The Incidence of Pulmonary Embolism in Hospitalized Non-ICU Patients with COVID-19 during the First Wave: A Multicenter Retrospective Cohort Study in the Netherlands.

INTRODUCTION: During the first COVID-19 outbreak in 2020 in the Netherlands, the incidence of pulmonary embolism (PE) appeared to be high in COVID-19 patients admitted to the intensive care unit (ICU). This study was performed to evaluate the incidence of PE during hospital stay in COVID-19 patients not admitted to the ICU. METHODS: Data were retrospectively collected from 8 hospitals in the Netherlands. Patients admitted between February 27, 2020, and July 31, 2020, were included. Data extracted comprised clinical characteristics, medication use, first onset of COVID-19-related symptoms, admission date due to COVID-19, and date of PE diagnosis. Only polymerase chain reaction (PCR)-positive patients were included. All PEs were diagnosed with computed tomography pulmonary angiography (CTPA). RESULTS: Data from 1,852 patients who were admitted to the hospital ward were collected. Forty patients (2.2%) were diagnosed with PE within 28 days following hospital admission. The median time to PE since admission was 4.5 days (IQR 0.0-9.0). In all 40 patients, PE was diagnosed within the first 2 weeks after hospital admission and for 22 (55%) patients within 2 weeks after onset of symptoms. Patient characteristics, pre-existing comorbidities, anticoagulant use, and laboratory parameters at admission were not related to the development of PE. CONCLUSION: In this retrospective multicenter cohort study of 1,852 COVID-19 patients only admitted to the non-ICU wards, the incidence of CTPA-confirmed PE was 2.2% during the first 4 weeks after onset of symptoms and occurred exclusively within 2 weeks after hospital admission.

Lymphopenia is associated with broad host response aberrations in community-acquired pneumonia.

OBJECTIVES: Lymphopenia at hospital admission occurs in over one-third of patients with community-acquired pneumonia (CAP), yet its clinical relevance and pathophysiological implications remain underexplored. We evaluated outcomes and immune features of patients with lymphopenic CAP (L-CAP), a previously described immunophenotype characterized by admission lymphocyte count <0.724 × 109 cells/L. METHODS: Observational study in 149 patients admitted to a general ward for CAP. We measured 34 plasma biomarkers reflective of inflammation, endothelial cell responses, coagulation, and immune checkpoints. We characterized lymphocyte phenotypes in 29 patients using spectral flow cytometry. RESULTS: L-CAP occurred in 45 patients (30.2%) and was associated with prolonged time-to-clinical-stability (median 5 versus 3 days), also when we accounted for competing events for reaching clinical stability and adjusted for baseline covariates (subdistribution hazard ratio 0.63; 95% confidence interval 0.45-0.88). L-CAP patients demonstrated a proportional depletion of CD4 T follicular helper cells, CD4 T effector memory cells, naïve CD8 T cells and IgG+ B cells. Plasma biomarker analyses indicated increased activation of the cytokine network and the vascular endothelium in L-CAP. CONCLUSIONS: L-CAP patients have a protracted clinical recovery course and a more broadly dysregulated host response. These findings highlight the prognostic and pathophysiological relevance of admission lymphopenia in patients with CAP.

Host Response Changes and Their Association with Mortality in COVID-19 Patients with Lymphopenia.

Rationale: Lymphopenia in coronavirus disease (COVID-19) is associated with increased mortality. Objectives: To explore the association between lymphopenia, host response aberrations, and mortality in patients with lymphopenic COVID-19. Methods: We determined 43 plasma biomarkers reflective of four pathophysiological domains: endothelial cell and coagulation activation, inflammation and organ damage, cytokine release, and chemokine release. We explored if decreased concentrations of lymphocyte-derived proteins in patients with lymphopenia were associated with an increase in mortality. We sought to identify host response phenotypes in patients with lymphopenia by cluster analysis of plasma biomarkers. Measurements and Main Results: A total of 439 general ward patients with COVID-19 were stratified by baseline lymphocyte counts: normal (>1.0 × 109/L; n = 167), mild lymphopenia (>0.5 to ⩽1.0 × 109/L; n = 194), and severe lymphopenia (⩽0.5 × 109/L; n = 78). Lymphopenia was associated with alterations in each host response domain. Lymphopenia was associated with increased mortality. Moreover, in patients with lymphopenia (n = 272), decreased concentrations of several lymphocyte-derived proteins (e.g., CCL5, IL-4, IL-13, IL-17A) were associated with an increase in mortality (at P < 0.01 or stronger significance levels). A cluster analysis revealed three host response phenotypes in patients with lymphopenia: "hyporesponsive" (23.2%), "hypercytokinemic" (36.4%), and "inflammatory-injurious" (40.4%), with substantially differing mortality rates of 9.5%, 5.1%, and 26.4%, respectively. A 10-biomarker model accurately predicted these host response phenotypes in an external cohort with similar mortality distribution. The inflammatory-injurious phenotype showed a remarkable combination of relatively high inflammation and organ damage markers with high antiinflammatory cytokine levels yet low proinflammatory cytokine levels. Conclusions: Lymphopenia in COVID-19 signifies a heterogenous group of patients with distinct host response features. Specific host responses contribute to lymphopenia-associated mortality in COVID-19, including reduced CCL5 levels.

High-dimensional phenotyping of the peripheral immune response in community-acquired pneumonia.

Background: Community-acquired pneumonia (CAP) represents a major health burden worldwide. Dysregulation of the immune response plays an important role in adverse outcomes in patients with CAP. Methods: We analyzed peripheral blood mononuclear cells by 36-color spectral flow cytometry in adult patients hospitalized for CAP (n=40), matched control subjects (n=31), and patients hospitalized for COVID-19 (n=35). Results: We identified 86 immune cell metaclusters, 19 of which (22.1%) were differentially abundant in patients with CAP versus matched controls. The most notable differences involved classical monocyte metaclusters, which were more abundant in CAP and displayed phenotypic alterations reminiscent of immunosuppression, increased susceptibility to apoptosis, and enhanced expression of chemokine receptors. Expression profiles on classical monocytes, driven by CCR7 and CXCR5, divided patients with CAP into two clusters with a distinct inflammatory response and disease course. The peripheral immune response in patients with CAP was highly similar to that in patients with COVID-19, but increased CCR7 expression on classical monocytes was only present in CAP. Conclusion: CAP is associated with profound cellular changes in blood that mainly relate to classical monocytes and largely overlap with the immune response detected in COVID-19.

Platelets of COVID-19 patients display mitochondrial dysfunction, oxidative stress, and energy metabolism failure compatible with cell death.

Background: Alterations in platelet function have been implicated in the pathophysiology of COVID-19 since the beginning of the pandemic. While early reports linked hyperactivated platelets to thromboembolic events in COVID-19, subsequent investigations demonstrated hyporeactive platelets with a procoagulant phenotype. Mitochondria are important for energy metabolism and the function of platelets. Objectives: Here, we sought to map the energy metabolism of platelets in a cohort of noncritically ill COVID-19 patients and assess platelet mitochondrial function, activation status, and responsiveness to external stimuli. Methods: We enrolled hospitalized COVID-19 patients and controls between October 2020 and December 2021. Platelets function and metabolism was analyzed by flow cytometry, metabolomics, glucose fluxomics, electron and fluorescence microscopy and western blot. Results: Platelets from COVID-19 patients showed increased phosphatidylserine externalization indicating a procoagulant phenotype and hyporeactivity to ex vivo stimuli, associated with profound mitochondrial dysfunction characterized by mitochondrial depolarization, lower mitochondrial DNA-encoded transcript levels, an altered mitochondrial morphology consistent with increased mitochondrial fission, and increased pyruvate/lactate ratios in platelet supernatants. Metabolic profiling by untargeted metabolomics revealed NADH, NAD+, and ATP among the top decreased metabolites in patients' platelets, suggestive of energy metabolism failure. Consistently, platelet fluxomics analyses showed a strongly reduced utilization of 13C-glucose in all major energy pathways together with a rerouting of glucose to de novo generation of purine metabolites. Patients' platelets further showed evidence of oxidative stress, together with increased glutathione oxidation and synthesis. Addition of plasma from COVID-19 patients to normal platelets partially reproduced the phenotype of patients' platelets and disclosed a temporal relationship between mitochondrial decay and (subsequent) phosphatidylserine exposure and hyporeactivity. Conclusion: These data link energy metabolism failure in platelets from COVID-19 patients with a prothrombotic platelet phenotype with features matching cell death.

Does atrial fibrillation affect prognosis in hospitalised COVID-19 patients? A multicentre historical cohort study in the Netherlands.

OBJECTIVES: The aim of this multicentre COVID-PREDICT study (a nationwide observational cohort study that aims to better understand clinical course of COVID-19 and to predict which COVID-19 patients should receive which treatment and which type of care) was to determine the association between atrial fibrillation (AF) and mortality, intensive care unit (ICU) admission, complications and discharge destination in hospitalised COVID-19 patients. SETTING: Data from a historical cohort study in eight hospitals (both academic and non-academic) in the Netherlands between January 2020 and July 2021 were used in this study. PARTICIPANTS: 3064 hospitalised COVID-19 patients >18 years old. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the incidence of new-onset AF during hospitalisation. Secondary outcomes were the association between new-onset AF (vs prevalent or non-AF) and mortality, ICU admissions, complications and discharge destination, performed by univariable and multivariable logistic regression analyses. RESULTS: Of the 3064 included patients (60.6% men, median age: 65 years, IQR 55-75 years), 72 (2.3%) patients had prevalent AF and 164 (5.4%) patients developed new-onset AF during hospitalisation. Compared with patients without AF, patients with new-onset AF had a higher incidence of death (adjusted OR (aOR) 1.71, 95% CI 1.17 to 2.59) an ICU admission (aOR 5.45, 95% CI 3.90 to 7.61). Mortality was non-significantly different between patients with prevalent AF and those with new-onset AF (aOR 0.97, 95% CI 0.53 to 1.76). However, new-onset AF was associated with a higher incidence of ICU admission and complications compared with prevalent AF (OR 6.34, 95% CI 2.95 to 13.63, OR 3.04, 95% CI 1.67 to 5.55, respectively). CONCLUSION: New-onset AF was associated with an increased incidence of death, ICU admission, complications and a lower chance to be discharged home. These effects were far less pronounced in patients with prevalent AF. Therefore, new-onset AF seems to represent a marker of disease severity, rather than a cause of adverse outcomes.

What is the aetiology of dysnatraemia in COVID-19 and how is this related to outcomes in patients admitted during earlier and later COVID-19 waves? A multicentre, retrospective observational study in 11 Dutch hospitals.

OBJECTIVES: To evaluate the relationship among dysnatraemia at hospital presentation and duration of admission, risk of intensive care unit (ICU) admission and all-cause mortality and to assess the underlying pathophysiological mechanism of hyponatraemia in patients with COVID-19. Our hypothesis is that both hyponatraemia and hypernatraemia at presentation are associated with adverse outcomes. DESIGN: Observational study. SETTING: Secondary care; 11 Dutch hospitals (2 university and 9 general hospitals). PARTICIPANTS: An analysis was performed within the retrospective multicentre cohort study COVIDPredict. 7811 patients were included (60% men, 40% women) between 24 February 2020 and 9 August 2022. Patients who were ≥18 years with PCR-confirmed COVID-19 or CT with COVID-19 reporting and data system score≥4 and alternative diagnosis were included. Patients were excluded when serum sodium levels at presentation were not registered in the database or when they had been transferred from another participating hospital. OUTCOME MEASURES: We studied demographics, medical history, symptoms and outcomes. Patients were stratified according to serum sodium concentration and urinary sodium excretion. RESULTS: Hyponatraemia was present in 2677 (34.2%) patients and hypernatraemia in 126 (1.6%) patients. Patients with hyponatraemia presented more frequently with diarrhoea, lower blood pressure and tachycardia. Hyponatraemia was, despite a higher risk for ICU admission (OR 1.27 (1.11-1.46; p<0.001)), not associated with mortality or the risk for intubation. Patients with hypernatraemia had higher mortality rates (OR 2.25 (1.49-3.41; p<0.001)) and were at risk for ICU admission (OR 2.89 (1.83-4.58)) and intubation (OR 2.95 (1.83-4.74)). CONCLUSIONS: Hypernatraemia at presentation was associated with adverse outcomes in patients with COVID-19. Hypovolaemic hyponatraemia was found to be the most common aetiology of hyponatraemia. Hyponatraemia of unknown aetiology was associated with a higher risk for ICU admission and intubation and longer duration of admission.

Thrombocytopenia is associated with a dysregulated host response in severe COVID-19.

BACKGROUND: Thrombocytopenia is associated with increased mortality in COVID-19 patients. OBJECTIVE: To determine the association between thrombocytopenia and alterations in host response pathways implicated in disease pathogenesis in patients with severe COVID-19. PATIENTS/METHODS: We studied COVID-19 patients admitted to a general hospital ward included in a national (CovidPredict) cohort derived from 13 hospitals in the Netherlands. In a subgroup, 43 host response biomarkers providing insight in aberrations in distinct pathophysiological domains (coagulation and endothelial cell function; inflammation and damage; cytokines and chemokines) were determined in plasma obtained at a single time point within 48 h after admission. Patients were stratified in those with normal platelet counts (150-400 × 109/L) and those with thrombocytopenia (<150 × 109/L). RESULTS: 6.864 patients were enrolled in the national cohort, of whom 1.348 had thrombocytopenia and 5.516 had normal platelets counts; the biomarker cohort consisted of 429 patients, of whom 85 with thrombocytopenia and 344 with normal platelet counts. Plasma D-dimer levels were not different in thrombocytopenia, although patients with moderate-severe thrombocytopenia (<100 × 109/L) showed higher D-dimer levels, indicating enhanced coagulation activation. Patients with thrombocytopenia had lower plasma levels of many proinflammatory cytokines and chemokines, and antiviral mediators, suggesting involvement of platelets in inflammation and antiviral immunity. Thrombocytopenia was associated with alterations in endothelial cell biomarkers indicative of enhanced activation and a relatively preserved glycocalyx integrity. CONCLUSION: Thrombocytopenia in hospitalized patients with severe COVID-19 is associated with broad host response changes across several pathophysiological domains. These results suggest a role of platelets in the immune response during severe COVID-19.

Age-related changes in plasma biomarkers and their association with mortality in COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19)-induced mortality occurs predominantly in older patients. Several immunomodulating therapies seem less beneficial in these patients. The biological substrate behind these observations is unknown. The aim of this study was to obtain insight into the association between ageing, the host response and mortality in patients with COVID-19. METHODS: We determined 43 biomarkers reflective of alterations in four pathophysiological domains: endothelial cell and coagulation activation, inflammation and organ damage, and cytokine and chemokine release. We used mediation analysis to associate ageing-driven alterations in the host response with 30-day mortality. Biomarkers associated with both ageing and mortality were validated in an intensive care unit and external cohort. RESULTS: 464 general ward patients with COVID-19 were stratified according to age decades. Increasing age was an independent risk factor for 30-day mortality. Ageing was associated with alterations in each of the host response domains, characterised by greater activation of the endothelium and coagulation system and stronger elevation of inflammation and organ damage markers, which was independent of an increase in age-related comorbidities. Soluble tumour necrosis factor receptor 1, soluble triggering receptor expressed on myeloid cells 1 and soluble thrombomodulin showed the strongest correlation with ageing and explained part of the ageing-driven increase in 30-day mortality (proportion mediated: 13.0%, 12.9% and 12.6%, respectively). CONCLUSIONS: Ageing is associated with a strong and broad modification of the host response to COVID-19, and specific immune changes likely contribute to increased mortality in older patients. These results may provide insight into potential age-specific immunomodulatory targets in COVID-19.

Ethnic Differences in Coronavirus Disease 2019 Hospitalization and Hospital Outcomes in a Multiethnic Population in the Netherlands.

Background: Evidence from the United States and United Kingdom suggests that ethnic minority populations are at an increased risk for developing severe coronavirus disease 2019 (COVID-19); however, data from other West-European countries are scarce. Methods: We analyzed data from 1439 patients admitted between February 2020 and January 2021 to 4 main hospitals in Amsterdam and Almere, the Netherlands. Differences in the risk for hospitalization were assessed by comparing demographics to the general population. Using a population-based cohort as reference, we determined differences in the association between comorbidities and COVID-19 hospitalization. Outcomes after hospitalization were analyzed using Cox regression. Results: The hospitalization risk was higher in all ethnic minority groups than in those of Dutch origin, with age-adjusted odds ratios ranging from 2.2 (95% confidence interval [CI], 1.7-2.6) in Moroccans to 4.5 (95% CI, 3.2-6.0) in Ghanaians. Hypertension and diabetes were similarly associated with COVID-19 hospitalization. For all other comorbidities, we found differential associations. Intensive care unit admission and mortality during 21-day follow-up after hospitalization was comparable between ethnicities. Conclusions: The risk of COVID-19 hospitalization was higher in all ethnic minority groups compared to the Dutch, but the risk of adverse outcomes after hospitalization was similar. Our results suggest that these inequalities may in part be attributable to comorbidities that can be prevented by targeted public health prevention measures. More work is needed to gain insight into the role of other potential factors such as social determinants of health, which might have contributed to the ethnic inequalities in COVID-19 hospitalization.

The Platelet Lipidome Is Altered in Patients with COVID-19 and Correlates with Platelet Reactivity.

BACKGROUND: Activated platelets have been implicated in the proinflammatory and prothrombotic phenotype of coronavirus disease 2019 (COVID-19). While it is increasingly recognized that lipids have important structural and signaling roles in platelets, the lipidomic landscape of platelets during infection has remained unexplored. OBJECTIVE: To investigate the platelet lipidome of patients hospitalized for COVID-19. METHODS: We performed untargeted lipidomics in platelets of 25 patients hospitalized for COVID-19 and 23 noninfectious controls with similar age and sex characteristics, and with comparable comorbidities. RESULTS: Twenty-five percent of the 1,650 annotated lipids were significantly different between the groups. The significantly altered part of the platelet lipidome mostly comprised lipids that were less abundant in patients with COVID-19 (20.4% down, 4.6% up, 75% unchanged). Platelets from COVID-19 patients showed decreased levels of membrane plasmalogens, and a distinct decrease of long-chain, unsaturated triacylglycerols. Conversely, platelets from patients with COVID-19 displayed class-wide higher abundances of bis(monoacylglycero)phosphate and its biosynthetic precursor lysophosphatidylglycerol. Levels of these classes positively correlated with ex vivo platelet reactivity-as measured by P-selectin expression after PAR1 activation-irrespective of disease state. CONCLUSION: Taken together, this investigation provides the first exploration of the profound impact of infection on the human platelet lipidome, and reveals associations between the lipid composition of platelets and their reactivity. These results warrant further lipidomic research in other infections and disease states involving platelet pathophysiology.

The host response in different aetiologies of community-acquired pneumonia.

BACKGROUND: Community-acquired pneumonia (CAP) can be caused by a variety of pathogens, of which Streptococcus pneumoniae, Influenza and currently SARS-CoV-2 are the most common. We sought to identify shared and pathogen-specific host response features by directly comparing different aetiologies of CAP. METHODS: We measured 72 plasma biomarkers in a cohort of 265 patients hospitalized for CAP, all sampled within 48 hours of admission, and 28 age-and sex matched non-infectious controls. We stratified the biomarkers into several pathophysiological domains- antiviral response, vascular response and function, coagulation, systemic inflammation, and immune checkpoint markers. We directly compared CAP caused by SARS-CoV-2 (COVID-19, n=39), Streptococcus pneumoniae (CAP-strep, n=27), Influenza (CAP-flu, n=22) and other or unknown pathogens (CAP-other, n=177). We adjusted the comparisons for age, sex and disease severity scores. FINDINGS: Biomarkers reflective of a stronger cell-mediated antiviral response clearly separated COVID-19 from other CAPs (most notably granzyme B). Biomarkers reflecting activation and function of the vasculature showed endothelial barrier integrity was least affected in COVID-19, while glycocalyx degradation and angiogenesis were enhanced relative to other CAPs. Notably, markers of coagulation activation, including D-dimer, were not different between the CAP groups. Ferritin was most increased in COVID-19, while other systemic inflammation biomarkers such as IL-6 and procalcitonin were highest in CAP-strep. Immune checkpoint markers showed distinctive patterns in viral and non-viral CAP, with highly elevated levels of Galectin-9 in COVID-19. INTERPRETATION: Our investigation provides insight into shared and distinct pathophysiological mechanisms in different aetiologies of CAP, which may help guide new pathogen-specific therapeutic strategies. FUNDING: This study was financially supported by the Dutch Research Council, the European Commission and the Netherlands Organization for Health Research and Development.

Association between dexamethasone treatment and the host response in COVID-19 patients admitted to the general ward.

Dexamethasone improves clinical outcomes in COVID-19 patients requiring supplementary oxygen. We investigated possible mechanisms of action by comparing sixteen plasma host response biomarkers in general ward patients before and after implementation of dexamethasone as standard of care. 48 patients without and 126 patients with dexamethasone treatment were sampled within 48 h of admission. Endothelial cell and coagulation activation biomarkers were comparable. Dexamethasone treatment was associated with lower plasma interleukin (IL)-6 and IL-1 receptor antagonist levels, whilst other inflammation parameters were not affected. These data argue against modification of vascular-procoagulant responses as an early mechanism of action of dexamethasone in COVID-19.

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.

Early warning scores to assess the probability of critical illness in patients with COVID-19.

OBJECTIVE: Validated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current study was to evaluate the performance of early warning scores (EWS) in the ED when identifying patients with COVID-19 who will require intensive care unit (ICU) admission for high-flow-oxygen usage or mechanical ventilation. METHODS: Patients with a proven SARS-CoV-2 infection with complete resuscitate orders treated in nine hospitals between 27 February and 30 July 2020 needing hospital admission were included. Primary outcome was the performance of EWS in identifying patients needing ICU admission within 24 hours after ED presentation. RESULTS: In total, 1501 patients were included. Median age was 71 (range 19-99) years and 60.3% were male. Of all patients, 86.9% were admitted to the general ward and 13.1% to the ICU within 24 hours after ED admission. ICU patients had lower peripheral oxygen saturation (86.7% vs 93.7, p≤0.001) and had a higher body mass index (29.2 vs 27.9 p=0.043) compared with non-ICU patients. National Early Warning Score 2 (NEWS2) ≥ 6 and q-COVID Score were superior to all other studied clinical risk scores in predicting ICU admission with a fair area under the receiver operating characteristics curve of 0.740 (95% CI 0.696 to 0.783) and 0.760 (95% CI 0.712 to 0.800), respectively. NEWS2 ≥6 and q-COVID Score ≥3 discriminated patients admitted to the ICU with a sensitivity of 78.1% and 75.9%, and specificity of 56.3% and 61.8%, respectively. CONCLUSION: In this multicentre study, the best performing models to predict ICU admittance were the NEWS2 and the Quick COVID-19 Severity Index Score, with fair diagnostic performance. However, due to the moderate performance, these models cannot be clinically used to adequately predict the need for ICU admission within 24 hours in patients with SARS-CoV-2 infection presenting at the ED.

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.

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.

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.

[Clinical course of COVID-19 in the Netherlands: an overview of 2607 patients in hospital during the first wave]. / Klinisch beloop van covid-19 in Nederland.

OBJECTIVE: To systematically collect clinical data from patients with a proven COVID-19 infection in the Netherlands. DESIGN: Data from 2579 patients with COVID-19 admitted to 10 Dutch centers in the period February to July 2020 are described. The clinical data are based on the WHO COVID case record form (CRF) and supplemented with patient characteristics of which recently an association disease severity has been reported. METHODS: Survival analyses were performed as primary statistical analysis. These Kaplan-Meier curves for time to (early) death (3 weeks) have been determined for pre-morbid patient characteristics and clinical, radiological and laboratory data at hospital admission. RESULTS: Total in-hospital mortality after 3 weeks was 22.2% (95% CI: 20.7% - 23.9%), hospital mortality within 21 days was significantly higher for elderly patients (> 70 years; 35, 0% (95% CI: 32.4% - 37.8%) and patients who died during the 21 days and were admitted to the intensive care (36.5% (95% CI: 32.1% - 41.3%)). Apart from that, in this Dutch population we also see a risk of early death in patients with co-morbidities (such as chronic neurological, nephrological and cardiac disorders and hypertension), and in patients with more home medication and / or with increased urea and creatinine levels. CONCLUSION: Early death due to a COVID-19 infection in the Netherlands appears to be associated with demographic variables (e.g. age), comorbidity (e.g. cardiovascular disease) but also disease char-acteristics at admission.