ABSTRACT
INTRODUCTION: The variety, time patterns and long-term prognosis of persistent COVID-19 symptoms (long COVID-19) in patients who suffered from mild to severe acute COVID-19 are incompletely understood. Cohort studies will be combined to describe the prevalence of long COVID-19 symptoms, and to explore the pathophysiological mechanisms and impact on health-related quality of life. A prediction model for long COVID-19 will be developed and internally validated to guide care in future patients. METHODS AND ANALYSIS: Data from seven COVID-19 cohorts will be aggregated in the longitudinal multiple cohort CORona Follow Up (CORFU) study. CORFU includes Dutch patients who suffered from COVID-19 at home, were hospitalised without or with intensive care unit treatment, needed inpatient or outpatient rehabilitation and controls who did not suffer from COVID-19. Individual cohort study designs were aligned and follow-up has been synchronised. Cohort participants will be followed up for a maximum of 24 months after acute infection. Next to the clinical characteristics measured in individual cohorts, the CORFU questionnaire on long COVID-19 outcomes and determinants will be administered digitally at 3, 6, 12, 18 and 24 months after the infection. The primary outcome is the prevalence of long COVID-19 symptoms up to 2 years after acute infection. Secondary outcomes are health-related quality of life (eg, EQ-5D), physical functioning, and the prevalence of thromboembolic complications, respiratory complications, cardiovascular diseases and endothelial dysfunction. A prediction model and a patient platform prototype will be developed. ETHICS AND DISSEMINATION: Approval was obtained from the medical research ethics committee of Maastricht University Medical Center+ and Maastricht University (METC 2021-2990) and local committees of the participating cohorts. The project is supported by ZonMW and EuroQol Research Foundation. Results will be published in open access peer-reviewed scientific journals and presented at (inter)national conferences. TRIAL REGISTRATION NUMBER: NCT05240742.
Subject(s)
COVID-19 , Humans , Cohort Studies , COVID-19/epidemiology , Follow-Up Studies , Prevalence , Quality of Life , Post-Acute COVID-19 SyndromeABSTRACT
COVID-19 restrictions have resulted in major changes in healthcare, including the prescribing of antibiotics. We aimed to monitor antibiotic prescribing trends during the COVID-19 pandemic in Dutch general practice, both during daytime and out-of-hours (OOH). Routine care data were used from 379 daytime general practices (DGP) and 28 OOH-services over the period 2019-2021. Per week, we analyzed prescription rates per 100,000 inhabitants, overall, for respiratory and urinary tract infections (RTIs and UTIs) specifically and within age categories. We assessed changes in antibiotic prescribing during different phases of the pandemic using interrupted time series analyses. Both at DGPs and OOH-services significantly fewer antibiotics were prescribed during the COVID-19 pandemic after government measures became effective. Furthermore, the number of contacts decreased in both settings. When restrictions were revoked in 2021 prescription rates increased both at DGP and OOH-services, returning to pre-pandemic levels at OOH-services, but not in DGP. Changes in antibiotic prescribing rates were prominent for RTIs and among children up to 11 years old, but not for UTIs. To conclude, while antibiotic prescribing decreased during the first year of the COVID-19 pandemic both in daytime and out-of-hours, the pandemic does not seem to have a lasting effect on antibiotic prescribing.
ABSTRACT
AIM: To validate the Roth score as a triage tool for detecting hypoxaemia. BACKGROUNDS: The virtual assessment of patients has become increasingly important during the corona virus disease (COVID-19) pandemic, but has limitations as to the evaluation of deteriorating respiratory function. This study presents data on the validity of the Roth score as a triage tool for detecting hypoxaemia remotely in potential COVID-19 patients in general practice. METHODS: This cross-sectional validation study was conducted in Dutch general practice. Patients aged ≥18 with suspected or confirmed COVID-19 were asked to rapidly count from 1 to 30 in a single breath. The Roth score involves the highest number counted during exhalation (counting number) and the time taken to reach the maximal count (counting time).Outcome measures were (1) the correlation between both Roth score measurements and simultaneous pulse oximetry (SpO2) on room air and (2) discrimination (c-statistic), sensitivity, specificity and predictive values of the Roth score for detecting hypoxaemia (SpO2 < 95%). FINDINGS: A total of 33 physicians enrolled 105 patients (52.4% female, mean age of 52.6 ± 20.4 years). A positive correlation was found between counting number and SpO2 (rs = 0.44, P < 0.001), whereas only a weak correlation was found between counting time and SpO2 (rs = 0.15, P = 0.14). Discrimination for hypoxaemia was higher for counting number [c-statistic 0.91 (95% CI: 0.85-0.96)] than for counting time [c-statistic 0.77 (95% CI: 0.62-0.93)]. Optimal diagnostic performance was found at a counting number of 20, with a sensitivity of 93.3% (95% CI: 68.1-99.8) and a specificity of 77.8% (95% CI: 67.8-85.9). A counting time of 7 s showed the best sensitivity of 85.7% (95% CI: 57.2-98.2) and specificity of 81.1% (95% CI: 71.5-88.6). CONCLUSIONS: A Roth score, with an optimal counting number cut-off value of 20, maybe of added value for signalling hypoxaemia in general practice. Further external validation is warranted before recommending integration in telephone triage.