Combination of spironolactone and sitagliptin improves clinical outcomes of outpatients with COVID-19: a prospective cohort study.

BACKGROUND: There are evidences showing that sitagliptin and spironolactone can potentially improve the clinical outcomes of COVID-19 cases. In this observational study on acutely symptomatic outpatient COVID-19 cases, we investigated the effects of spironolactone and sitagliptin on the outcomes of the disease. METHODS: This is a prospective, naturally randomized cohort study. We followed mild to moderate symptomatic COVID-19 patients, who were treated with either combination (spironolactone 100 mg daily and sitagliptin 100 mg daily) or standard (steroid, antiviral and/or supportive care) therapy up to 30 days. The primary outcome was hospitalization rate. The secondary outcomes included ER visit, duration of disease, and complications, such as hypoglycemia, low blood pressure or altered mental status. RESULTS: Of the 206 patients referred to clinics randomly, 103 received standard therapy and 103 treated with combination therapy. There were no significant differences in baseline characteristics, except for slightly higher clinical score in control group (6.92 ± 4.01 control, 4.87 ± 2.92 combination; P < 0.0001). Treatment with combination therapy was associated with lower admission rate (5.8% combination, 22.3% control; P = 0.0011), ER visits (7.8% combination, 23.3% control; P = 0.0021) and average duration of symptoms (6.67 ± 2.30 days combination, 18.71 ± 6.49 days control; P ≤ 0.0001). CONCLUSIONS: The combination of sitagliptin and spironolactone reduced duration of COVID infection and hospital visits better than standard therapeutic approaches in outpatients with COVID-19. The effects of combination of sitagliptin and spironolactone in COVID-19 patients should be further verified in a double-blind, randomized, placebo-controlled trial.

The Fauna and Active Season of Mosquitoes in West of Fars Province, Southwest of Iran.

Culicidae are highly important for public health as they can be vectors of diseases and are responsible for a wide spectrum of infections. Five collection sites were selected randomly with regards to existing facilities in Firouzabad County. For collecting larvae and total catch for adult mosquitoes, sampling was carried out by dipping technique for collecting larvae and total catch for adult mosquitoes. A total of 689 adults and 1313 larvae of Culicidae were collected, of which 3 genera and 6 species of Culicidae were recognized, namely, Anopheles superpictus, Anopheles d&rsquo;thali, Culex sinaiticus, Culex theileri, Culex mimeticus, and Culiseta longiareolata. Cx. theileri was the most frequent Culicidae collected at Firouzabad, with a total of 613 and 247 larval and adult specimens, respectively. The highest number of mosquitoes was collected in June (31.1%) and the lowest in May (3.4%). The mean temperatures in June and May were 31.3˚C and 28.2˚C, respectively. We found some vectors that are of medical and veterinary importance; our results could be applied in vector control programs that aim at eradication or control of mosquitoes in this area.

Prevention of Disease Complications through Diagnostic Models: How to Tackle the Problem of Missing Data?

BACKGROUND: Diagnostic models are frequently used to assess the role of risk factors on disease complications, and therefore to avoid them. Missing data is an issue that challenges the model making. The aim of this study was to develop a diagnostic model to predict death in HIV/AIDS patients when missing data exist. METHODS: HIV patients (n=1460) referred to Voluntary Consoling and Testing Center (VCT) of Shiraz southern Iran during 2004-2009 were recruited. Univariate association between variables and death was assessed. Only variables which had univariate P< 0.25 were selected to be offered to the Multifactorial models. First, patients with missing data on candidate variables were deleted (C-C model). Then, applying Multivariable Imputation via Chained Equations (MICE), missing data were imputed. Logistic regression was fitted to C-C and imputed data sets (MICE model). Models were compared in terms of number of variables retained in the final model, width of confidence intervals, and discrimination ability. RESULT: About 22% of data were lost in C-C model. Number of variables retained in the C-C and MICE models was 2 and 6 respectively. Confidence Intervals (C.I.) corresponding to C-C model was wider than that of MICE. The MICE model showed greater discrimination ability than C-C model (70% versus 64%). CONCLUSION: The C-C analysis resulted to loss of power and wide CI's. Once missing data were imputed, more variables reached significance level and C.I.'s were narrower. Therefore, we do recommend the application of the imputation method for handling missing data.

An outbreak of food-borne group A Streptococcus (GAS) tonsillopharyngitis among residents of a dormitory.

Epidemics of food-borne pharyngitis due to group A Streptococcus are rarely reported. Here we present an outbreak of food-borne tonsillopharyngitis in female dormitories in the Islamic Republic of Iran. Throat swabs and cultures were performed on a number of patients, and of specimens from the nasopharynx and hands of staff who were involved in food processing. We planned a case-control study for assessing the source of epidemics. 11 out of 17 throat swabs of students were positive for Streptococcus group A and also 2 throat samples from asymptomatic cooks were positive. A DNA fingerprinting study showed that Streptococcus group A strains of 11 students and 1 cook had the same T agglutination pattern and M protein factor (M3/T13). It is suggested that group A streptococci as well as group C and G streptococci can cause epidemic food-borne pharyngitis. Regular health surveillance of food handlers and food preparation processes are important for prevention of such outbreaks.