Prevalence of and factors associated with COVID-19 diagnosis in symptomatic patients followed in general practices in Germany between March 2020 and March 2021

Jacob, Louis; Koyanagi, Ai; Smith, Lynwood H.; Haro, Josep María; Rohe, Anna M.; Kostev, Karel

doi:10.1016/j.ijid.2021.08.010

Cited by 14 publications

(14 citation statements)

References 36 publications

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“…Finally, one could argue that about half of the individuals identified as positive by the bracelet did not show SARS-CoV-2 infection in subsequent laboratory testing, and an unnecessary testing burden could arise from this fact. The positivity rates of PCR testing (ie, approximately 15%, depending on disease prevalence)37 38 in symptomatic outpatients routinely tested during the pandemic which were considerably lower than the 50% observed in asymptomatic Ava-bracelet users. Hence, the Ava-bracelet could be regarded as progress when compared with the current testing routine.…”

Section: Discussionmentioning

confidence: 80%

Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP)

et al. 2022

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ObjectivesWe investigated machinelearningbased identification of presymptomatic COVID-19 and detection of infection-related changes in physiology using a wearable device.DesignInterim analysis of a prospective cohort study.Setting, participants and interventionsParticipants from a national cohort study in Liechtenstein were included. Nightly they wore the Ava-bracelet that measured respiratory rate (RR), heart rate (HR), HR variability (HRV), wrist-skin temperature (WST) and skin perfusion. SARS-CoV-2 infection was diagnosed by molecular and/or serological assays.ResultsA total of 1.5 million hours of physiological data were recorded from 1163 participants (mean age 44±5.5 years). COVID-19 was confirmed in 127 participants of which, 66 (52%) had worn their device from baseline to symptom onset (SO) and were included in this analysis. Multi-level modelling revealed significant changes in five (RR, HR, HRV, HRV ratio and WST) device-measured physiological parameters during the incubation, presymptomatic, symptomatic and recovery periods of COVID-19 compared with baseline. The training set represented an 8-day long instance extracted from day 10 to day 2 before SO. The training set consisted of 40 days measurements from 66 participants. Based on a random split, the test set included 30% of participants and 70% were selected for the training set. The developed long short-term memory (LSTM) based recurrent neural network (RNN) algorithm had a recall (sensitivity) of 0.73 in the training set and 0.68 in the testing set when detecting COVID-19 up to 2 days prior to SO.ConclusionWearable sensor technology can enable COVID-19 detection during the presymptomatic period. Our proposed RNN algorithm identified 68% of COVID-19 positive participants 2 days prior to SO and will be further trained and validated in a randomised, single-blinded, two-period, two-sequence crossover trial.Trial registration numberISRCTN51255782; Pre-results.

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Section: Discussionmentioning

confidence: 80%

Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP)

et al. 2022

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“…According to previous reports, older age, male sex, presence of comorbidities including hypertension, CVD, COPD, CKD, cancer and immunosuppression were more common in patients deceased, probably as a result of more severe disease and higher rates of respiratory failure requiring intubation and ICU admission [3,4,[20][21][22][23][12][13][14][15][16][17][18][19]. With regard to comorbidities, the results of this study revealed an association of CKD and immunosuppression with COVID-19 related mortality as previously reported [17,[24][25][26].…”

Section: Administrated Therapies During Hospitalizationmentioning

confidence: 99%

Association of patient characteristics with clinical outcomes in a cohort of hospitalised patients with SARS-CoV-2 infection in a Greek referral centre for COVID-19

et al. 2022

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Patient-important outcomes related to COVID-19 continue to drive the pandemic response across the globe. Various prognostic factors for COVID-19 severity have emerged and their replication across different clinical settings providing health services is ongoing. We aimed to describe the clinical characteristics and their association with outcomes in patients hospitalised with COVID-19 in the University hospital of Ioannina. We assessed a cohort of 681 consecutively hospitalised patients with COVID-19 from January 2020 to December 2021. Demographic data, underlying comorbidities, clinical presentation, biochemical markers, radiologic findings, COVID-19 treatment and outcome data were collected at the first day of hospitalisation and up to 90 days. Multivariable Cox regression analyses were performed to investigate the associations between clinical characteristics (hazard ratios [HRs] per standard deviation [SD]) with intubation and/or mortality status. The participants' mean age was 62.8 (SD, 16.9) years and 57% were males. The most common comorbidities were hypertension (45%), cardiovascular disease (19%), and diabetes mellitus (21%). Patients usually presented with fever (81%), cough (50%), and dyspnea (27%), while lymphopenia and increased inflammatory markers were the most common laboratory abnormalities. Overall, 55 patients (8%) were intubated, and 86 patients (13%) died. There were statistically significant positive associations between intubation or death with age (HR:2.59; 95% CI:1.52-4.40), lactate dehydrogenase (HR:1.44; 95% CI:1.04-1.98), pO 2 /FiO 2 ratio<100mmHg (HR:3.52; 95% CI:1.14-10.84), and inverse association with absolute lymphocyte count (HR:0.54; 95% CI:0.33-0.87). These data might help to identify points for improvement in the management of COVID-19 patients.

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“…A review from the early phase of the pandemic concluded that individuals with obesity had 113% higher risk of hospitalization if they had COVID, with 74% increased risk of ICU admission and 48% increased risk of death [3]. Many studies have since demonstrated that obesity increases risk of severe outcomes, and a few meta-analyses and studies also suggest that obesity could be a risk factor for increased susceptibility to COVID-19 (i.e., likelihood to test positive) [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Predictive capacity of COVID-19-related risk beliefs on weight management behaviors on a commercial weight loss program and speed of COVID-19 vaccination uptake: prospective cohort study

Mitchell

Lee

et al. 2022

BMC Public Health

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Background Recent work has shown that obesity may be a risk factor for severe COVID-19. However, it is unclear to what extent individuals have heard or believe this risk factor information, and how these beliefs may predict their preventive behaviors (e.g., weight management behaviors or COVID-19 preventive behaviors). Previous work has primarily looked at overall risk likelihood perceptions (i.e., not about obesity as a risk factor) within general populations of varying weight and concentrated on COVID-19-related preventive behaviors. Therefore, this prospective cohort study explored whether beliefs about obesity as a risk factor and overall risk likelihood perceptions predicted weight management and COVID-19 preventive behaviors over the next 16 weeks in individuals with obesity or overweight. Methods Participants were 393 individuals in the US who joined a commercial weight management program in January, 2021. We leveraged the mobile program’s automatic measurement of real-time engagement in weight management behaviors (e.g., steps taken), while surveys measured risk beliefs at baseline as well as when individuals received COVID-19 vaccination doses (asked monthly) over the next 16 weeks. Mixed effects models predicted engagement and weight loss each week for 16 weeks, while ordinal logistic regression models predicted the month that individuals got vaccinated against COVID-19. Results We found that belief in obesity as a risk factor at baseline significantly predicted greater engagement (e.g., steps taken, foods logged) in program-measured weight management behaviors over the next 16 weeks in models adjusted for baseline BMI, age, gender, and local vaccination rates (minimally adjusted) and in models additionally adjusted for demographic factors. Belief in obesity as a risk factor at baseline also significantly predicted speed of COVID-19 vaccination uptake in minimally adjusted models but not when demographic factors were taken into account. Exposure to obesity risk factor information at baseline predicted greater engagement over 16 weeks in minimally adjusted models. Conclusions The results highlight the potential utility of effective education to increase individuals’ belief in obesity risk factor information and ultimately promote engagement or faster vaccination. Future research should investigate to what extent the results generalize to other populations.

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Prevalence of and factors associated with COVID-19 diagnosis in symptomatic patients followed in general practices in Germany between March 2020 and March 2021

Cited by 14 publications

References 36 publications

Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP)

Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP)

Association of patient characteristics with clinical outcomes in a cohort of hospitalised patients with SARS-CoV-2 infection in a Greek referral centre for COVID-19

Predictive capacity of COVID-19-related risk beliefs on weight management behaviors on a commercial weight loss program and speed of COVID-19 vaccination uptake: prospective cohort study

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