Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19.

BACKGROUND: The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs). OBJECTIVE: To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19. DESIGN: Retrospective cohort. SETTING: Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN). TARGET POPULATION: Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020. MEASUREMENTS: We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs. RESULTS: Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error. LIMITATIONS: Results are limited by available documentation and do not capture communication between providers and patients. CONCLUSION: Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

Point-of-Care Ultrasound Predicts Clinical Outcomes in Patients With COVID-19.

OBJECTIVES: Point-of-care ultrasound (POCUS) detects the pulmonary manifestations of COVID-19 and may predict patient outcomes. METHODS: We conducted a prospective cohort study at four hospitals from March 2020 to January 2021 to evaluate lung POCUS and clinical outcomes of COVID-19. Inclusion criteria included adult patients hospitalized for COVID-19 who received lung POCUS with a 12-zone protocol. Each image was interpreted by two reviewers blinded to clinical outcomes. Our primary outcome was the need for intensive care unit (ICU) admission versus no ICU admission. Secondary outcomes included intubation and supplemental oxygen usage. RESULTS: N = 160 patients were included. Among critically ill patients, B-lines (94 vs 76%; P < .01) and consolidations (70 vs 46%; P < .01) were more common. For scans collected within 24 hours of admission (N = 101 patients), early B-lines (odds ratio [OR] 4.41 [95% confidence interval, CI: 1.71-14.30]; P < .01) or consolidations (OR 2.49 [95% CI: 1.35-4.86]; P < .01) were predictive of ICU admission. Early consolidations were associated with oxygen usage after discharge (OR 2.16 [95% CI: 1.01-4.70]; P = .047). Patients with a normal scan within 24 hours of admission were less likely to require ICU admission (OR 0.28 [95% CI: 0.09-0.75]; P < .01) or supplemental oxygen (OR 0.26 [95% CI: 0.11-0.61]; P < .01). Ultrasound findings did not dynamically change over a 28-day scanning window after symptom onset. CONCLUSIONS: Lung POCUS findings detected within 24 hours of admission may provide expedient risk stratification for important COVID-19 clinical outcomes, including future ICU admission or need for supplemental oxygen. Conversely, a normal scan within 24 hours of admission appears protective. POCUS findings appeared stable over a 28-day scanning window, suggesting that these findings, regardless of their timing, may have clinical implications.

Development and validation of a quantitative, non-invasive, highly sensitive and specific, electrochemical assay for anti-SARS-CoV-2 IgG antibodies in saliva.

Amperial™ is a novel assay platform that uses immobilized antigen in a conducting polymer gel followed by detection via electrochemical measurement of oxidation-reduction reaction between H2O2/Tetrametylbenzidine and peroxidase enzyme in a completed assay complex. A highly specific and sensitive assay was developed to quantify levels of IgG antibodies to SARS-CoV-2 in saliva. After establishing linearity and limit of detection we established a reference range of 5 standard deviations above the mean. There were no false positives in 667 consecutive saliva samples obtained prior to 2019. Saliva was obtained from 34 patients who had recovered from documented COVID-19 or had documented positive serologies. All of the patients with symptoms severe enough to seek medical attention had positive antibody tests and 88% overall had positive results. We obtained blinded paired saliva and plasma samples from 14 individuals. The plasma was analyzed using an EUA-FDA cleared ELISA kit and the saliva was analyzed by our Amperial™ assay. All 5 samples with negative plasma titers were negative in saliva testing. Eight of the 9 positive plasma samples were positive in saliva and 1 had borderline results. A CLIA validation was performed as a laboratory developed test in a high complexity laboratory. A quantitative non-invasive saliva based SARS-CoV-2 antibody test was developed and validated with sufficient specificity to be useful for population-based monitoring and monitoring of individuals following vaccination.