scholarly journals Heterogeneity in COVID-19 patient volume, characteristics and outcomes across US Department of Veterans Affairs facilities: an observational cohort study

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e044646
Author(s):  
Dawn M Bravata ◽  
Laura J Myers ◽  
Anthony J Perkins ◽  
Salomeh Keyhani ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Cohort Study ◽  
Hospital Admissions ◽  
Patient Characteristics ◽  
Observational Cohort Study ◽  
Veterans Health ◽  
Patient Volume ◽  
Health Administration ◽  
Observational Cohort ◽  
Volume Characteristics

ObjectiveStudies describe COVID-19 patient characteristics and outcomes across populations, but reports of variation across healthcare facilities are lacking. The objectives were to examine differences in COVID-19 patient volume and mortality across facilities, and understand whether facility variation in mortality was due primarily to differences in patient versus facility characteristics.DesignObservational cohort study with multilevel mixed effects logistic regression modelling.SettingThe Veterans Health Administration (VA) is the largest healthcare system in the USA.ParticipantsPatients with COVID-19.Main outcomeAll-cause mortality within 45 days after COVID-19 testing (March–May, follow-up through 16 July 2020).ResultsAmong 13 510 patients with COVID-19, 3942 (29.2%) were admitted (2266/3942 (57.5%) ward; 1676/3942 (42.5%) intensive care unit (ICU)) and 679/3942 (17.2%) received mechanical ventilation. Marked heterogeneity was observed across facilities in median age (range: 34.3–83.9 years; facility mean: 64.7, SD 7.2 years); patient volume (range: 1–737 at 160 facilities; facility median: 48.5, IQR 14–105.5); hospital admissions (range: 1–286 at 133 facilities; facility median: 11, IQR 1–26.5); ICU caseload (range: 1–85 at 115 facilities; facility median: 4, IQR 0–12); and mechanical ventilation (range: 1–53 at 90 facilities; facility median: 1, IQR 0–5). Heterogeneity was also observed in facility mortality for all patients with COVID-19 (range: 0%–29.7%; facility median: 8.9%, IQR 2.4%–13.7%); inpatients (range: 0%–100%; facility median: 18.0%, IQR 5.6%–28.6%); ICU patients (range: 0%–100%; facility median: 28.6%, IQR 14.3%–50.0%); and mechanical ventilator patients (range: 0%–100%; facility median: 52.7%, IQR 33.3%–80.6%). The majority of variation in facility mortality was attributable to differences in patient characteristics (eg, age).ConclusionsMarked heterogeneity in COVID-19 patient volume, characteristics and mortality were observed across VA facilities nationwide. Differences in patient characteristics accounted for the majority of explained variation in mortality across sites. Variation in unadjusted COVID-19 mortality across facilities or nations should be considered with caution.

Peripheral muscular ultrasound as outcome assessment tool in critically ill patients on mechanical ventilation: An observational cohort study

2021 ◽  
Author(s):  
Diogo Oliveira Toledo ◽  
Branca Jardini de Freitas ◽  
Rogério Dib ◽  
Flavia Julie do Amaral Pfeilsticker ◽  
Dyaiane Marques dos Santos ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Cohort Study ◽  
Outcome Assessment ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Assessment Tool ◽  
Observational Cohort Study ◽  
Observational Cohort

scholarly journals Serum potassium disorders predict subsequent kidney injury: a retrospective observational cohort study of hospitalized patients

2022 ◽  
Author(s):  
Gianmarco Lombardi ◽  
Giovanni Gambaro ◽  
Pietro Manuel Ferraro
Keyword(s):  
Cohort Study ◽  
Serum Potassium ◽  
Hospital Admissions ◽  
Kidney Injury ◽  
Observational Cohort Study ◽  
Hospitalized Patients ◽  
P Value ◽  
Significant Difference ◽  
Observational Cohort ◽  
Retrospective Observational Cohort Study

Introduction Electrolytes disorders are common findings in kidney diseases and might represent a useful biomarker preceding kidney injury. Serum potassium [K+] imbalance is still poorly investigated for association with acute kidney injury (AKI) and most evidence come from intensive care units (ICU). The aim of our study was to comprehensively investigate this association in a large, unselected cohort of hospitalized patients. Methods: We performed a retrospective observational cohort study on the inpatient population admitted to Fondazione Policlinico Universitario A. Gemelli IRCCS between January 1, 2010 and December 31, 2014 with inclusion of adult patients with at least 2 [K+] and 3 serum creatinine (sCr) measurements who did not develop AKI during an initial 10-day window. The outcome of interest was in-hospital AKI. The exposures of interest were [K+] fluctuations and hypo (HoK) and hyperkalemia (HerK). [K+] variability was evaluated using the coefficient of variation (CV). Cox proportional hazards regression models were used to obtain hazard ratios (HRs) and 95% confidence intervals (CIs) of the association between the exposures of interest and development of AKI. Results: 21,830 hospital admissions from 18,836 patients were included in our study. During a median follow-up of 5 (interquartile range [IQR] 7) days, AKI was observed in 555 hospital admissions (2.9%); median time for AKI development was 5 (IQR 7) days. Higher [K+] variability was independently associated with increased risk of AKI with a statistically significant linear trend across groups (p-value = 0.012). A significantly higher incidence of AKI was documented in patients with HerK compared with normokalemia. No statistically significant difference was observed between HoK and HerK (p-value = 0.92). Conclusion: [K+] abnormalities including fluctuations even within the normal range are associated with development of AKI.

scholarly journals Obesity and smoking as risk factors for invasive mechanical ventilation in COVID-19: A retrospective, observational cohort study

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0238552
Author(s):  
Ana C. Monteiro ◽  
Rajat Suri ◽  
Iheanacho O. Emeruwa ◽  
Robert J. Stretch ◽  
Roxana Y. Cortes-Lopez ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Cohort Study ◽  
Smoking Status ◽  
Univariate Analysis ◽  
Invasive Mechanical Ventilation ◽  
Multivariable Analysis ◽  
Observational Cohort Study ◽  
Smoking History ◽  
Observational Cohort ◽  
Retrospective Observational Cohort Study

Purpose To describe the trajectory of respiratory failure in COVID-19 and explore factors associated with risk of invasive mechanical ventilation (IMV). Materials and methods A retrospective, observational cohort study of 112 inpatient adults diagnosed with COVID-19 between March 12 and April 16, 2020. Data were manually extracted from electronic medical records. Multivariable and Univariable regression were used to evaluate association between baseline characteristics, initial serum markers and the outcome of IMV. Results Our cohort had median age of 61 (IQR 45–74) and was 66% male. In-hospital mortality was 6% (7/112). ICU mortality was 12.8% (6/47), and 18% (5/28) for those requiring IMV. Obesity (OR 5.82, CI 1.74–19.48), former (OR 8.06, CI 1.51–43.06) and current smoking status (OR 10.33, CI 1.43–74.67) were associated with IMV after adjusting for age, sex, and high prevalence comorbidities by multivariable analysis. Initial absolute lymphocyte count (OR 0.33, CI 0.11–0.96), procalcitonin (OR 1.27, CI 1.02–1.57), IL-6 (OR 1.17, CI 1.03–1.33), ferritin (OR 1.05, CI 1.005–1.11), LDH (OR 1.57, 95% CI 1.13–2.17) and CRP (OR 1.13, CI 1.06–1.21), were associated with IMV by univariate analysis. Conclusions Obesity, smoking history, and elevated inflammatory markers were associated with increased need for IMV in patients with COVID-19.

scholarly journals Valproate v. lithium in the treatment of bipolar disorder in clinical practice: observational nationwide register-based cohort study

2011 ◽  
Vol 199 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Lars Vedel Kessing ◽  
Gunnar Hellmund ◽  
John R. Geddes ◽  
Guy M. Goodwin ◽  
Per Kragh Andersen
Keyword(s):  
Bipolar Disorder ◽  
Cohort Study ◽  
Clinical Practice ◽  
Hospital Admission ◽  
Psychiatric Hospital ◽  
Hospital Admissions ◽  
Observational Cohort Study ◽  
Hazard Ratio ◽  
Daily Clinical Practice ◽  
Observational Cohort

BackgroundValproate is one of the most used mood stabilisers for bipolar disorder, although the evidence for the effectiveness of valproate is sparse.AimsTo compare the effect of valproate v. lithium for treatment of bipolar disorder in clinical practice.MethodAn observational cohort study with linkage of nationwide registers of all people with a diagnosis of bipolar disorder in psychiatric hospital settings who were prescribed valproate or lithium in Denmark during a period from 1995 to 2006.ResultsA total of 4268 participants were included among whom 719 received valproate and 3549 received lithium subsequent to the diagnosis of bipolar disorder. The rate of switch/add on to the opposite drug (lithium or valproate), antidepressants, antipsychotics or anticonvulsants (other than valproate) was increased for valproate compared with lithium (hazard ratio (HR) = 1.86, 95% CI 1.59–2.16). The rate of psychiatric hospital admissions was increased for valproate v. lithium (HR = 1.33, 95% CI 1.18–1.48) and regardless of the type of episode leading to a hospital admission (depressive or manic/mixed). Similarly, for participants with a depressive index episode (HR = 1.87, 95% CI 1.40–2.48), a manic index episode (HR = 1.24, 95% CI 1.01–1.51) and a mixed index episode (HR = 1.44, 95% CI 1.04–2.01), the overall rate of hospital admissions was significantly increased for valproate compared with lithium.ConclusionsIn daily clinical practice, treatment with lithium seems in general to be superior to treatment with valproate.

Prolonged mechanical ventilation in patients with terminated status epilepticus and outcome: An observational cohort study

Epilepsia ◽  
2021 ◽  
Author(s):  
Sira M. Baumann ◽  
Saskia Semmlack ◽  
Anja Rybitschka ◽  
Paulina S. C. Kliem ◽  
Gian Marco De Marchis ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Cohort Study ◽  
Status Epilepticus ◽  
Prolonged Mechanical Ventilation ◽  
Observational Cohort Study ◽  
Observational Cohort
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