scholarly journals The increased mortality associated with a weekend emergency admission is due to increased illness severity and altered case-mix

2011 ◽  
Vol 10 (4) ◽  
Author(s):  
Olga Mikulich ◽  
◽  
Elizabeth Callaly ◽  
Kathleen Bennett ◽  
Deirdre O’Riordan ◽  
...  

Background: A weekend emergency medical admission has been associated with a higher mortality. We have examined all weekend admissions to St James’ Hospital, Dublin between 2002 and 2009. Methods: We divided admissions by weekday or weekend (Saturday or Sunday) presentation. We utilised a multivariate logistic model, to determine whether a weekend admission was independently predictive of 30 day outcome. Results: There were 49337 episodes recorded in 25883 patients; 30-day inhospital mortality at the weekend (9.9% vs. 9.0%) had an unadjusted Odds Ratio of 1.11 (95% CI 0.99, 1.23: p=0.057). In the full risk (unlike the univariate) model, a weekend admission was not independently predictive (OR 1.05; 95% CI: 0.88, 1.24). The case-mix for a weekend admission differed; with more neurological diagnoses (22.8% vs 20.4% : p = 0.001) and less gastrointestinal disease (18.3% vs 21.1% : p = 0.001). A biochemistry only illness severity score predicted a higher mortality for weekend admissions. Conclusion: Patients admitted at the weekend had an approximate 11% increased 30-day in-hospital mortality, compared with a weekday admission. However, admission at the weekend was not independently predictive in a risk model that included Illness Severity (age and biochemical markers) and co-morbidity. Sicker patients, with a worse outcome, are admitted over the weekend; these considerations should inform the allocation of healthcare resources.

Author(s):  
Michelle M.J. Nassal ◽  
Dylan Nichols ◽  
Stephanie Demasi ◽  
Jon C. Rittenberger ◽  
Ashish R. Panchal ◽  
...  

Neurology ◽  
1984 ◽  
Vol 34 (10) ◽  
pp. 1343-1343 ◽  
Author(s):  
M. R. Mickey ◽  
G. W. Ellison ◽  
L. W. Myers

2020 ◽  
Vol 19 (3) ◽  
pp. 138-144
Author(s):  
Richard Conway ◽  
◽  
Declan Byrne ◽  
Deirdre O’Riordan ◽  
Bernard Silke ◽  
...  

Background: Accurate efficient prognostication in acute medical admissions remains challenging.Methods: We constructed a Vital Sign based Risk Calculator using vital parameters and Major Disease Categories to predict 30-day in-hospital mortality using a multivariable fractional polynomial model. Results: We evaluated 113,807 admissions in 58,126 patients. The Vital Sign based Risk Calculator predicted 30-day inhospital mortality to increase from 2 points – 3.6% (95%CI 3.4, 3.7) to 12 points – 14.8% (95%CI 14.0, 15.7). AUROC was 0.74 (95%CI 0.72, 0.74). The addition of illness severity and comorbidity data improved AUROC to 0.90 (95%CI 0.89, 0.90). Conclusion: The Vital Sign based Risk Calculator is limited by its simplicity; inclusion of illness severity and comorbidity data improve prediction.


2020 ◽  
Author(s):  
Hongwei Ji ◽  
Natalie Achamallah ◽  
Nancy Sun ◽  
Patrick Botting ◽  
Peter Chen ◽  
...  

Abstract Background Multiple reports have highlighted important racial and ethnic differences in the degree to which Americans may be vulnerable to severe forms of Covid-19 illness. Whether or not racial or ethnic disparities are related to variations in the underlying burden of comorbidities or other predisposing factors remains unclear.Methods We identified patients diagnosed with Covid-19, based on a positive PCR for SARS-CoV-2, from the electronic health record of a large multi-hospital system located in Southern California. We developed an illness severity score, based on the level of care each patient required (not admitted to the hospital; required hospital admission but never required intensive care; required intensive level care but never intubation; and, required intubation during hospitalization) and assessed for associations with clinical and demographic factors for each patient using ordinal logistic regression.Results A total of 571 patients with Covid-19 were identified a majority of whom were male (56%), with a mean age of 55±21 years. There were 81 (14%) patient who identified as African American, and 101 (18%) as Hispanic. A total of 202 (36%) patients required hospitalization without need for intensive care, 43 (8%) required intensive care without intubation, and 64 (11%) required intubation while also receiving intensive care. Of the total sample, African American race (OR 2.33, 95% CI 1.44-3.78, P=0.001) and Hispanic ethnicity (OR 1.97, 95% CI 1.14-3.12, P=0.004) were associated with greater illness severity.Conclusions Racial and ethnic disparities in the severity of Covid-19 illness persist, even when controlling for baseline comorbidities. It remains unclear if these differences are related to variations in physiologic response to SARS-CoV-2, differential timing of presentation or disparities in care.


Resuscitation ◽  
2015 ◽  
Vol 89 ◽  
pp. 86-92 ◽  
Author(s):  
Patrick J. Coppler ◽  
Jonathan Elmer ◽  
Luis Calderon ◽  
Alexa Sabedra ◽  
Ankur A. Doshi ◽  
...  

2014 ◽  
Vol 126 (1) ◽  
pp. 81-89 ◽  
Author(s):  
T. Pankhurst ◽  
D. Mani ◽  
D. Ray ◽  
S. Jham ◽  
R. Borrows ◽  
...  

2020 ◽  
Author(s):  
Annemarie B Docherty ◽  
Rachel H Mulholland ◽  
Nazir I Lone ◽  
Christopher P Cheyne ◽  
Daniela De Angelis ◽  
...  

AbstractBackgroundMortality rates of UK patients hospitalised with COVID-19 appeared to fall during the first wave. We quantify potential drivers of this change and identify groups of patients who remain at high risk of dying in hospital.MethodsThe International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) WHO Clinical Characterisation Protocol UK recruited a prospective cohort admitted to 247 acute UK hospitals with COVID-19 in the first wave (March to August 2020). Outcome was hospital mortality within 28 days of admission. We performed a three-way decomposition mediation analysis using natural effects models to explore associations between week of admission and hospital mortality adjusting for confounders (demographics, comorbidity, illness severity) and quantifying potential mediators (respiratory support and steroids).FindingsUnadjusted hospital mortality fell from 32.3% (95%CI 31.8, 32.7) in March/April to 16.4% (95%CI 15.0, 17.8) in June/July 2020. Reductions were seen in all ages, ethnicities, both sexes, and in comorbid and non-comorbid patients. After adjustment, there was a 19% reduction in the odds of mortality per 4 week period (OR 0.81, 95%CI 0.79, 0.83). 15.2% of this reduction was explained by greater disease severity and comorbidity earlier in the epidemic. The use of respiratory support changed with greater use of non-invasive ventilation (NIV). 22.2% (OR 0.94, 95%CI 0.94, 0.96) of the reduction in mortality was mediated by changes in respiratory support.InterpretationThe fall in hospital mortality in COVID-19 patients during the first wave in the UK was partly accounted for by changes in case mix and illness severity. A significant reduction was associated with differences in respiratory support and critical care use, which may partly reflect improved clinical decision making. The remaining improvement in mortality is not explained by these factors, and may relate to community behaviour on inoculum dose and hospital capacity strain.FundingNIHR & MRCKey points / Research in ContextEvidence before this studyRisk factors for mortality in patients hospitalised with COVID-19 have been established. However there is little literature regarding how mortality is changing over time, and potential explanations for why this might be. Understanding changes in mortality rates over time will help policy makers identify evolving risk, strategies to manage this and broader decisions about public health interventions.Added value of this studyMortality in hospitalised patients at the beginning of the first wave was extremely high. Patients who were admitted to hospital in March and early April were significantly more unwell at presentation than patients who were admitted in later months. Mortality fell in all ages, ethnic groups, both sexes and in patients with and without comorbidity, over and above contributions from falling illness severity. After adjustment for these variables, a fifth of the fall in mortality was explained by changes in the use of respiratory support and steroid treatment, along with associated changes in clinical decision-making relating to supportive interventions. However, mortality was persistently high in patients who required invasive mechanical ventilation, and in those patients who received non-invasive ventilation outside of critical care.Implications of all the available evidenceThe observed reduction in hospital mortality was greater than expected based on the changes seen in both case mix and illness severity. Some of this fall can be explained by changes in respiratory care, including clinical learning. In addition, introduction of community policies including wearing of masks, social distancing, shielding of vulnerable patients and the UK lockdown potentially resulted in people being exposed to less virus.The decrease in mortality varied depending on the level of respiratory support received. Patients receiving invasive mechanical ventilation have persistently high mortality rates, albeit with a changing case-mix, and further research should target this group.Severe COVID-19 disease has primarily affected older people in the UK. Many of these people, but not all have significant frailty. It is essential to ensure that patients and their families remain at the centre of decision-making, and we continue with an individualised approach to their treatment and care.


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