. As a result, the ability of IG levels to predict the severity of severe COVID-19 and its association with prognosis were studied in our study. Material and Mthods: A total of 317 patients diagnosed with severe COVID-19 in the emergency department were analyzed retrospectively. IGC and IG% levels were compared statistically between patient groups (survivors and non-survivors, those who received and did not get mechanical ventilation (MV) assistance, patients who required and did not require vasopressors, and hospital stays >=10 and <10 days). Result(s): When compared to patients who survived but did not get treatment, non-survivors who got MV and vasopressor support had substantially higher IGC and IG% values (for all p<0.001). Additionally, it was shown that the IG% of patients with hospital stays of >=10 days was substantially greater than that of patients with hospital stays of <10 days (p<0.001). While the IG% cut-off value was >0.45, it reached 75.5% sensitivity, 81.9% specificity, 87.6% NPV and 66.4% PPV for predicting mortality (AUC:0.86, p<0.001). Discussion(s): IG levels are a low-cost, easily accessible, and strong marker that may be used to predict mortality and prognosis in COVID-19 patients.Copyright © 2023, Derman Medical Publishing. All rights reserved.

DeepChestNet: Artificial intelligence approach for COVID-19 detection on computed tomography images

The conventional approach for identifying ground glass opacities (GGO) in medical imaging is to use a convolutional neural network (CNN), a subset of artificial intelligence, which provides promising performance in COVID-19 detection. However, CNN is still limited in capturing structured relationships of GGO as the texture and shape of the GGO can be confused with other structures in the image. In this paper, a novel framework called DeepChestNet is proposed that leverages structured relationships by jointly performing segmentation and classification on the lung, pulmonary lobe, and GGO, leading to enhanced detection of COVID-19 with findings. The performance of DeepChestNet in terms of dice similarity coefficient is 99.35%, 99.73%, and 97.89% for the lung, pulmonary lobe, and GGO segmentation, respectively. The experimental investigations on DeepChestNet-Lung, DeepChestNet-Lobe and DeepChestNet-COVID datasets, and comparison with several state-of-the-art approaches reveal the great potential of DeepChestNet for diagnosis of COVID-19 disease. © 2023 Wiley Periodicals LLC.

Comparison of COVID-19 patients who underwent thrombectomy with those in the pre-pandemic period in terms of etiology and prognosis.

OBJECTIVE: We aimed at determining the effectiveness of mechanical thrombectomy (MT) in patients with major vessel occlusion and infected with COVID-19, evaluating its clinical outcome and comparing it with non-COVID patients. PATIENTS AND METHODS: During the pandemic, 729 patients who underwent MT in stroke centers due to Acute Ischemic Stroke (AIS) with large vessel occlusion were evaluated. This study included 40 patients with a confirmed COVID-19 diagnosis by a positive PCR test between March 11, 2020, and December 31, 2020. These patients were compared to 409 patients who underwent MT due to major vessel occlusion between March 11, 2019, and December 31, 2019. RESULTS: Of the patients with AIS who are infected with COVID-19, 62.5% were males, and all patients have a median age of 63.5 ± 14.4 years. The median NIHSS score of the COVID-19 group was significantly higher than that of the non-COVID-19 groups. Dissection was significantly more in the COVID-19 group. The mortality rates at 3 months were higher in the COVID-19 groups compared to non-COVID-19 groups. CONCLUSIONS: This study revealed an increased frequency of dissection in patients with COVID-19. COVID-19-related ischemic strokes are associated with worse functional outcomes and higher mortality rates than non-COVID-19 ischemic strokes.

Specialist physicians battle against the COVID-19 pandemic: the relationship between specialist physicians working conditions and levels of burnout during the COVID-19 pandemic.

OBJECTIVE: This study was planned to determine the burnout levels of physicians during the COVID-19 pandemic, and to contribute to taking the necessary measures by determining the associated factors. MATERIALS AND METHODS: This research was designed via Google Online Form as an online survey with questions of Sociodemographic Data Form, Maslach Burnout Inventory and Beck Anxiety Inventory and was conducted with 40 specialist physicians actively working at the Sakarya University Training and Research Hospital. The same questionnaire was re-applied online after two months, and 24 out of 40 physicians were accessed. The SPSS 25 (IBM, Armonk, NY, USA) program was used for the analysis of the data. RESULTS: According to the Maslach Burnout Inventory applied in the pre-test, it was found that the feeling of personal accomplishment was high, emotional burnout was normal, and depersonalization was low. Anxiety and burnout were found to be positively correlated, and there were no statistically significant differences in the average values of the pre-and post-test Maslach Burnout Inventory and Beck Anxiety Inventory scores. CONCLUSIONS: Detecting possible burnout in physicians working in a pandemic, identifying associated factors and taking required measures can be beneficial both for physicians and society from a biopsychosocial perspective.