Background: Telephones, internet-connected devices (phablets, personal computers), chat platforms, and mobile apps (eg, Skype, Facebook Messenger, WhatsApp) can be exploited for telemedicine applications. WhatsApp and similar apps are also widely used to facilitate clinical communication between physicians. Moreover, WhatsApp is used by emergency department (ED) physicians and consulting physicians to exchange medical information during ED consultations. This platform is regarded as a useful app in the consultation of dermatological and orthopedic cases. Preventing overcrowding in the ED is key to reducing the risk of disease transmission, and teleconsulting practice is thought to be effective in the diagnosis, treatment, and reduction of transmission risk of disease, most notably during the COVID-19 pandemic. Video consultation is highly recommended in some countries on the grounds that it is likely to reduce the risk of transmission. WhatsApp-like apps are among the video consultation platforms that are assumed to reduce the risk of contamination by minimizing patient-physician contact. Objective: The aim of this study was to investigate the effects of WhatsApp video consultation on patient admission and discharge times in comparison to bedside consultation in the evaluation of potential patients with COVID-19 visiting a COVID-19 outpatient clinic during the pandemic. Methods: Patients who presented to the ED COVID-19 outpatient clinic between March 11 and May 31, 2020, and for whom an infectious disease specialist was consulted (via WhatsApp or at bedside) were included in the study in accordance with the inclusion and exclusion criteria. Eventually, 54 patients whose consultations were performed via WhatsApp and 90 patients whose consultations were performed at bedside were included in our study. Results: The median length of stay in the ED of discharged patients amounted to 103 minutes (IQR 85-147.75) in the WhatsApp group and 196 minutes (IQR 141-215) in the bedside group. In this regard, the length of stay in the ED was found to be significantly shorter in the WhatsApp group than in the bedside group (P<.001). Among the consulted and discharged patients, 1 patient in each group tested positive for SARS-CoV-2 by polymerase chain reaction test and thus was readmitted and hospitalized (P=.62). The median length of stay of the inpatients in the ED was found to be 116.5 minutes (IQR 85.5-145.5) in the WhatsApp group and 132 minutes (IQR 102-168) in the bedside group. The statistical analysis of this time difference revealed that the length of stay in the ED was significantly shorter for patients in the WhatsApp group than in the bedside group (P=.04). Conclusions: Consultation via WhatsApp reduces both contact time with patients with COVID-19 and the number of medical staff contacting the patients, which contributes greatly to reducing the risk of COVID-19 transmission. WhatsApp consultation may prove useful in clinical decision making as well as in shortening process times. Moreover, it does not result in a decreased accuracy rate. The shortened discharge and hospitalization timespans also decreased the length of stay in the ED, which can have an impact on minimizing ED crowding. Trial Registration: ClinicalTrials.gov NCT04645563; https://clinicaltrials.gov/ct2/show/NCT04645563.

Recent studies have investigated the importance of Galetin-3 in inflammation, fibrosis, cell proliferation, cardiac disease, diabetes, and tumor formation. This study aims to investigate the role of the Galectin-3 level in the diagnosis of COVID-19 pneumonia and the value of the Galectin-3 level in predicting the clinical course of the patient. This study employed a prospective, case-control study design and was conducted at Bakircay University Ciğli Training and Research Hospital. A total of 100 patients (40 had moderate and 60 had severe/critical COVID-19 disease according to World Health Organisation guidelines) and 50 non-symptomatic healthy volunteers participated in the study. Blood samples were taken from patients at the time of hospital admission, after which serum was isolated. Following the isolation of serum, Galectin-3 levels were evaluated using the enzyme-linked immunosorbent assay (ELISA) method. The serum Galectin-3 level was measured as 13.57 (10.9-16.4) ng/mL in the control group, 13.52 (10.69-16.6) ng/mL in the moderate disease group, and 11.65 (6.09-14.33) ng/mL in the severe/critical disease group. Serum Galectin-3 levels were significantly lower in the severe/critical disease group compared to the control and moderate disease groups (p=0.001 and p=0.019, respectively). Using ROC analysis, a larger area under the curve (AUC) for the serum Galectin-3 levels of the control group (AUC=0.622, 95% CI =0.529-0.714; p=0.015) was calculated compared to the COVID-19 patient group for the diagnosis of COVID-19 disease. The Galectin-3 level was found to be 75% sensitive and 50% specific at a cut-off level of 11.3 ng/mL in predicting the need for ICU treatment. Galectin-3 levels may be a beneficial biomarker in predicting the clinical severity of COVID-19 disease when used in conjunction with other known biomarkers, at the time of admission to the emergency department (ED).

The objective of this study was to evaluate the usefulness of the serum biomarkers myeloperoxidase (MPO), paraoxonase (PON), and plasma asprosin in acute myocardial infarction (AMI) diagnosis and assess their compatibility with routinely screened cardiac biomarkers. This study was conducted using a prospective cross-sectional design and included 90 patients, consisting of 60 patients diagnosed with AMI (30 with ST-segment elevation and 30 with non-ST-segment elevation on ECG) and 30 controls (without a diagnosis of AMI). Changes in the levels of cardiac biomarkers (Hs-cTnI, CK, CK-MB), lipid profile (TC, TG, LDL, HDL), MPO, PON, asprosin, and routine biochemical parameters of patients were evaluated. Furthermore, receiver operating characteristic curve analysis revealed the diagnostic value of Hs-cTnI, MPO, PON, and asprosin in predicting AMI. Binary logistic regression analysis of cardiac marker concentrations was used to predict the presence of AMI. In contrast, multinomial logistic regression analysis was conducted to predict the type of AMI and the control group. The median levels of MPO and plasma asprosin were found to be higher in the patient group (3.22 [interquartile range {IQR}: 2.4–4.4] ng/ml and 10.84 [IQR: 8.8–17.8] ng/ml, respectively) than in the control group (2.49 [IQR: 1.9–2.9] ng/ml and 4.82 [IQR: 4.6–8.0] ng/ml, respectively) (p = 0.001 and p < 0.001, respectively). The median levels of PON were 8.94 (IQR: 7.6–10.4) ng/ml in the patient group and 10.44 (IQR: 9.1–20.0) ng/ml in the control group (p < 0.001). In the binary logistic regression model, compared with the control group, a 1 ng/ml increase in MPO level increased the odds of having AMI by 3.61 (p = 0.041, 95% CI: 1.055–12.397), whereas a 1 ng/ml increase in asprosin level increased the odds of having AMI by 2.33 (p < 0.001, 95% CI: 1.479–3.683). In the multinominal logistic regression model, compared with the control group, a 1 ng/ml increase in the MPO level increased the odds of having NSTEMI by 4.14 (p = 0.025, 95% CI: 1.195–14.350), whereas a 1 ng/ml increase in asprosin concentrations increased the odds of having NSTEMI by 2.35 (p < 0.001, 95% CI: 1.494–3.721). Herein, MPO and asprosin concentrations increased with Hs-cTnI, and a decrease in PON concentration indicated that oxidant–antioxidant parameters and adipokines were related to AMI pathogenesis.

Background: High altitude, known for its effects on respiratory diseases, was analyzed for its potential protective role. Data from the New York Times COVID-19 repository, U.S. Census Bureau, and topographic maps were utilized, covering January 2020 to August 2022, including pre- and post-vaccination periods. This study investigates the influence of high altitude on COVID-19 mortality, fatality rates, and vaccination outcomes in the United States. COVID-19, caused by SARS-CoV-2, has shown significant disparities in severity and outcomes across populations. Methods: This study utilized publicly available data from the New York Times COVID-19 repository and the US Census Bureau’s American Community Survey to analyze case fatality rates across mainland US counties from January 21, 2020, to August 13, 2022. Average altitude data were obtained from topographic maps, and counties outside the mainland USA were excluded. Vaccination-related data were assessed using the cutoff date of December 14, 2020. The rural-urban status of counties was determined using the Index of Relative Rurality (IRR) from Waldorf and Kim’s study, which included 3105 of 3109 counties. Results: Counties above 1500 m exhibited significantly lower case numbers, deaths, cases per million, and fatality rates compared to counties below this altitude. Pre-vaccination fatality rates were notably reduced in high-altitude regions (p = 0.0001), while post-vaccination data continued to demonstrate lower fatality rates (p < 0.0001). A positive correlation between rurality and post-vaccination fatality rates was observed (rho = 0.176, p = 0.0001). Altitude, alongside vaccination status, was identified as a critical factor influencing fatality rates (p = 0.001 for both). Additionally, a significant positive correlation between rurality (Index of Relative Rurality) and post-vaccination fatality rates was observed (rho = 0.176, p = 0.0001). Conclusions: Our findings highlight that high-altitude adaptations, such as increased lung capacity and epigenetic changes, may mitigate COVID-19 severity. However, the role of environmental and genetic factors remains insufficiently explored. Importantly, the study underscores healthcare inequities in rural high-altitude areas, where limited vaccination access exacerbates mortality risks. While altitude shows promise as a protective factor, addressing healthcare access disparities and further investigating high-altitude physiological and genetic adaptations are imperative for optimizing COVID-19 outcomes in diverse populations.

This study investigated the association between serum hypoxia-inducible factor 1-alpha (HIF-1α) levels and clinical severity in patients with coronavirus disease 2019 (COVID-19). This prospective case–control study included 91 patients with confirmed COVID-19, of whom 51 had severe-critical disease with pneumonia and 40 had mild disease without pneumonia, as well as 39 healthy controls. Vital signs, including body temperature, pulse rate, respiratory rate, oxygen saturation, and blood pressure, were recorded. Biochemical parameters such as complete blood count, D-dimer, ferritin, creatinine, urea, and high-sensitivity cardiac troponin T were analyzed. Serum HIF-1α levels were measured using ELISA. Median HIF-1α levels were 132.9 pg/mL (IQR: 131.7–138.0) in the severe-critical disease group, 137.35 pg/mL (IQR: 131.65–152.75) in the mild disease group, and 136.6 pg/mL (IQR: 132.2–162.2) in controls. Significant differences were observed between groups (p = 0.012). ROC analysis showed a discriminatory performance for HIF-1α, with a sensitivity of 89.01% and specificity of 35.90% at a cut-off value of ≤154 pg/mL for distinguishing mild disease from controls, and a sensitivity of 86.3% and specificity of 42.5% at a cut-off value of ≤141.1 pg/mL for distinguishing severe-critical disease from mild disease. HIF-1α levels decreased with increasing disease severity. HIF-1α levels were found to be associated with disease severity; however, the low AUC values indicate that this parameter has limited discriminative ability for clinical use when used alone.