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BackgroundCOVID-19 was declared a pandemic on March 11, 2020. Given that the severe shortage of hospital beds has led to early discharge and insufficient patient education on home care routines and isolation protocols, the close follow-up of patients and their immediate relatives is an integral part of transitioning from hospital care to home care for patients with COVID-19. ObjectiveWe designed the Tele-COVID-19 prospective cohort to follow-up with COVID-19 patients in Tehran, Iran, and improve health care delivery and the recording of postdischarge patients’ clinical profiles. MethodsAll adult patients who were admitted to the COVID-19 wards of teaching hospitals in Tehran, Iran were eligible to participate in this cohort study. At baseline, patients were recruited from 4 major hospitals from March 9, 2020 to May 20, 2020. Telephone follow-ups, which were led by volunteer medical students, were conducted on postdischarge days 1-3, 5, 7, 10, and 14. We collected data on a range of sociodemographic, epidemiological, and clinical characteristics by using a standard questionnaire. ResultsOf the 950 patients with confirmed COVID-19 who were approached, 823 (response rate: 86.6%) consented and were enrolled into the cohort. Of the 823 participants, 449 (54.5%) were male. The mean age of participants was 50.1 years (SD 12.6 years). During the initial data collection phase, more than 5000 phone calls were made and over 577 reports of critical patients who were in need of urgent medical attention were recorded. ConclusionsThe Tele-COVID-19 cohort will provide patients with sufficient education on home care and isolation, and medical advice on care and the proper use of drugs. In addition, by preventing unnecessary hospital returns and providing information on household SARS-CoV-2 transmission as early as possible, this cohort will help with effective disease management in resource-limited settings. International Registered Report Identifier (IRRID)DERR1-10.2196/23316

Background: The differential diagnosis of tuberculous pleural effusion (TPE) and malignant pleural effusion (MPE) is difficult because the biochemical profiles are similar. The present study aimed to differentiate TPE from MPE, using a decision tree and a weighted sparse representation-based classification (WSRC) method, based on the best combination of routine pleural effusion fluid biomarkers. Materials and Methods: The routine biomarkers of pleural fluid, including differential cell count, lactate dehydrogenase (LDH), protein, glucose and adenosine deaminase (ADA), were measured in 236 patients (100 with TPE and 136 with MPE). A Sequential Forward Selection (SFS) algorithm was employed to obtain the best combination of parameters for the classification of pleural effusions. Moreover, WSRC was compared to the standard sparse representation-based classification (SRC) and the Support Vector Machine (SVM) methods for classification accuracy. Results: ADA provided the highest diagnostic performance in differentiating TPE from MPE, with 91.91% sensitivity and 74.0% specificity. The best combination of parameters for discriminating TPE from MPE included age, ADA, polynuclear leukocytes and lymphocytes. WSRC outperformed the SRC and SVM methods, with an area under the curve of 0.877, sensitivity of 93.38%, and specificity of 82.0%. The generated flowchart of the decision tree demonstrated 87.2% accuracy for discriminating TPE from MPE. Conclusion: This study indicates that a decision tree and a WSRC are novel, noninvasive, and inexpensive methods, which can be useful in discriminating between TPE and MPE, based on the combination of routine pleural fluid biomarkers. [ABSTRACT FROM AUTHOR]

Background: COVID-19 was declared a pandemic on March 11, 2020. Given that the severe shortage of hospital beds has led to early discharge and insufficient patient education on home care routines and isolation protocols, the close follow-up of patients and their immediate relatives is an integral part of transitioning from hospital care to home care for patients with COVID-19. Objective: We designed the Tele-COVID-19 prospective cohort to follow-up with COVID-19 patients in Tehran, Iran, and improve health care delivery and the recording of postdischarge patients' clinical profiles. Methods: All adult patients who were admitted to the COVID-19 wards of teaching hospitals in Tehran, Iran were eligible to participate in this cohort study. At baseline, patients were recruited from 4 major hospitals from March 9, 2020 to May 20, 2020. Telephone follow-ups, which were led by volunteer medical students, were conducted on postdischarge days 1-3, 5, 7, 10, and 14. We collected data on a range of sociodemographic, epidemiological, and clinical characteristics by using a standard questionnaire. Results: Of the 950 patients with confirmed COVID-19 who were approached, 823 (response rate: 86.6%) consented and were enrolled into the cohort. Of the 823 participants, 449 (54.5%) were male. The mean age of participants was 50.1 years (SD 12.6 years). During the initial data collection phase, more than 5000 phone calls were made and over 577 reports of critical patients who were in need of urgent medical attention were recorded. Conclusions: The Tele-COVID-19 cohort will provide patients with sufficient education on home care and isolation, and medical advice on care and the proper use of drugs. In addition, by preventing unnecessary hospital returns and providing information on household SARS-CoV-2 transmission as early as possible, this cohort will help with effective disease management in resource-limited settings. International Registered Report Identifier (IRRID): DERR1-10.2196/23316 JMIR Res Protoc 2021;10(2):e23316 doi:10.2196/23316 We help JMIR researchers to raise funds to pursue their research and development aimed at tackling important health and technology challenges. If you would like to show your support for this author, please donate using the button below. The funds raised will directly benefit the corresponding author of this article (minus 8% admin fees). Your donations will help this author to continue publishing open access papers in JMIR journals. Donations of over $100 may also be acknowledged in future publications. Submit Suggested contribution levels: $20/$50/$100 [ABSTRACT FROM AUTHOR]

Introduction: Recently, Covid 19 as a fatal virus has been known as the cause of the pandemic. Different number of the mortality rate in various societies have been reported. However, it seems the underlying comorbidities increase the risk of mortality and the severity of presentation. In this study we evaluated the pattern of presentation of COVID-19 among cancerous patients in terms of severity., Method: between 20th February to 22nd April of 2020, among 214 hospitalized patients because of COVID-19. 41 patients revealed the cancer as a synchronous comorbidity. These patients based on the severity of COVID-19 infection presentation were divided to mild and severe groups. Then, the demographic characteristics, manifestation and laboratory data between these groups were compared., Result: about 19 (46.34%) of 41 cases were categorized as severe forms of COVID-19 with malignancy. The mean age of severe groups was significantly higher (P=0.00). Dyspnea (48.78%), cough (46.34%) and myalgia (24.39%) were the most common clinical features among cancerous patients with COVID-19.  diarrhea and nearly cough caused significant effects on severe form of presentation of COVID-19 infection (P=0.05, P=0.06, respectively). Hematological cancers were the most frequent types of cancer among these patients (46.34%). White Blood Cell counts were significantly lower in severe groups (P=0.03, P=.0.06, respectively). C-reactive protein is another item that nearly significantly was higher in severe groups of cancerous patients (P=0.06)., Conclusion: The elderly age, the positive chemotherapy history, diarrhea, cough, declined WBC, PLT and elevated CRP correlated with a severe form of this infection in malignant cases.

Background: COVID-19 targets the liver and there is no available data about liver injury due to mild to moderate form of COVID-19. In this study, we evaluated the risk factors associated with liver injury in NON-ICU admitted COVID-19 patients., Methods: in this retrospective study, 102 eligible adult participants admitted in the ward were included. The patients with previous history of liver disease were excluded. The patients with AST or ALT or bilirubin more than normal ranges were allocated in liver injury group and patients with normal ranges of them were categorized in non-liver injury. Characteristics and laboratory data were analyzed between these two groups., Results: The mean age of the population was 55.13± 17.02 years old. The most common symptom was fever (45.8%). The most frequent co-morbidity was hypertension (25%). 65 patients had liver injury (63.72%). CRP were significantly higher in liver injury group (P=0.01). Univariate analysis reported ALKP, and CRP was associated significantly with liver injury (P=0.04, OR= 1.003, Cl 95%= 1.000-1.007; P=0.03, OR= 1.009, Cl 95%= 1.000- 1.017, respectively). No independent factor was detected in multivariate analysis. Based on the Spearman's rank correlation coefficients CRP correlated significantly with AST (r=0.22, P=0.00). Moreover, neutrophil and CRP, correlated with ALT (r=0.01, P=0.90; r=0.23, P=0.02, respectively)., Conclusion: No independent factor was detected to predict liver injury chance due to COVID-19. However, CRP had a significant association with it. It appears that the role of inflammatory pathways in liver damage was due to COVID-19.