All Journals from Seán Cournane
Abstract
Background: Following an emergency medical admission, patients may be admitted an acute medical assessment unit (AMAU) or directly into a ward. An AMAU provides a structured environment for their initial assessment and treatment.
Methods: All emergency admissions (66,933 episodes in 36,271 patients) to an Irish hospital over an 12-year period (2002-2013) were studied with 30-day in-hospital mortality as the outcome measure. Univariate Odds Ratios, by initial patient allocation, and the fully adjusted Odds Ratios were calculated, using a validated logistic regression model.
Results: Patients, by design, were intended to be admitted initially to the AMAU (<= 5 day stay). Capacity constraints dictated that only 39.8% of patients were so admitted; the remainder bypassed the AMAU to a ward (60.2%). All patients remained under the care of the admitting consultant/team. We computed the risk profile for each group, using a multiple variable validated model of 30-day in-hospital mortality; the model indicated the same risk profile between these groups. The univariate OR of an in-hospital death by day 30 for a patient initially allocated to the AMAU, compared with an initial ward allocation was 0.76 (95% CI: 0.71, 0.82- p<0.001). The fully adjusted risk for patients was 0.67 (95% CI: 0.62, 0.73- p<0.001). Conclusion: Patients, with equivalent mortality risk, allocated initially to AMAU or a more traditional ward, appeared to have substantially different outcomes.
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Abstract
Background: There is concern that undue ED wait times may result in adverse outcomes.
Methods: We studied 30-day in-hospital mortality (2002-2017) for all medical admissions (106,586 episodes; 54,928 patients) focusing on clinical risk profile
Results: Comparing 2002-09 vs. 2010-17, median ED waits > 6 hours (hr) increased 10h (95% CI: 8,13) to 15h (95% CI: 9,19). 30-day mortality declined 6.2% to 4.9%- (RRR- 20.8%/ NNT- 78). 30-day-mortality by ED wait: - < 4hr 6.6% (95% CI: 6.3%, 6.9%), 4-8hr 4.8% (95% CI: 4.6%, 5.0%), 8-12hr 4.3% (95% CI: 4.1%, 4.5%) or >=12hr 4.2% (95% CI: 3.9%, 4.5%).
Conclusion: Admissions with shorter waits are overrepresented with high clinical acuity. Higher Risk Score patient with extended wait times had worse clinical outcomes.
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Abstract
Background: An Illness Severity and Co-morbidity composite score can predict 30-day mortality outcome.
Methods: We computed a summary risk score (RS) for emergency medical admissions and used cluster analysis to define four subsets
Results: Four cluster groups were defined. Cluster 1 – RS 7 points (IQR 5, 8) Cluster 2 - 9 (IQR 8, 11), Cluster 3 - 12 (IQR 11, 13) and Cluster 4 - 14 (IQR 13, 15). Clusters predicted 30-day in hospital mortality OR 1.86 (95%CI: 1.82, 1.92); respective rates 1.4% (95% CI: 1.3%, 1.6%), 3.4% (95% CI: 3.1%, 3.6%), 7.8% (95% CI: 7.5%, 8.1%) and 16.5% (95% CI: 15.7%, 17.2%).
Conclusion: Cluster grouping of Risk Score was age related; strongest outcome determinant was Acute Illness Severity
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Background: Areas of low socio-economic status (SES) have a disproportionate number of emergency medical admissions; we quantitate the profile of multi-morbidity related to SES.
Methods: We developed a logistic multiple variable regression model, based on over 15 years of hospital data, to examine the effect of socio-demography on hospital outcomes.
Results: Admissions from low SES cohort were a decade younger, and had a shorter hospital stay, and lower 30-day episode mortality outcome. The number of morbidities was equivalent between groups, but the more disadvantaged were more likely to have a respiratory diagnosis or diabetes.
Conclusion: Low SES emergency admissions present > 10 yr. earlier than the high SES population; their equivalent multimorbidity, despite a lower age, could reflect accelerated disease progression.
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Background: The prediction of clinical outcomes using biochemical markers is an important tool.
Methods: We calculated a risk score for all emergency admissions 2002-2017. We related potassium and mortality in a multivariable fractional polynomial model. We investigated the potassium distribution and relationship of potassium to mortality over time.
Results: There were 106,586 admissions in 54,928 patients. Mortality was higher for those with an admission potassium above the median – 6.1% vs 4.6% (p<0.001), OR 1.07 (95%CI: 1.06, 1.09). There was a progressive increase in mortality from the lowest – 8.9% (95%CI: 8.3%, 9.4%) to highest potassium decile – 14.2% (95%CI: 13.5%, 14.8%). The frequency of admission hypokalaemia and the mortality at any given potassium decreased over time. Conclusion: Admission potassium predicts mortality.
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