Pilot analysis of intravenous lipid infusion role in COVID-19 mortality.

INTRODUCTION: How to reduce the fatality of coronavirus disease (COVID-19) is still challenging. A proper nutritional support has been always a matter of attention in critically ill patients. MATERIAL AND METHODS: We assessed COVID-19 patients who had received intralipid infusion due to medical indications and compared them with those who did not receive it regarding fatality rate and prognosis. As a part of a data mining project using data of observational cohort of COVID-19 patients hospitalized in the educational centers of Iran University of Medical Sciences, Tehran, Iran, an inferential case series was performed. A total of 19 patients with SARS-CoV-2 infection were selected from the cohort. Briefly, 13 patients survived and 6 patients died, and 12 patients were admitted in intensive care unit (ICU). All dead cases were ICU admitted. The association of intralipid infusion and survival rate was examined using Fisher exact test. No association was observed between intralipid infusion and survival. CONCLUSIONS: No significant protecting effect was observed for patients who received intralipid for medical indications. Since intralipid was administered according to medical indications, surviving of all the non-ICU admitted patients despite having underlying diseases was remarkable. Despite the fact, due to several bias factors that could not be controlled in such a retrospective study, the results might be accidental. We suggest to assess such an effect retrospectively in other centers as well.

A near real-time electronic health record-based COVID-19 surveillance system: An experience from a developing country.

CONTEXT: Access to real-time data that provide accurate and timely information about the status and extent of disease spread could assist management of the COVID-19 pandemic and inform decision-making. AIM: To demonstrate our experience with regard to implementation of technical and architectural infrastructure for a near real-time electronic health record-based surveillance system for COVID-19 in Iran. METHOD: This COVID-19 surveillance system was developed from hospital information and electronic health record (EHR) systems available in the study hospitals in conjunction with a set of open-source solutions; and designed to integrate data from multiple resources to provide near real-time access to COVID-19 patients' data, as well as a pool of health data for analytical and decision-making purposes. OUTCOMES: Using this surveillance system, we were able to monitor confirmed and suspected cases of COVID-19 in our population and to automatically notify stakeholders. Based on aggregated data collected, this surveillance system was able to facilitate many activities, such as resource allocation for hospitals, including managing bed allocations, providing and distributing equipment and funding, and setting up isolation centres. CONCLUSION: Electronic health record systems and an integrated data analytics infrastructure are effective tools to enable policymakers to make better decisions, and for epidemiologists to conduct improved analyses regarding COVID-19. IMPLICATIONS: Improved quality of clinical coding for better case finding, improved quality of health information in data sources, data-sharing agreements, and increased EHR coverage in the population can empower EHR-based COVID-19 surveillance systems.

An Easy-to-Use Platform for Reporting COVID-19 Patients by Private Offices and Clinics Without IT Support: A Pilot Study.

BACKGROUND: It is feasible to collect data rapidly and online using IT solutions. OBJECTIVES: To present a data collection platform for COVID-19 suspected patients in private offices and clinics without a standard software. METHODS: The proposed system for collecting and sharing data of patients with respiratory symptoms was designed to be simple to use, without the need for special technology, and with proper security to authenticate reporters. RESULTS: Two methods were developed to collect data from private physicians and offices. Finally, the data collected by both approaches is integrated and provided to primary healthcare staff to arrange appropriate healthcare measures. CONCLUSION: Our platform can provide an easy-to-use case reporting system for private physicians.

Effects of Immune System-Related Medications on COVID-19 Outcome in a Cohort of Iranian Patients: Preliminary Report of a Data Mining Study.

BACKGROUND: Regulation of the immune system is critical for fighting against viral infections. Both suppression and hyperactivity of the immune system result in failure of treatment. The present study was designed to show the effects of immune system-related medications on mortality and length of stay (LOS) in a cohort of Iranian patients with coronavirus disease 2019 (COVID-19). METHODS: A data mining study was performed on 6417 cases of COVID-19 covered by 17 educational hospitals of Iran University of Medical Sciences, Tehran. Association of a researcher-designed drug list with death and LOS was studied. For death outcome, logistic regression was used reporting odds ratio (OR) with 95% confidence interval (CI). For LOS, right censored Poisson regression was used reporting incidence rate ratio (IRR) with 95% CI. RESULTS: Among the corticosteroids, prednisolone was a risk factor on death (OR = 1.41, 95%CI = 1.03 - 1.94). This association was increased after adjustment of age interactions (OR = 3.45, 95%CI = 1.01 - 11.81) and was removed after adjustment of ICU admission interactions (OR = 2.64, 95%CI = 0.70 - 9.92). Hydroxychloroquine showed a protecting effect on death (OR = 0.735, 95%CI = 0.627 - 0.862); however, this association was removed after adjustment of age interactions (OR = 0.76, 95%CI = 0.41 - 1.40). Among the antivirals, oseltamivir showed a protecting effect on death (OR = 0.628, 95%CI = 0.451 - 0.873); however, this association was removed after adjustment of age interactions (OR = 0.45, 95%CI = 0.11 - 1.82). For reduction of LOS, the only significant association was for hydroxychloroquine (IRR = 0.85, 95%CI = 0.79 - 0.92). CONCLUSION: The results of such data mining studies can be used in clinics until completing the evidence. Hydroxychloroquine may reduce mortality in some specific groups; however, its association may be confounded by some latent variables and unknown interactions. Administration of corticosteroids should be based on the conditions of each case.