Correction: Low serum albumin and the risk of hospitalization in COVID-19 infection: A retrospective case-control study.

[This corrects the article DOI: 10.1371/journal.pone.0250906.].

Low Serum Albumin Predicts Severe Outcomes in COVID-19 Infection: A Single-Center Retrospective Case-Control Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) can cause serious complications such as multiorgan failure and death which are difficult to predict. We conducted this retrospective case-control observational study with the hypothesis that low serum albumin at presentation can predict serious outcomes in COVID-19 infection. METHODS: We included severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) confirmed, hospitalized patients from March to July 2020 in a tertiary care hospital in the USA. Patients were followed for 21 days for the development of the primary endpoint defined as the composite outcome which included acute encephalopathy, acute kidney injury, the requirement of new renal replacement therapy, acute hypercoagulability, acute circulatory failure, new-onset heart failure, acute cardiac injury, acute arrhythmia, acute respiratory distress syndrome (ARDS), high flow oxygen support, intensive care unit (ICU) stay, mechanical ventilation or death; and the secondary endpoint of death only. Univariate and multivariate logistic regression analyses were performed to study the effect of albumin level and outcomes. RESULTS: The mean age was 56.76 years vs. 55.67 years (P = 0.68) in the normal albumin vs. the low albumin group. We noticed an inverse relationship between serum albumin at presentation and serious outcomes. The low albumin group had a higher composite outcome (93.88% vs. 6.12%, P < 0.05) and higher mortality (13.87% vs. 2.38%, P < 0.05) in comparison to the normal albumin group. The multivariate logistic regression analysis revealed higher odds of having composite outcomes with lower albumin group (odds ratio (OR) 10.88, 95% confidence interval (CI) 4.74 - 24.97, P < 0.05). In the subgroup analysis, the multivariate logistic regression analysis revealed higher odds of having composite outcomes with the very low albumin group (OR 7.94, 95% CI 1.70 - 37.14, P < 0.05). CONCLUSIONS: Low serum albumin on presentation in COVID-19 infection is associated with serious outcomes not limited to mortality. The therapeutic option of albumin infusion should be investigated.

Low serum albumin and the risk of hospitalization in COVID-19 infection: A retrospective case-control study.

BACKGROUND: The data on the COVID-19 patients who were discharged to self-quarantine is lacking. AIM: The aim of the study was to investigate the percentage of COVID-19 positive patients that were hospitalized within a three-week period after discharge from ED to self-quarantine. METHODS: The patients who had confirmed SARS-CoV-2 on RT-PCR of the nasopharyngeal swab and were discharged from ED of a tertiary care hospital in the USA to self-quarantine from March 01- July 31, 2020, were included. Patients were divided into two groups based on serum albumin levels and were followed up for three weeks to see if low level of albumin increased the risk of hospitalization. Univariate and multivariate logistic regression analyses were performed to study the effect of albumin level and outcomes. RESULTS: A total of 112 patients were included in the study out of which 65 had low serum albumin (<3.5 g/dL) and 47 had normal serum albumin (≥3.5 g/dL). More than 10% of patients discharged to self-quarantine needed hospitalization within three weeks. The Low albumin group had more co-morbidities at baseline. The low serum albumin group had 10 (15.38%) vs 2 (4.26%), p = 0.06 hospitalizations as compared to the normal serum albumin group. The multivariate logistic regression analysis did not reveal lower odds of hospitalization in the group with normal albumin, (OR 0.26, 95% CI 0.03-1.92, p = 0.19) after controlling for age, sex, and various co-morbidities. CONCLUSION: The low serum albumin was not associated with the risk of hospitalization in COVID-19 patients who were initially discharged to self-quarantine.

A Retrospective Analysis of Hospital Electrocardiogram Auto-Populated QT Interval Calculation.

Background The current electrocardiogram (ECG) standard for rate correction of the QT interval (QTc) is a power function known as the Bazett formula (QTcB). QTc formulae are either power functions or linear functions. QTcB is known to lack reliability, as heart rate (HR) rises from or falls below 60 beats per minute (bpm). The American Heart Association (AHA), the American College of Cardiology Foundation (ACCF), and the Heart Rhythm Society (HRS) have recommended using other formulae in place of QTcB since 2009. The Epic Electronic Health Record System (Epic Systems Corporation, Verona, WI) automatically populates the Fridericia formula (QTcFri) on hospital ECG reports without any provider calculation. Methods We aimed to retrospectively investigate the effect of QTcFri on one year of ECGs in the Epic Electronic Health Record (EHR) at a single tertiary care center. Inclusion criteria for ECG reports specified HR 60-120 bpm without QRS duration > 120 ms. Gathered data from Epic EHR ECG reports included patient age, sex, HR, QRS duration (QRSd), QT interval, QTcB, and QTcFri. EHR documented 61,946 ECG reports for the year, with 44,566 meeting criteria for inclusion. General statistical methods included range, median, mean, and standard deviation. Confidence intervals were assessed to maintain the fidelity of analysis. The normality of data distribution was assessed with Kolmogorov-Smirnov testing. The Wilcoxon rank-sum test was then performed to confirm a statistically significant difference between the Bazett and Fridericia formulae. The ∆QTc analysis was conducted on prolonged QTc (males > 450 ms; females > 460 ms) and severely prolonged QTc > 500 ms data subsets. A value of p<0.05 was interpreted as significant. Statistical analysis was performed using SPSS statistical software (IBM Statistics, v. 26; IBM Corp, Armonk, NY). Results The 44,566 ECG reports demonstrated 57% female gender and a mean age of 57 ± 17.5 years. The mean HR was 83 ± 14.7 bpm and the mean ∆QTc was 23 ± 12.9 ms shorter with QTcFri. Mean data showed minimal variation between sexes: age, heart rate, uncorrected QT, QTcB, QTcFri, and ∆QTc varied by less than 2%. Mean QRS varied by 4% between sexes. The Wilcoxon rank-sum test revealed 44,127 ranks with a negative difference, 0 ranks with a positive difference, and 439 ties, p <0.001 (99% CI: 22.5 ms, 23.0 ms). QTcB identified 37.4% (16665/44566) ECGs prolonged. Using QTcFri, 21% (9371/44566) of the total ECGs corrected to normal QTc (<450 ms (men) and 460 ms (women)). QTcFri use reduced the number of ECG reports with QTc > 500 ms by 57.3%. A total of 125 ECG reports, 117 females and eight males, corrected to normal gender-specific QTc with QTcFri. The mean decrease in QTc with the Fridericia formula when QTcB > 500 ms was 31 ± 14.5 ms (99% CI: 30.4 ms, 31.7 ms). Conclusion Our data from the Wilcoxon rank-sum analysis indicated that the EHR QTcFri analysis yields a statistically significant difference (p < 0.001) in QTc calculation of 22 ms over 44,566 ECG reports. The data showed a 21% reduction in inaccurately documented test results. The utilization of this resource will provide the most accurate and clinically relevant data to inform clinical decision-making. Accurate QT interval calculation will better inform downstream clinical decision-making through a wider scope of therapeutic intervention. This analysis is readily available to clinicians without calculation and its awareness will benefit patient care.

Cannabinoid-Induced Brugada Syndrome: A Case Report.

Brugada syndrome, also called Pokkuri Death Syndrome, is an autosomal dominant electrophysiological phenomenon that increases the risk of spontaneous ventricular tachyarrhythmia and sudden cardiac death. Due to sodium channel mutations in the cardiac membrane, most commonly SCN5A and SCN10A, the heart can be triggered into a fatal arrhythmia. Brugada syndrome can be triggered by fever, and medications including antiarrhythmics, psychotropics, and recreational drugs like cocaine and marijuana. We report a case that demonstrates the diagnosis of Brugada syndrome in an otherwise very healthy 22-year-old African-American male. He presented after a syncopal event and developed spontaneous ventricular tachycardia and torsades de pointes. Electrocardiogram (EKG) findings documented a type I Brugada pattern and, once stabilized, the patient underwent an internal cardioverter defibrillator (ICD) placement.