Objectives
A high incidence of delirium has been reported in older patients with Coronavirus disease 2019 (COVID‐19). We aimed to identify determinants of delirium, including the Clinical Frailty ...Scale, in hospitalized older patients with COVID‐19. Furthermore, we aimed to study the association of delirium independent of frailty with in‐hospital outcomes in older COVID‐19 patients.
Methods
This study was performed within the framework of the multi‐center COVID‐OLD cohort study and included patients aged ≥60 years who were admitted to the general ward because of COVID‐19 in the Netherlands between February and May 2020. Data were collected on demographics, co‐morbidity, disease severity, and geriatric parameters. Prevalence of delirium during hospital admission was recorded based on delirium screening using the Delirium Observation Screening Scale (DOSS) which was scored three times daily. A DOSS score ≥3 was followed by a delirium assessment by the ward physician In‐hospital outcomes included length of stay, discharge destination, and mortality.
Results
A total of 412 patients were included (median age 76, 58% male). Delirium was present in 82 patients. In multivariable analysis, previous episode of delirium (Odds ratio OR 8.9 95% CI 2.3–33.6 p = 0.001), and pre‐existent memory problems (OR 7.6 95% CI 3.1–22.5 p < 0.001) were associated with increased delirium risk. Clinical Frailty Scale was associated with increased delirium risk (OR 1.63 95%CI 1.40–1.90 p < 0.001) in univariable analysis, but not in multivariable analysis. Patients who developed delirium had a shorter symptom duration and lower levels of C‐reactive protein upon presentation, whereas vital parameters did not differ. Patients who developed a delirium had a longer hospital stay and were more often discharged to a nursing home. Delirium was associated with mortality (OR 2.84 95% CI1.71–4.72 p < 0.001), but not in multivariable analyses.
Conclusions
A previous delirium and pre‐existent memory problems were associated with delirium risk in COVID‐19. Delirium was not an independent predictor of mortality after adjustment for frailty.
Key points
A previous episode of delirium and pre‐existent memory problems were independent predictors of delirium risk in older adults hospitalized with COVID‐19.
Reports on the association of delirium with poor outcomes, independent of frailty, in older hospitalized COVID‐19 patients have been conflicting.
In this study, delirium was not a predictor of in‐hospital mortality independent of frailty.
The COVID-19 outbreak has put an unprecedented strain on Emergency Departments (EDs) and other critical care resources. Early detection of patients that are at high risk of clinical deterioration and ...require intensive monitoring, is key in ED evaluation and disposition. A rapid and easy risk-stratification tool could aid clinicians in early decision making. The Shock Index (SI: heart rate/systolic blood pressure) proved useful in detecting hemodynamic instability in sepsis and myocardial infarction patients. In this study we aim to determine whether SI is discriminative for ICU admission and in-hospital mortality in COVID-19 patients.
Retrospective, observational, single-center study. All patients ≥18 years old who were hospitalized with COVID-19 (defined as: positive result on reverse transcription polymerase chain reaction (PCR) test) between March 1, 2020 and December 31, 2020 were included for analysis. Data were collected from electronic medical patient records and stored in a protected database. ED shock index was calculated and analyzed for its discriminative value on in-hospital mortality and ICU admission by a ROC curve analysis.
In total, 411 patients were included. Of all patients 249 (61%) were male. ICU admission was observed in 92 patients (22%). Of these, 37 patients (40%) died in the ICU. Total in-hospital mortality was 28% (114 patients). For in-hospital mortality the optimal cut-off SI ≥ 0.86 was not discriminative (AUC 0.49 (95% CI: 0.43–0.56)), with a sensitivity of 12.3% and specificity of 93.6%. For ICU admission the optimal cut-off SI ≥ 0.57 was also not discriminative (AUC 0.56 (95% CI: 0.49–0.62)), with a sensitivity of 78.3% and a specificity of 34.2%.
In this cohort of patients hospitalized with COVID-19, SI measured at ED presentation was not discriminative for ICU admission and was not useful for early identification of patients at risk of clinical deterioration.
Some COVID-19 survivors suffer from persistent pulmonary function impairment, but the extent and associated factors are unclear. This study aimed to characterize pulmonary function impairment three ...to five months after hospital discharge and the association with disease severity. Survivors of COVID-19 after hospitalization to the VieCuri Medical Centre between February and December 2020 were invited for follow-up, three to five months after discharge. Dynamic and static lung volumes, respiratory muscle strength and diffusion capacity were measured. The cohort comprised 257 patients after a moderate (n = 33), severe (n = 151) or critical (n = 73) COVID-19 infection with a median follow-up of 112 days (interquartile range 96-134 days). The main sequelae included reduced diffusion capacity (36%) and reduced maximal expiratory pressure (24%). Critically ill patients were more likely to have reduced diffusion capacity than moderate (OR 8.00, 95% CI 2.46-26.01) and severe cases (OR 3.74, 95% CI 1.88-7.44) and lower forced vital capacity (OR 3.29, 95% CI 1.20-9.06) compared to severe cases. Many COVID-19 survivors, especially after a critical disease course, showed pulmonary function sequelae, mainly DLCO impairments, three to five months after discharge. Monitoring is needed to investigate the persistence of these symptoms and the longer-term implications of the COVID-19 burden.
Although male Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) patients have higher Intensive Care Unit (ICU) admission rates and a worse disease course, a comprehensive analysis of ...female and male ICU survival and underlying factors such as comorbidities, risk factors, and/or anti-infection/inflammatory therapy administration is currently lacking. Therefore, we investigated the association between sex and ICU survival, adjusting for these and other variables. In this multicenter observational cohort study, all patients with SARS-CoV-2 pneumonia admitted to seven ICUs in one region across Belgium, The Netherlands, and Germany, and requiring vital organ support during the first pandemic wave were included. With a random intercept for a center, mixed-effects logistic regression was used to investigate the association between sex and ICU survival. Models were adjusted for age, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, comorbidities, and anti-infection/inflammatory therapy. Interaction terms were added to investigate effect modifications by sex with country and sex with obesity. A total of 551 patients (29% were females) were included. Mean age was 65.4 ± 11.2 years. Females were more often obese and smoked less frequently than males (p-value 0.001 and 0.042, respectively). APACHE II scores of females and males were comparable. Overall, ICU mortality was 12% lower in females than males (27% vs 39% respectively, p-value < 0.01) with an odds ratio (OR) of 0.62 (95%CI 0.39-0.96, p-value 0.032) after adjustment for age and APACHE II score, 0.63 (95%CI 0.40-0.99, p-value 0.044) after additional adjustment for comorbidities, and 0.63 (95%CI 0.39-0.99, p-value 0.047) after adjustment for anti-infection/inflammatory therapy. No effect modifications by sex with country and sex with obesity were found (p-values for interaction > 0.23 and 0.84, respectively). ICU survival in female SARS-CoV-2 patients was higher than in male patients, independent of age, disease severity, smoking, obesity, comorbidities, anti-infection/inflammatory therapy, and country. Sex-specific biological mechanisms may play a role, emphasizing the need to address diversity, such as more sex-specific prediction, prognostic, and therapeutic approach strategies.
ObjectiveTo study the SARS-CoV-2 infection rate among hospital healthcare workers after the first wave of the COVID-19 pandemic, and provide more knowledge in the understanding of the relationship ...between infection, symptomatology and source of infection.DesignA cross-sectional study in healthcare workers.SettingNorthern Limburg, the Netherlands.ParticipantsAll employees of VieCuri Medical Center (n=3300) were invited to enrol in current study. In total 2507 healthcare workers participated.InterventionBetween 22 June 2020 and 3 July 2020, participants provided venous blood samples voluntarily, which were tested for SARS-CoV-2 antibodies with the Wantai SARS-CoV-2 Ig total ELISA test. Work characteristics, exposure risks and prior symptoms consistent with COVID-19 were gathered through a survey.Main outcome measureProportion of healthcare workers with positive SARS-CoV-2 serology.ResultsThe overall seroprevalence was 21.1% (n=530/2507). Healthcare workers between 17 and 30 years were more likely to have SARS-CoV-2 antibodies compared with participants >30 years. The probability of having SARS-CoV-2 antibodies was comparable for healthcare workers with and without direct patient (OR 1.42, 95% CI 0.86 to 2.34) and COVID-19 patient contact (OR 1.62, 95% CI 0.80 to 3.33). On the contrary, exposure to COVID-19 positive coworkers (OR 1.83, 95% CI 1.15 to 2.93) and household members (OR 6.09, 95% CI 2.23 to 16.64) was associated with seropositivity. Of those healthcare workers with SARS-CoV-2 antibodies, 16% (n=85/530) had not experienced any prior COVID-19-related symptoms. Only fever and anosmia were associated with seropositivity (OR 1.90, 95% CI 1.42 to 2.55 and OR 10.51, 95% CI 7.86 to 14.07).ConclusionsHealthcare workers caring for hospitalised COVID-19 patients were not at an increased risk of infection, most likely as a result of taking standard infection control measures into consideration. These data show that compliance with infection control measures is essential to control secondary transmission and constrain the spread of the virus.
With increasing age, assuming the upright position is more often accompanied by symptoms such as dizziness and lightheadedness, possibly as a result of a diminished oxygen supply to the brain due to ...impaired cerebral autoregulation. We aimed to quantify postural changes in cerebral oxygenation and systemic hemodynamics in healthy elderly and young subjects.
In 18 healthy elderly subjects (aged 70 to 83 years) and 10 healthy young subjects (aged 22 to 45 years), frontal cortical oxygenation and hemodynamic responses were continuously monitored by near infrared spectroscopy and Finapres, respectively, before and during 10 minutes of active standing.
-Cortical oxyhemoglobin concentration O(2)Hb decreased by -4.6+/-2.2 micromol/L (P<0.001) and cortical deoxyhemoglobin concentration increased by 1.5+/-2.4 micromol/L (P<0.05) in the elderly subjects after posture change, whereas these variables did not change significantly in the young subjects. The postural hemodynamic changes tended to be attenuated in the elderly subjects, except for the increases in systolic blood pressure (BP). Smaller postural increases in diastolic BP were related to larger O(2)Hb decreases (r=0.53, P<0.01, corrected for the age effect).
Assuming the upright position evokes an asymptomatic decrease in frontal cortical oxygenation in healthy elderly subjects but not in healthy young subjects. Cortical O(2)Hb changes are affected by diastolic BP changes. These findings may indicate that regulation of cerebral oxygenation alters with increasing age.
To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. ...Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data.
Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors.
A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors.
In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves.
To investigate healthcare system-driven variation in general characteristics, interventions, and outcomes in coronavirus disease 2019 (COVID-19) patients admitted to the ICU within one Western ...European region across three countries.
Multicenter observational cohort study.
Seven ICUs in the Euregio Meuse-Rhine, one region across Belgium, The Netherlands, and Germany.
Consecutive COVID-19 patients supported in the ICU during the first pandemic wave.
None.
Baseline demographic and clinical characteristics, laboratory values, and outcome data were retrieved after ethical approval and data-sharing agreements. Descriptive statistics were performed to investigate country-related practice variation. From March 2, 2020, to August 12, 2020, 551 patients were admitted. Mean age was 65.4 ± 11.2 years, and 29% were female. At admission, Acute Physiology and Chronic Health Evaluation II scores were 15.0 ± 5.5, 16.8 ± 5.5, and 15.8 ± 5.3 (p = 0.002), and Sequential Organ Failure Assessment scores were 4.4 ± 2.7, 7.4 ± 2.2, and 7.7 ± 3.2 (p < 0.001) in the Belgian, Dutch, and German parts of Euregio, respectively. The ICU mortality rate was 22%, 42%, and 44%, respectively (p < 0.001). Large differences were observed in the frequency of organ support, antimicrobial/inflammatory therapy application, and ICU capacity. Mixed-multivariable logistic regression analyses showed that differences in ICU mortality were independent of age, sex, disease severity, comorbidities, support strategies, therapies, and complications.
COVID-19 patients admitted to ICUs within one region, the Euregio Meuse-Rhine, differed significantly in general characteristics, applied interventions, and outcomes despite presumed genetic and socioeconomic background, admission diagnosis, access to international literature, and data collection are similar. Variances in healthcare systems' organization, particularly ICU capacity and admission criteria, combined with a rapidly spreading pandemic might be important drivers for the observed differences. Heterogeneity between patient groups but also healthcare systems should be presumed to interfere with outcomes in coronavirus disease 2019.
Many prediction models for coronavirus disease 2019 (COVID-19) have been developed. External validation is mandatory before implementation in the intensive care unit (ICU). We selected and validated ...prognostic models in the Euregio Intensive Care COVID (EICC) cohort.
In this multinational cohort study, routine data from COVID-19 patients admitted to ICUs within the Euregio Meuse-Rhine were collected from March to August 2020. COVID-19 models were selected based on model type, predictors, outcomes, and reporting. Furthermore, general ICU scores were assessed. Discrimination was assessed by area under the receiver operating characteristic curves (AUCs) and calibration by calibration-in-the-large and calibration plots. A random-effects meta-analysis was used to pool results.
551 patients were admitted. Mean age was 65.4 ± 11.2 years, 29% were female, and ICU mortality was 36%. Nine out of 238 published models were externally validated. Pooled AUCs were between 0.53 and 0.70 and calibration-in-the-large between −9% and 6%. Calibration plots showed generally poor but, for the 4C Mortality score and Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC) score, moderate calibration.
Of the nine prognostic models that were externally validated in the EICC cohort, only two showed reasonable discrimination and moderate calibration. For future pandemics, better models based on routine data are needed to support admission decision-making.
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