Correction: Serial measurement of cytokines strongly predict COVID-19 outcome.

[This corrects the article DOI: 10.1371/journal.pone.0260623.].

Visiting and Communication Policy in Intensive Care Units during COVID-19 Pandemic: A Cross-sectional Survey from South Asia and the Middle East.

Purpose: The coronavirus disease-2019 (COVID-19) pandemic had affected the visiting or communicating policies for family members. We surveyed the intensive care units (ICUs) in South Asia and the Middle East to assess the impact of the COVID-19 pandemic on visiting and communication policies. Materials and method: A web-based cross-sectional survey was used to collect data between March 22, 2021, and April 7, 2021, from healthcare professionals (HCP) working in COVID and non-COVID ICUs (one response per ICU). The topics of the questionnaire included current and pre-pandemic policies on visiting, communication, informed consent, and end-of-life care in ICUs. Results: A total of 292 ICUs (73% of COVID ICUs) from 18 countries were included in the final analysis. Most (92%) of ICUs restricted their visiting hours, and nearly one-third (32.3%) followed a "no-visitor" policy. There was a significant change in the daily visiting duration in COVID ICUs compared to the pre-pandemic times (p = 0.011). There was also a significant change (p <0.001) in the process of informed consent and end-of-life discussions during the ongoing pandemic compared to pre-pandemic times. Conclusion: Visiting and communication policies of the ICUs had significantly changed during the COVID-19 pandemic. Future studies are needed to understand the sociopsychological and medicolegal implications of revised policies. How to cite this article: Chanchalani G, Arora N, Nasa P, Sodhi K, Al Bahrani MJ, Al Tayar A, et al. Visiting and Communication Policy in Intensive Care Units during COVID-19 Pandemic: A Cross-sectional Survey from South Asia and the Middle East. Indian J Crit Care Med 2022;26(3):268-275.

Serial measurement of cytokines strongly predict COVID-19 outcome.

PURPOSE: Cytokines are major mediators of COVID-19 pathogenesis and several of them are already being regarded as predictive markers for the clinical course and outcome of COVID-19 cases. A major pitfall of many COVID-19 cytokine studies is the lack of a benchmark sampling timing. Since cytokines and their relative change during an infectious disease course is quite dynamic, we evaluated the predictive value of serially measured cytokines for COVID-19 cases. METHODS: In this single-center, prospective study, a broad spectrum of cytokines were determined by multiplex ELISA assay in samples collected at admission and at the third day of hospitalization. Appropriateness of cytokine levels in predicting mortality were assessed by receiver-operating characteristic (ROC) analyses for both sampling times in paralel to conventional biomarkers. RESULTS: At both sampling points, higher levels of IL-6, IL-7, IL-10, IL-15, IL-27 IP-10, MCP-1, and GCSF were found to be more predictive for mortality (p<0.05). Some of these cytokines, such as IL-6, IL-10, IL-7 and GCSF, had higher sensitivity and specificity in predicting mortality. AUC values of IL-6, IL-10, IL-7 and GCSF were 0.85 (0.65 to 0.92), 0.88 (0.73 to 0.96), 0.80 (0.63 to 0.91) and 0.86 (0.70 to 0.95), respectively at hospital admission. Compared to hospital admission, on the 3rd day of hospitalization serum levels of IL-6 and, IL-10 decreased significantly in the survivor group, unlike the non-survivor group (IL-6, p = 0.015, and IL-10, p = 0.016). CONCLUSION: Our study results suggest that single-sample-based cytokine analyzes can be misleading and that cytokine levels measured serially at different sampling times provide a more precise and accurate estimate for the outcome of COVID-19 patients.

Clinical Outcomes and Independent Risk Factors for 90-Day Mortality in Critically Ill Patients with Respiratory Failure Infected with SARS-CoV-2: A Multicenter Study in Turkish Intensive Care Units.

BACKGROUND: There are limited data on the long-term outcomes of COVID-19 from different parts of the world. AIMS: To determine risk factors of 90-day mortality in critically ill patients in Turkish intensive care units (ICUs), with respiratory failure. STUDY DESIGN: Retrospective, observational cohort. METHODS: Patients with laboratory-confirmed COVID-19 and who had been followed up in the ICUs with respiratory failure for more than 24 hours were included in the study. Their demographics, clinical characteristics, laboratory variables, treatment protocols, and survival data were recorded. RESULTS: A total of 421 patients were included. The median age was 67 (IQR: 57-76) years, and 251 patients (59.6%) were men. The 90-day mortality rate was 55.1%. The factors independently associated with 90-day mortality were invasive mechanical ventilation (IMV) (HR 4.09 [95% CI: [2.20-7.63], P < .001), lactate level >2 mmol/L (2.78 [1.93-4.01], P < .001), age ≥60 years (2.45 [1.48-4.06)], P < .001), cardiac arrhythmia during ICU stay (2.01 [1.27-3.20], P = .003), vasopressor treatment (1.94 [1.32-2.84], P = .001), positive fluid balance of ≥600 mL/day (1.68 [1.21-2.34], P = .002), PaO2/FiO2 ratio of ≤150 mmHg (1.66 [1.18-2.32], P = .003), and ECOG score ≥1 (1.42 [1.00-2.02], P = .050). CONCLUSION: Long-term mortality was high in critically ill patients with COVID-19 hospitalized in intensive care units in Turkey. Invasive mechanical ventilation, lactate level, age, cardiac arrhythmia, vasopressor therapy, positive fluid balance, severe hypoxemia and ECOG score were the independent risk factors for 90-day mortality.

The factors predicting pneumonia in COVID-19 patients: preliminary results from a university hospital in Turkey

Background/aim: Pneumonia is the most serious clinical presentation of COVID-19. This study aimed to determine the demographic, clinical, and laboratory findings that can properly predict COVID-19 pneumonia. Materials and methods: This study was conducted in the Gazi University hospital. All hospitalized patients with confirmed and suspected SARS-CoV-2 infection between 16 March 2020 and 30 April 2020 were analyzed retrospectively. COVID-19 patients were separated into two groups, pneumonia and nonpneumonia, and then compared to determine predicting factors for COVID-19 pneumonia. Variables that had a P-value of less than 0.20 and were not correlated with each other were included in the logistic regression model. Results: Of the 247 patients included in the study 58% were female, and the median age was 40. COVID-19 was confirmed in 70.9% of these patients. Among the confirmed COVID-19 cases, 21.4% had pneumonia. In the multivariate analysis male sex (P = 0.028), hypertension (P = 0.022), and shortness of breath on hospital admission (P = 0.025) were significant factors predicting COVID-19 pneumonia. Conclusion: Shortness of breath, male sex, and hypertension were significant for predicting COVID-19 pneumonia on admission. Patients with these factors should be evaluated more carefully for diagnostic procedures, such as thorax CT.