Diagnostic accuracy of non-contact infrared thermometers and thermal scanners: a systematic review and meta-analysis.

Infrared thermal screening, via the use of handheld non-contact infrared thermometers (NCITs) and thermal scanners, has been widely implemented all over the world. We performed a systematic review and meta-analysis to investigate its diagnostic accuracy for the detection of fever. We searched PubMed, Embase, the Cochrane Library, medRxiv, bioRxiv, ClinicalTrials.gov, COVID-19 Open Research Dataset, COVID-19 research database, Epistemonikos, EPPI-Centre, World Health Organization International Clinical Trials Registry Platform, Scopus and Web of Science databases for studies where a non-contact infrared device was used to detect fever against a reference standard of conventional thermometers. Forest plots and Hierarchical Summary Receiver Operating Characteristics curves were used to describe the pooled summary estimates of sensitivity, specificity and diagnostic odds ratio. From a total of 1063 results, 30 studies were included in the qualitative synthesis, of which 19 were included in the meta-analysis. The pooled sensitivity and specificity were 0.808 (95%CI 0.656-0.903) and 0.920 (95%CI 0.769-0.975), respectively, for the NCITs (using forehead as the site of measurement), and 0.818 (95%CI 0.758-0.866) and 0.923 (95%CI 0.823-0.969), respectively, for thermal scanners. The sensitivity of NCITs increased on use of rectal temperature as the reference. The sensitivity of thermal scanners decreased in a disease outbreak/pandemic setting. Changes approaching statistical significance were also observed on the exclusion of neonates from the analysis. Thermal screening had a low positive predictive value, especially at the initial stage of an outbreak, whereas the negative predictive value (NPV) continued to be high even at later stages. Thermal screening has reasonable diagnostic accuracy in the detection of fever, although it may vary with changes in subject characteristics, setting, index test and the reference standard used. Thermal screening has a good NPV even during a pandemic. The policymakers must take into consideration the factors surrounding the screening strategy while forming ad-hoc guidelines.

Temperature Screening for SARS-CoV-2 in Nursing Homes: Evidence from Two National Cohorts.

BACKGROUND/OBJECTIVES: Infection screening tools classically define fever as 38.0°C (100.4°F). Frail older adults may not mount the same febrile response to systemic infection as younger or healthier individuals. We evaluate temperature trends among nursing home (NH) residents undergoing diagnostic SARS-CoV-2 testing and describe the diagnostic accuracy of temperature measurements for predicting test-confirmed SARS-CoV-2 infection. DESIGN: Retrospective cohort study evaluating diagnostic accuracy of pre-SARS-CoV-2 testing temperature changes. SETTING: Two separate NH cohorts tested diagnostically (e.g., for symptoms) for SARS-CoV-2. PARTICIPANTS Veterans residing in Veterans Affairs (VA) managed NHs and residents in a private national chain of community NHs. MEASUREMENTS: For both cohorts, we determined the sensitivity, specificity, and Youden's index with different temperature cutoffs for SARS-CoV-2 polymerase chain reaction results. RESULTS: The VA cohort consisted of 1,301 residents in 134 facilities from March 1, 2020, to May 14, 2020, with 25% confirmed for SARS-CoV-2. The community cohort included 3,368 residents spread across 282 facilities from February 18, 2020, to June 9, 2020, and 42% were confirmed for SARS-CoV-2. The VA cohort was younger, less White, and mostly male. A temperature testing threshold of 37.2°C has better sensitivity for SARS-CoV-2, 76% and 34% in the VA and community NH, respectively, versus 38.0°C with 43% and 12% sensitivity, respectively. CONCLUSION: A definition of 38.0°C for fever in NH screening tools should be lowered to improve predictive accuracy for SARS-CoV-2 infection. Stakeholders should carefully consider the impact of adopting lower testing thresholds on testing availability, cost, and burden on staff and residents. Temperatures alone have relatively low sensitivity/specificity, and we advocate any threshold be used as part of a screening tool, along with other signs and symptoms of infection.

QT Interval Prolongation Under Hydroxychloroquine/Azithromycin Association for Inpatients With SARS-CoV-2 Lower Respiratory Tract Infection.

Association between Hydroxychloroquine (HCQ) and Azithromycin (AZT) is under evaluation for patients with lower respiratory tract infection (LRTI) caused by the Severe Acute Respiratory Syndrome (SARS-CoV-2). Both drugs have a known torsadogenic potential, but sparse data are available concerning QT prolongation induced by this association. Our objective was to assess for COVID-19 LRTI variations of QT interval under HCQ/AZT in patients hospitalized, and to compare manual versus automated QT measurements. Before therapy initiation, a baseline 12 lead-ECG was electronically sent to our cardiology department for automated and manual QT analysis (Bazett and Fridericia's correction), repeated 2 days after initiation. According to our institutional protocol (Pasteur University Hospital), HCQ/AZT was initiated only if baseline QTc ≤ 480ms and potassium level> 4.0 mmol/L. From March 24th to April 20th 2020, 73 patients were included (mean age 62 ± 14 years, male 67%). Two patients out of 73 (2.7%) were not eligible for drug initiation (QTc ≥ 500 ms). Baseline average automated QTc was 415 ± 29 ms and lengthened to 438 ± 40 ms after 48 hours of combined therapy. The treatment had to be stopped because of significant QTc prolongation in two out of 71 patients (2.8%). No drug-induced life-threatening arrhythmia, nor death was observed. Automated QTc measurements revealed accurate in comparison with manual QTc measurements. In this specific population of inpatients with COVID-19 LRTI, HCQ/AZT could not be initiated or had to be interrupted in less than 6% of the cases.