In:
Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 100, No. 30 ( 2021-07-30), p. e26720-
Abstract:
Isolation of confirmed or suspected coronavirus disease 2019 (COVID-19) cases is essential but, as symptoms of COVID-19 are non-specific and test results not immediately available, case identification at admission remains challenging. To inform optimization of triage algorithms, patient flow and patient care, we analyzed characteristics of patients admitted to an isolation ward, both severe acute respiratory syndrome coronavirus 2019 (SARS-CoV-2) positive patients and patients in which initial suspicion was not confirmed after appropriate testing. Data from patients with confirmed or suspected COVID-19 treated in an isolation unit were analyzed retrospectively. Symptoms, comorbidities and clinical findings were analyzed descriptively and associations between patient characteristics and final SARS-CoV-2 status were assessed using univariate regression. Eighty three patients (49 SARS-CoV-2 negative and 34 positive) were included in the final analysis. Of initially suspected COVID-19 cases, 59% proved to be SARS-CoV-2-negative. These patients had more comorbidities (Charlson Comorbidity Index median 5(interquartile range [IQR] 2.5, 7) vs 2.7(IQR 1, 4)), and higher proportion of active malignancy than patients with confirmed COVID-19 (47% vs 15%; P = .004), while immunosuppression was frequent in both patient groups (20% vs 21%; P = .984). Of SARS-CoV-2 negative patients, 31% were diagnosed with non-infectious diseases. A high proportion of patients (59%) triaged to the isolation unit were tested negative for SARS-CoV-2. Of these, many suffered from active malignancy (47%) and were immunosuppressed (20%). Non-infectious diseases were diagnosed in 31%, highlighting the need for appropriate patient flow, timely expert medical care including evaluation for differential diagnostics while providing isolation and ruling out of COVID-19 in these patients with complex underlying diseases.
Type of Medium:
Online Resource
ISSN:
0025-7974
,
1536-5964
DOI:
10.1097/MD.0000000000026720
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2021
detail.hit.zdb_id:
2049818-4
