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1.
Front Endocrinol (Lausanne) ; 12: 747732, 2021.
Article in English | MEDLINE | ID: covidwho-1598924

ABSTRACT

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.


Subject(s)
Acute Kidney Injury/complications , COVID-19/mortality , Hospital Mortality , Hospitalization , Obesity/complications , Respiratory Distress Syndrome/complications , Aged , Female , Humans , Intensive Care Units , Length of Stay , Male , Middle Aged , Patient Discharge , Respiration, Artificial , Retrospective Studies , Treatment Outcome
2.
Int J Environ Res Public Health ; 18(17)2021 09 02.
Article in English | MEDLINE | ID: covidwho-1390632

ABSTRACT

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.


Subject(s)
COVID-19 , Triage , Aged , Emergency Service, Hospital , Humans , Retrospective Studies , SARS-CoV-2
3.
BMJ Open ; 11(7): e047347, 2021 07 19.
Article in English | MEDLINE | ID: covidwho-1318029

ABSTRACT

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.


Subject(s)
COVID-19 , Cohort Studies , Humans , Logistic Models , Retrospective Studies , SARS-CoV-2
4.
Am J Emerg Med ; 49: 76-79, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-1240142

ABSTRACT

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.


Subject(s)
COVID-19/diagnosis , Clinical Deterioration , Shock/classification , Triage , Adult , Aged , Aged, 80 and over , COVID-19/mortality , Emergency Service, Hospital/statistics & numerical data , Female , Hospital Mortality/trends , Humans , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Netherlands , Organ Dysfunction Scores , ROC Curve , Retrospective Studies , Risk Assessment , Shock/mortality , Young Adult
5.
PLoS One ; 16(4): e0249920, 2021.
Article in English | MEDLINE | ID: covidwho-1186609

ABSTRACT

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.


Subject(s)
COVID-19/mortality , Age Factors , Aged , Aged, 80 and over , Belgium/epidemiology , COVID-19/diagnosis , COVID-19/epidemiology , Cohort Studies , Communicable Disease Control , Comorbidity , Electronic Health Records , Female , Hospitalization , Humans , Male , Middle Aged , Netherlands/epidemiology , Prognosis , Risk Assessment , Risk Factors , SARS-CoV-2/isolation & purification
6.
Age Ageing ; 50(3): 631-640, 2021 05 05.
Article in English | MEDLINE | ID: covidwho-1054261

ABSTRACT

BACKGROUND: During the first wave of the coronavirus disease 2019 (COVID-19) pandemic, older patients had an increased risk of hospitalisation and death. Reports on the association of frailty with poor outcome have been conflicting. OBJECTIVE: The aim of the present study was to investigate the independent association between frailty and in-hospital mortality in older hospitalised COVID-19 patients in the Netherlands. METHODS: This was a multicentre retrospective cohort study in 15 hospitals in the Netherlands, including all patients aged ≥70 years, who were hospitalised with clinically confirmed COVID-19 between February and May 2020. Data were collected on demographics, co-morbidity, disease severity and Clinical Frailty Scale (CFS). Primary outcome was in-hospital mortality. RESULTS: A total of 1,376 patients were included (median age 78 years (interquartile range 74-84), 60% male). In total, 499 (38%) patients died during hospital admission. Parameters indicating presence of frailty (CFS 6-9) were associated with more co-morbidities, shorter symptom duration upon presentation (median 4 versus 7 days), lower oxygen demand and lower levels of C-reactive protein. In multivariable analyses, the CFS was independently associated with in-hospital mortality: compared with patients with CFS 1-3, patients with CFS 4-5 had a two times higher risk (odds ratio (OR) 2.0 (95% confidence interval (CI) 1.3-3.0)) and patients with CFS 6-9 had a three times higher risk of in-hospital mortality (OR 2.8 (95% CI 1.8-4.3)). CONCLUSIONS: The in-hospital mortality of older hospitalised COVID-19 patients in the Netherlands was 38%. Frailty was independently associated with higher in-hospital mortality, even though COVID-19 patients with frailty presented earlier to the hospital with less severe symptoms.


Subject(s)
COVID-19/mortality , Frail Elderly/statistics & numerical data , Frailty/complications , Hospitalization/statistics & numerical data , Pandemics/statistics & numerical data , Aged , Aged, 80 and over , Female , Frailty/diagnosis , Hospital Mortality , Humans , Male , Netherlands/epidemiology , Retrospective Studies , SARS-CoV-2
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