Procalcitonin-guided antibiotic prescription in patients with COVID-19: a multicentre observational cohort study

Background Despite the low rate of bacterial co-infection, antibiotics are very commonly prescribed in hospitalised COVID-19 patients. Research question Does the use of a PCT-guided antibiotic protocol safely reduce the use of antibiotics in patients with a COVID-19 infection? Study design and methods In this multicentre cohort, 3 groups of COVID-19 patients were compared in terms of antibiotic consumption, namely one group treated based on a PCT-algorithm in one hospital (n=216) and 2 control groups, consisted of patients from the same hospital (n=57) and of patients from 3 similar hospitals (n=486) without PCT measurements during the same period. The primary endpoint was antibiotic prescription in the first week of admission. Results Antibiotic prescription during the first 7 days was 26.8% in the PCT-group, 43.9% in the non-PCT group in the same hospital and 44.7% in the non-PCT group in other hospitals. Patients in the PCT-group had lower odds of receiving antibiotics in the first 7 days of admission (OR 0.33;0.16 - 0.66 compared to the same hospital and OR 0.42;95% CI 0.28 – 0.62 compared to the other hospitals). The proportion of patients receiving antibiotic prescription during the total admission was respectively 35.2%, 43.9% and 54.5%. The PCT-group had lower odds of receiving antibiotics during the total admission only when compared to the other hospitals (OR 0.23;95%CI 0.08 - 0.63). There were no significant differences in other secondary endpoints, except for re-admission in the PCT-group versus the other hospitals group. Interpretation : PCT-guided antibiotic prescription reduces antibiotic prescription rates in hospitalised patients with COVID-19, without major safety concerns.

CT Scan-Derived Muscle, But Not Fat, Area Independently Predicts Mortality in COVID-19.

BACKGROUND: COVID-19 has demonstrated a highly variable disease course, from asymptomatic to severe illness and eventually death. Clinical parameters, as included in the 4C Mortality Score, can predict mortality accurately in COVID-19. Additionally, CT scan-derived low muscle and high adipose tissue cross-sectional areas (CSAs) have been associated with adverse outcomes in COVID-19. RESEARCH QUESTION: Are CT scan-derived muscle and adipose tissue CSAs associated with 30-day in-hospital mortality in COVID-19, independent of 4C Mortality Score? STUDY DESIGN AND METHODS: This was a retrospective cohort analysis of patients with COVID-19 seeking treatment at the ED of two participating hospitals during the first wave of the pandemic. Skeletal muscle and adipose tissue CSAs were collected from routine chest CT-scans at admission. Pectoralis muscle CSA was demarcated manually at the fourth thoracic vertebra, and skeletal muscle and adipose tissue CSA was demarcated at the first lumbar vertebra level. Outcome measures and 4C Mortality Score items were retrieved from medical records. RESULTS: Data from 578 patients were analyzed (64.6% men; mean age, 67.7 ± 13.5 years; 18.2% 30-day in-hospital mortality). Patients who died within 30 days demonstrated lower pectoralis CSA (median, 32.6 [interquartile range (IQR), 24.3-38.8] vs 35.4 [IQR, 27.2-44.2]; P = .002) than survivors, whereas visceral adipose tissue CSA was higher (median, 151.1 [IQR, 93.6-219.7] vs 112.9 [IQR, 63.7-174.1]; P = .013). In multivariate analyses, low pectoralis muscle CSA remained associated with 30-day in-hospital mortality when adjusted for 4C Mortality Score (hazard ratio, 0.98; 95% CI, 0.96-1.00; P = .038). INTERPRETATION: CT scan-derived low pectoralis muscle CSA is associated significantly with higher 30-day in-hospital mortality in patients with COVID-19 independently of the 4C Mortality Score.

Association of Heart Rate Variability with Pulmonary Function Impairment and Symptomatology Post-COVID-19 Hospitalization.

The persistence of symptoms beyond three months after COVID-19 infection, often referred to as post-COVID-19 condition (PCC), is commonly experienced. It is hypothesized that PCC results from autonomic dysfunction with decreased vagal nerve activity, which can be indexed by low heart rate variability (HRV). The aim of this study was to assess the association of HRV upon admission with pulmonary function impairment and the number of reported symptoms beyond three months after initial hospitalization for COVID-19 between February and December 2020. Follow-up took place three to five months after discharge and included pulmonary function tests and the assessment of persistent symptoms. HRV analysis was performed on one 10 s electrocardiogram obtained upon admission. Analyses were performed using multivariable and multinomial logistic regression models. Among 171 patients who received follow-up, and with an electrocardiogram at admission, decreased diffusion capacity of the lung for carbon monoxide (DLCO) (41%) was most frequently found. After a median of 119 days (IQR 101-141), 81% of the participants reported at least one symptom. HRV was not associated with pulmonary function impairment or persistent symptoms three to five months after hospitalization for COVID-19.

Pulmonary function three to five months after hospital discharge for COVID-19: a single centre cohort study.

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.

Overweight and Obesity Are Associated With Acute Kidney Injury and Acute Respiratory Distress Syndrome, but Not With Increased Mortality in Hospitalized COVID-19 Patients: A Retrospective Cohort Study.

Objective: To evaluate the association between overweight and obesity on the clinical course and outcomes in patients hospitalized with COVID-19. Design: Retrospective, observational cohort study. Methods: We performed a multicenter, retrospective, observational cohort study of hospitalized COVID-19 patients to evaluate the associations between overweight and obesity on the clinical course and outcomes. Results: Out of 1634 hospitalized COVID-19 patients, 473 (28.9%) had normal weight, 669 (40.9%) were overweight, and 492 (30.1%) were obese. Patients who were overweight or had obesity were younger, and there were more women in the obese group. Normal-weight patients more often had pre-existing conditions such as malignancy, or were organ recipients. During admission, patients who were overweight or had obesity had an increased probability of acute respiratory distress syndrome [OR 1.70 (1.26-2.30) and 1.40 (1.01-1.96)], respectively and acute kidney failure [OR 2.29 (1.28-3.76) and 1.92 (1.06-3.48)], respectively. Length of hospital stay was similar between groups. The overall in-hospital mortality rate was 27.7%, and multivariate logistic regression analyses showed that overweight and obesity were not associated with increased mortality compared to normal-weight patients. Conclusion: In this study, overweight and obesity were associated with acute respiratory distress syndrome and acute kidney injury, but not with in-hospital mortality nor length of hospital stay.

SARS-CoV-2 seroprevalence in healthcare workers of a teaching hospital in a highly endemic region in the Netherlands after the first wave: a cross-sectional study.

OBJECTIVE: To 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. DESIGN: A cross-sectional study in healthcare workers. SETTING: Northern Limburg, the Netherlands. PARTICIPANTS: All employees of VieCuri Medical Center (n=3300) were invited to enrol in current study. In total 2507 healthcare workers participated. INTERVENTION: Between 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 MEASURE: Proportion of healthcare workers with positive SARS-CoV-2 serology. RESULTS: The 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). CONCLUSIONS: Healthcare 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.

Sort and Sieve: Pre-Triage Screening of Patients with Suspected COVID-19 in the Emergency Department.

INTRODUCTION: To reduce the risk of nosocomial transmission, suspected COVID-19 patients entering the Emergency Department (ED) were assigned to a high-risk (ED) or low-risk (acute medical unit, AMU) area based on symptoms, travel and contact history. The objective of this study was to evaluate the performance of our pre-triage screening method and to analyse the characteristics of initially undetected COVID-19 patients. METHODS: This was a retrospective, observational, single centre study. Patients ≥ 18 years visiting the AMU-ED between 17 March and 17 April 2020 were included. Primary outcome was the (correct) number of COVID-19 patients assigned to the AMU or ED. RESULTS: In total, 1287 patients visited the AMU-ED: 525 (40.8%) AMU, 762 (59.2%) ED. Within the ED group, 304 (64.3%) of 473 tested patients were COVID-19 positive, compared to 13 (46.4%) of 28 tested patients in the AMU group. Our pre-triage screening accuracy was 63.7%. Of the 13 COVID-19 patients who were initially assigned to the AMU, all patients were ≥65 years of age and the majority presented with gastro-intestinal or non-specific symptoms. CONCLUSION: Older COVID-19 patients presenting with non-specific symptoms were more likely to remain undetected. ED screening protocols should therefore also include non-specific symptoms, particularly in older patients.

Predicting mortality of individual patients with COVID-19: a multicentre Dutch cohort.

OBJECTIVE: Develop and validate models that predict mortality of patients diagnosed with COVID-19 admitted to the hospital. DESIGN: Retrospective cohort study. SETTING: A multicentre cohort across 10 Dutch hospitals including patients from 27 February to 8 June 2020. PARTICIPANTS: SARS-CoV-2 positive patients (age ≥18) admitted to the hospital. MAIN OUTCOME MEASURES: 21-day all-cause mortality evaluated by the area under the receiver operator curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The predictive value of age was explored by comparison with age-based rules used in practice and by excluding age from the analysis. RESULTS: 2273 patients were included, of whom 516 had died or discharged to palliative care within 21 days after admission. Five feature sets, including premorbid, clinical presentation and laboratory and radiology values, were derived from 80 features. Additionally, an Analysis of Variance (ANOVA)-based data-driven feature selection selected the 10 features with the highest F values: age, number of home medications, urea nitrogen, lactate dehydrogenase, albumin, oxygen saturation (%), oxygen saturation is measured on room air, oxygen saturation is measured on oxygen therapy, blood gas pH and history of chronic cardiac disease. A linear logistic regression and non-linear tree-based gradient boosting algorithm fitted the data with an AUC of 0.81 (95% CI 0.77 to 0.85) and 0.82 (0.79 to 0.85), respectively, using the 10 selected features. Both models outperformed age-based decision rules used in practice (AUC of 0.69, 0.65 to 0.74 for age >70). Furthermore, performance remained stable when excluding age as predictor (AUC of 0.78, 0.75 to 0.81). CONCLUSION: Both models showed good performance and had better test characteristics than age-based decision rules, using 10 admission features readily available in Dutch hospitals. The models hold promise to aid decision-making during a hospital bed shortage.

Treatment with a DPP-4 inhibitor at time of hospital admission for COVID-19 is not associated with improved clinical outcomes: data from the COVID-PREDICT cohort study in The Netherlands.

Purpose: Inhibition of dipeptidyl peptidase (DPP-)4 could reduce coronavirus disease 2019 (COVID-19) severity by reducing inflammation and enhancing tissue repair beyond glucose lowering. We aimed to assess this in a prospective cohort study. Methods: We studied in 565 patients with type 2 diabetes in the CovidPredict Clinical Course Cohort whether use of a DPP-4 inhibitor prior to hospital admission due to COVID-19 was associated with improved clinical outcomes. Using crude analyses and propensity score matching (on age, sex and BMI), 28 patients using a DPP-4 inhibitor were identified and compared to non-users. Results: No differences were found in the primary outcome mortality (matched-analysis = odds-ratio: 0,94 [95% confidence interval: 0,69 - 1,28], p-value: 0,689) or any of the secondary outcomes (ICU admission, invasive ventilation, thrombotic events or infectious complications). Additional analyses comparing users of DPP-4 inhibitors with subgroups of non-users (subgroup 1: users of metformin and sulphonylurea; subgroup 2: users of any insulin combination), allowing to correct for diabetes severity, did not yield different results. Conclusions: We conclude that outpatient use of a DPP-4 inhibitor does not affect the clinical outcomes of patients with type 2 diabetes who are hospitalized because of COVID-19 infection.

Early detection of hospitalized patients with COVID-19 at high risk of clinical deterioration: Utility of emergency department shock index.

BACKGROUND: 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. METHODS: 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. RESULTS: 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%. CONCLUSION: 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.

Can predicting COVID-19 mortality in a European cohort using only demographic and comorbidity data surpass age-based prediction: An externally validated study.

OBJECTIVE: To establish whether one can build a mortality prediction model for COVID-19 patients based solely on demographics and comorbidity data that outperforms age alone. Such a model could be a precursor to implementing smart lockdowns and vaccine distribution strategies. METHODS: The training cohort comprised 2337 COVID-19 inpatients from nine hospitals in The Netherlands. The clinical outcome was death within 21 days of being discharged. The features were derived from electronic health records collected during admission. Three feature selection methods were used: LASSO, univariate using a novel metric, and pairwise (age being half of each pair). 478 patients from Belgium were used to test the model. All modeling attempts were compared against an age-only model. RESULTS: In the training cohort, the mortality group's median age was 77 years (interquartile range = 70-83), higher than the non-mortality group (median = 65, IQR = 55-75). The incidence of former/active smokers, male gender, hypertension, diabetes, dementia, cancer, chronic obstructive pulmonary disease, chronic cardiac disease, chronic neurological disease, and chronic kidney disease was higher in the mortality group. All stated differences were statistically significant after Bonferroni correction. LASSO selected eight features, novel univariate chose five, and pairwise chose none. No model was able to surpass an age-only model in the external validation set, where age had an AUC of 0.85 and a balanced accuracy of 0.77. CONCLUSION: When applied to an external validation set, we found that an age-only mortality model outperformed all modeling attempts (curated on www.covid19risk.ai) using three feature selection methods on 22 demographic and comorbid features.

Osteoporosis care during the COVID-19 pandemic in the Netherlands: A national survey.

This is a survey study concerning osteoporosis care during the COVID-19 pandemic in the Netherlands. Respondents reported that osteoporosis care stagnated and lower quality of care was provided. This leads to the conclusion that standardization of osteoporosis care delivery in situations of crisis is needed. PURPOSE: During the initial phase of the COVID-19 pandemic, there was no guidance of professional societies or guidelines on the organization of osteoporosis care in case of such a crisis, and treatment relied on local ad hoc strategies. Experiences from the current pandemic need to be taken into account for the near future, and therefore, a national multidisciplinary survey was carried out in the Netherlands. METHODS: A survey of 17 questions concerning the continuation of bone mineral density measurements by Dual Energy X-ray absorptiometry (DXA), outpatient clinic visits, and prescription of medication was sent to physicians, nurses, nurse practitioners, and physician assistants working in the field of osteoporosis. RESULTS: 77 respondents finished the questionnaire, of whom 39 (50.6%) reported a decline in DXA-scanning and 36 (46.8%) no scanning at all during the pandemic. There was an increase in remote consultations for both new and control patient visits (n = 48, 62.3%; n = 62, 81.7% respectively). Lower quality of care regarding fracture prevention was reported by more than half of the respondents (n = 44, 57.1%). Treatment with intravenous bisphosphonates and denosumab was delayed according to 35 (45.4%) and 6 (6.3%) of the respondents, respectively. CONCLUSION: During the COVID-19 pandemic, osteoporosis care almost completely arrested, especially because of the discontinuation of DXA-scanning and closing of outpatient clinics. More than half of the respondents reported a substantial lower quality of osteoporosis care during the COVID pandemic. To prevent an increase in fracture rates and a decrease in patient motivation, adherence and satisfaction, standardization of osteoporosis care delivery in situations of crisis is needed.