Relationship of the clinical acuity & complexity to the outcome of an emergency medical admission.

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.

COKE LIVe: recurrent vasculitis secondary to cocaine contaminated with levamisole.

Levamisole-induced vasculitis (LIV) is becoming an increasingly common entity secondary to both rising cocaine use in the UK and high levels of adulteration of cocaine with various contaminants. We report the first documented case of LIV secondary to adulterated cocaine in Ireland, which presented as a 6-year history of recurrent vasculitis of unknown aetiology. Classically, LIV is diagnosed by a combination of positive ANCA serology and agranulocytosis however, given the frequency of cocaine use, we urge acute physicians to consider the diagnosis in cases of typical retiform (angulated) purpura in association with a history of cocaine use.

The Relationship between Resource Utilization, Clinical Risk and Hospital Costs for Emergency Medical Admissions.

There has been little study of the relationship between resource utilisation, clinical risks and hospital costs in acute medicine with the question remaining as to whether current funding models reflect patient acuity. We examined the relationship between resource use for investigations/allied professional and patient episode costs in all emergency medical admissions admitted to our institution during 2008-2013. Univariate estimates were compared with a multivariate model adjusted for major cost predictors. Interestingly, the model adjusted cost estimates changed considerably when compared with univariate analysis. We used both linear and non-linear (quantile regression) methods due to the highly skewed nature of hospital costs. The data suggested that hospital episode costs were predictable and driven by objective measures of clinical complexity. The use of expensive investigations and healthcare professional time was secondary to the clinical acuity. Thus, cost was heavily weighted towards higher complexity, and lower resource utilisation associated with lower risk patient groups. However, the non-linear nature of the costings would caution against simple predictor models and non-linear techniques such as quantile regression may, as we have demonstrated, prove superior in defining the underlying relationships.

The Relationship Between Social Deprivation and a Weekend Emergency Medical Admission.

BACKGROUND: Deprivation increases admission rates; the specific effect of deprivation with regard to weekend admissions is unknown. METHODS: We calculated annual weekend admission rates for each small area population unit and related these to quintiles of Deprivation Index from 2002-2014. Univariate and multivariable risk estimates were calculated using truncated Poisson regression. RESULTS: There were 30,794 weekend admissions in 16,665 patients. The admission rate was substantially higher for more deprived areas, 12.7 per 1000 (95%CI 9.4, 14.7) vs 4.6 per 1000 (95%CI 3.3, 5.8). More deprived patients admitted at the weekend had a significantly lower 30-day in-hospital mortality (10.3% vs 14.5%, p<0.001). CONCLUSION: Deprivation is a powerful determinant of weekend admissions, however these comprise a group of patients with better outcomes.

Serum potassium levels as an outcome determinant in acute medical admissions.

The relationship between serum potassium levels and mortality in acute medical admissions is uncertain. In particular, the relevance of minor abnormalities in potassium level or variations within the normal range remains to be determined. We performed a retrospective cohort study of all emergency medical admissions to St James's Hospital (Dublin, Ireland) between 2002 and 2012. We used a stepwise logistic regression model to predict in-hospital mortality, adjusting risk estimates for major predictor variables. There were 67,585 admissions in 37,828 patients over 11 years. After removing long-stay patients, 60,864 admissions in 35,168 patients were included in the study. Hypokalaemia was present in 14.5% and hyperkalaemia in 4.9%. In-hospital mortality was 3.9, 5.0, and 18.1% in the normokalaemic, hypokalaemic and hyperkalaemic groups respectively. Hypokalaemic patients had a univariate odds ratio (OR) of 1.29 for in-hospital mortality (95% confidence interval (CI) 1.16-1.43; p<0.001). Hyperkalaemic patients had a univariate OR for in-hospital mortality of 5.2 (95% CI 4.7-5.7; p<0.001). The ORs for an in-hospital death for potassium between 4.3 and 4.7 mmol/l, and 4.7 and 5.2 mmol/l, were 1.73 (95% CI 1.51-1.99) and 2.97 (95% CI 2.53-3.50) respectively. Hyperkalaemia and hypokalaemia are associated with increased mortality.

Reduced 30-day in-hospital but increased long-term mortality for weekend vs weekday acute medical admission.

BACKGROUND: Acute medical admission at the weekend has been reported to be associated with increased mortality. We aimed to assess 30-day in-hospital mortality and subsequent follow-up of all community deaths following discharge for acute medical admission to our institution over 21 years. METHODS: We employed a database of all acute medical admissions to our institution over 21 years (2002-2023). We compared 30-day in-hospital mortality by weekend (Saturday/Sunday) or weekday (Tuesday/Wednesday) admission. Outcome post-discharge was determined from the National Death Register to December 2021. Predictors of 30-day in-hospital and long-term mortality were analysed by logistic regression or Cox proportional hazards models. RESULTS: The study population consisted of 109,232 admissions in 57,059 patients. A weekend admission was associated with a reduced 30-day in-hospital mortality, odds ratio (OR) 0.70 (95%CI 0.65, 0.76). Major predictors of 30-day in-hospital mortality were acute illness severity score (AISS) OR 6.9 (95%CI 5.5, 8.6) and comorbidity score OR 2.4 (95%CI 1.2, 4.6). At a median follow-up of 5.9 years post-discharge, 19.0% had died. The strongest long-term predictor of mortality was admission AISS OR 6.7 (95%CI 4.6, 9.9). The overall survival half-life after hospital discharge was 16.6 years. Survival was significantly worse for weekend admissions at 20.8 years compared to weekday admissions at 13.3 years. CONCLUSION: Weekend admission of acute medical patients is associated with reduced 30-day in-hospital mortality but reduced long-term survival.

Towards machine learning-based quantitative hyperspectral image guidance for brain tumor resection.

BACKGROUND: Complete resection of malignant gliomas is hampered by the difficulty in distinguishing tumor cells at the infiltration zone. Fluorescence guidance with 5-ALA assists in reaching this goal. Using hyperspectral imaging, previous work characterized five fluorophores' emission spectra in most human brain tumors. METHODS: In this paper, the effectiveness of these five spectra was explored for different tumor and tissue classification tasks in 184 patients (891 hyperspectral measurements) harboring low- (n = 30) and high-grade gliomas (n = 115), non-glial primary brain tumors (n = 19), radiation necrosis (n = 2), miscellaneous (n = 10) and metastases (n = 8). Four machine-learning models were trained to classify tumor type, grade, glioma margins, and IDH mutation. RESULTS: Using random forests and multilayer perceptrons, the classifiers achieve average test accuracies of 84-87%, 96.1%, 86%, and 91% respectively. All five fluorophore abundances vary between tumor margin types and tumor grades (p < 0.01). For tissue type, at least four of the five fluorophore abundances are significantly different (p < 0.01) between all classes. CONCLUSIONS: These results demonstrate the fluorophores' differing abundances in different tissue classes and the value of the five fluorophores as potential optical biomarkers, opening new opportunities for intraoperative classification systems in fluorescence-guided neurosurgery.

Complete surgical removal of some primary brain tumors is difficult because it can be hard to distinguish the edge of the tumor. We evaluated whether the edges of tumors and the tumor type and grade can be more accurately determined if the tumor is imaged using many different wavelengths of light. We used measurements taken from the tumors of people undergoing brain tumor surgery and developed machine-learning algorithms that could predict where the edge of the tumor was. The methods could also provide information about the type and grade of the brain tumor. These classifications could potentially be used during operations to remove brain tumors more accurately and thus improve the outcome of surgery for people with brain tumors.

Red Cell Distribution Width as a Prognostic Indicator in Acute Medical Admissions.

The red cell distribution width (RDW) is the coefficient of variation of the mean corpuscular volume (MCV). We sought to evaluate RDW as a predictor of outcomes following acute medical admission. We studied 10 years of acute medical admissions (2002-2011) with subsequent follow-up to 2021. RDW was converted to a categorical variable, Q1 < 12.9 fl, Q2-Q4 ≥ 12.9 and <15.7 fL and Q5 ≥ 15.7 fL. The predictive value of RDW for 30-day in-hospital and long-term mortality was evaluated with logistic and Cox regression modelling. Adjusted odds ratios (aORs) were calculated and loss of life years estimated. There were 62,184 admissions in 35,140 patients. The 30-day in-hospital mortality (n = 3646) occurred in 5.9% of admissions. An additional 15,086 (42.9%) deaths occurred by December 2021. Admission RDW independently predicted 30-day in-hospital mortality aOR 1.93 (95%CI 1.79, 2.07). Admission RDW independently predicted long-term mortality aOR 1.04 (95%CI 1.02, 1.05). Median survival post-admission was 189 months. For those with admission RDW in Q5, observed survival half-life was 133 months-this represents a shortfall of 5.7 life years (33.9%). In conclusion, admission RDW independently predicts 30-day in-hospital and long-term mortality.

Prognostic value and clinical utility of NT-proBNP in acute emergency medical admissions.

BACKGROUND: NT-proB-type natriuretic peptide (NT-proBNP) is a frequently utilized test in congestive cardiac failure. There is little data on its utility in unselected emergency medical admissions. AIM: This study aims to investigate the clinical utility and prognostic value of NT-proBNP in emergency medical admissions and to determine whether such testing influenced downstream investigations and length of stay (LOS). METHODS: We report on NT-proBNP tests performed in emergency medical admissions in a 2005/2006 and subsequent 7-year (2014-2020) retrospective cohort. We assessed 30-day in-hospital mortality with a multivariable logistic regression model. The utilization of procedures/services was related to LOS with zero-truncated Poisson regression. RESULTS: There were 64,212 admissions in 36,252 patients. Patients with a NT-proBNP test were significantly older at 75.3 years vs. 63.0 years and had longer LOS -9.4 days vs. 4.9 days. They had higher acute illness severity and comorbidity scores. Thirty-day in-hospital mortality was higher in those with a NT-proBNP test (8.8%) vs. no request (3.2%). NT-proBNP test level was prognostic in univariate - OR 2.87 (2.61, 3.15), and multivariate analyses - OR 1.40 (1.26, 1.56). Higher NT-proBNP levels predicted higher 30-day in-hospital mortality. Multivariable thirty-day in-hospital mortality was 3.8% (3.6%, 3.9%) for those without a test, increasing to 4.9% (4.7%, 5.2%) for ≥ 250 ng/L and 5.8% (5.8%, 6.3%) for ≥ 3000 ng/L. LOS was linearly related to the total number of procedures/services performed. CONCLUSION: NT-proBNP is prognostic in emergency medical admissions. Downstream resource utilization differed following an NT-proBNP test; this may reflect different case complexity or the 'uncertainty' surrounding such admissions.

Hospital mortality and length of stay differences in emergency medical admissions related to 'on-call' specialty.

BACKGROUND: The outcomes of acute medical admissions have been shown to be influenced by a variety of factors including system, patient, societal, and physician-specific differences. AIM: To evaluate the influence of on-call specialty on outcomes in acute medical admissions. METHODS: All acute medical admissions to our institution from 2015 to 2020 were evaluated. Admissions were grouped based on admitting specialty. Thirty-day in-hospital mortality and length of stay (LOS) were evaluated. Data was analysed using multivariable logistic regression and truncated Poisson regression modelling. RESULTS: There were 50,347 admissions in 30,228 patients. The majority of admissions were under Acute Medicine (47.0%), and major medical subspecialties (36.1%); Elderly Care admitted 12.1%. Acute Medicine admissions were older at 72.9 years (IQR 57.0, 82.9) vs. 67.2 years (IQR 50.1, 80.2), had higher Acute Illness Severity (grades 4-6: 85.9% vs. 81.3%; p < 0.001), Charlson Index (> group 0; 61.5% vs. 54.6%; p < 0.001), and Comorbidity Score (40.7% vs. 36.7%; p < 0.001). Over time, there was a small (+ 8%) but significant increase in 30-day in-hospital mortality. Mortality rates for Acute Medicine, major medical specialties, and Elderly Care were not different at 5.1% (95% CI: 4.7, 5.5), 4.7% (95% CI: 4.3, 5.1), and 4.7% (95% CI: 3.9, 5.4), respectively. Elderly Care admissions had shorter LOS (7.8 days (95% CI: 7.6, 8.0)) compared with either Acute Medicine (8.7 days (95% CI: 8.6, 8.8)) or major medical specialties (8.7 days (95% CI: 8.6, 8.9)). CONCLUSION: No difference in mortality and minor differences in LOS were observed. The prior pattern of improved outcomes year on year for emergency medical admissions appears ended.

Time-to-Event Analysis of Factors Influencing Delay in Discharge from a Subacute Complex Discharge Unit during the First Year of the Pandemic (2020) in an Irish Tertiary Centre Hospital.

Our study aimed to analyse delaying factors amongst patients with a length of stay (LOS) > 15 days during the COVID-19 pandemic using time-to-event analysis. A total of 390 patients were admitted between March 2020-February 2021 to the subacute complex discharge unit in St James's Hospital: 326 (83.6%) were >65 years of age and 233 (59.7%) were female. The median (IQR) age was 79 (70-86) years with a median (IQR) of 19.4 (10-41) days. A total of 237 (60.7%) events were uncensored, with LOS > 15 days, of which 138 (58.2%) were female and 124 (52.32%) had >4 comorbidities; 153 (39.2%) were censored into LOS ≤ 15 days, and death occurred in 19 (4.8%). Kaplan-Meier's plot compared factors causing a delay in discharge to the single factors: age, gender, and multimorbidity. A multivariate Cox regression analysis adjusted to age, gender, and multimorbidity predicted factors affecting LOS. Further research is required to explore multimorbidity as a risk factor for mortality in patients with prolonged LOS within a complex discharge unit and target gender-specific frailty measures to achieve high-quality patient management.

Title: Understanding a Low Vitamin D State in the Context of COVID-19.

While a low vitamin D state has been associated with an increased risk of infection by SARS-CoV-2 in addition to an increased severity of COVID-19 disease, a causal role is not yet established. Here, we review the evidence relating to i) vitamin D and its role in SARS-CoV-2 infection and COVID-19 disease ii) the vitamin D status in the Irish adult population iii) the use of supplemental vitamin D to treat a deficient status and iv) the application of the Bradford-Hill causation criteria. We conclude that reverse causality probably makes a minimal contribution to the presence of low vitamin D states in the setting of COVID-19. Applying the Bradford-Hill criteria, however, the collective literature supports a causal association between low vitamin D status, SARS-CoV-2 infection, and severe COVID-19 (respiratory failure, requirement for ventilation and mortality). A biologically plausible rationale exists for these findings, given vitamin D's role in immune regulation. The thresholds which define low, deficient, and replete vitamin D states vary according to the disease studied, underscoring the complexities for determining the goals for supplementation. All are currently unknown in the setting of COVID-19. The design of vitamin D randomised controlled trials is notoriously problematic and these trials commonly fail for a number of behavioural and methodological reasons. In Ireland, as in most other countries, low vitamin D status is common in older adults, adults in institutions, and with obesity, dark skin, low UVB exposure, diabetes and low socio-economic status. Physiological vitamin D levels for optimal immune function are considerably higher than those that can be achieved from food and sunlight exposure alone in Ireland. A window exists in which a significant number of adults could benefit from vitamin D supplementation, not least because of recent data demonstrating an association between vitamin D status and COVID-19. During the COVID pandemic, we believe that supplementation with 20-25ug (800-1000 IU)/day or more may be required for adults with apparently normal immune systems to improve immunity against SARS-CoV-2. We expect that higher monitored doses of 37.5-50 ug (1,500-2,000)/day may be needed for vulnerable groups (e.g., those with obesity, darker skin, diabetes mellitus and older adults). Such doses are within the safe daily intakes cited by international advisory agencies.

Emergency medical admissions and COVID-19: impact on 30-day mortality and hospital length of stay.

BACKGROUND: The COVID-19 pandemic has put considerable strain on healthcare systems. AIM: To investigate the effect of the COVID-19 pandemic on 30-day in-hospital mortality, length of stay (LOS) and resource utilization in acute medical care. METHODS: We compared emergency medical admissions to a single secondary care centre during 2020 to the preceding 18 years (2002-2019). We investigated 30-day in-hospital mortality with a multiple variable logistic regression model. Utilization of procedures/services was related to LOS with zero truncated Poisson regression. RESULTS: There were 132,715 admissions in 67,185 patients over the 19-year study. There was a linear reduction in 30-day in-hospital mortality over time; over the most recent 5 years (2016-2020), there was a relative risk reduction of 36%, from 7.9 to 4.3% with a number needed to treat of 27.7. Emergency medical admissions increased 18.8% to 10,452 in 2020 with COVID-19 admissions representing 3.5%. 18.6% of COVID-19 cases required ICU admission with a median stay of 10.1 days (IQR 3.8, 16.0). COVID-19 was a significant univariate predictor of 30-day in-hospital mortality, 18.5% (95%CI: 13.9, 23.1) vs. 3.0% (95%CI: 2.7, 3.4)-OR 7.3 (95%CI: 5.3, 10.1). ICU admission was the dominant outcome predictor-OR 12.4 (95%CI: 7.7, 20.1). COVID-19 mortality in the last third of 2020 improved-OR 0.64 (95%CI: 0.47, 0.86). Hospital LOS and resource utilization were increased. CONCLUSION: A diagnosis of COVID-19 was associated with significantly increased mortality and LOS but represented only 3.5% of admissions and did not attenuate the established temporal decline in overall in-hospital mortality.

Severe COVID-19 is characterised by inflammation and immature myeloid cells early in disease progression.

SARS-CoV-2 infection causes a wide spectrum of disease severity. Identifying the immunological characteristics of severe disease and the risk factors for their development are important in the management of COVID-19. This study aimed to identify and rank clinical and immunological features associated with progression to severe COVID-19 in order to investigate an immunological signature of severe disease. One hundred and eight patients with positive SARS-CoV-2 PCR were recruited. Routine clinical and laboratory markers were measured, as well as myeloid and lymphoid whole-blood immunophenotyping and measurement of the pro-inflammatory cytokines IL-6 and soluble CD25. All analysis was carried out in a routine hospital diagnostic laboratory. Univariate analysis demonstrated that severe disease was most strongly associated with elevated CRP and IL-6, loss of DLA-DR expression on monocytes and CD10 expression on neutrophils. Unbiased machine learning demonstrated that these four features were strongly associated with severe disease, with an average prediction score for severe disease of 0.925. These results demonstrate that these four markers could be used to identify patients developing severe COVID-19 and allow timely delivery of therapeutics.

Non-Specific Clinical Presentations are Not Prognostic and do not Anticipate Hospital Length of Stay or Resource Utilization.

AIM: To investigate whether a specific (SP) or non-specific (NSP) clinical presentation, predicts prognosis and in-hospital resource utilization in emergency medical admissions. METHODS: We studied admissions over 5 years (2015-2019) and classified the symptom presentation as SP or NSP. The predictive capacity of the NSP category was related to 30-day in-hospital mortality with a multivariable logistic regression model. Utilization of procedures/services was related to hospital length of stay (LOS) with zero truncated Poisson regression. RESULTS: There were 39,776 admissions in 23,995 patients. A NSP occurred in 18.2% of our top 20 clinical presentations; the top five being shortness of breath (12.8%), 'unwell' (7.1%), collapse (4.1%), abdominal pain (3.6%) and headache (2.7%). Baseline demographic characteristics were similar and unrelated to type of presentation; the model adjusted mortality by SP 4.0% (95% CI: 3.8%, 4.2%) or NSP 3.9% (95% CI: 3.5%, 4.4%) was identical. LOS was a dependant quantitative function of procedures/services undertaken; for the top two presentations of shortness of breath (SP) or unwell (NSP) there was no relationship between a SP or NSP presentation and hospital utilization of procedures/services or LOS. CONCLUSION: Our data suggest no utility for a categorisation of presentations as specific or non-specific in terms of provision of prognostic information nor as an indicator of the pattern of hospital investigation or LOS.

Is there excessive troponin testing in clinical practice? Evidence from emergency medical admissions.

AIM: To investigate whether excessive high-sensitivity cardiac troponin T (hscTnT) testing, in non-cardiac presentations, increases hospital length of stay (LOS) by driving down-stream investigations. METHODS: We report on all hscTnT tests in emergency medical admissions, performed over a 9-year period between 2011-2019. Troponin testing frequency in different risk cohorts was determined and related to 30-day in-hospital mortality with a multivariable logistic regression model adjusted for other outcome predictors. Downstream utilization of procedures/services was related to LOS with zero truncated Poisson regression. RESULTS: There were 66,475 admissions in 36,518 patients. hscTnT was tested in 24.4% of admissions, more frequently in the elderly (>70 years 33.4%, >80 years 35.9%), cardiovascular presentations (33.6%) and in those with high comorbidity (42.2%), and reduced in those with neurologic presentations (20%). A hscTnT request predicted increased 30-day in-hospital mortality OR 3.33 (95% CI: 3.06, 3.64). The univariate odds ratio (OR) of hscTnT test result was 1.45 (95% CI: 1.42, 1.49) and was semi-quantative with worsening outcomes as hscTnT increased. It remained predictive in the fully adjusted model OR 1.17 (95% CI: 1.09, 1.26). LOS was linearly related to the number of procedures/services performed. hscTnT testing did not increase LOS or number of procedures/services CONCLUSION: : A clinical request for hscTnT testing is prognostic and risk categorises. Subsequent resource utilization, if increased, appears an epiphenomenon related to risk categorisation, rather than being driven by inappropriate hscTnT testing.

Investigating the Relationship between Vitamin D and Persistent Symptoms Following SARS-CoV-2 Infection.

The emergence of persistent symptoms following SARS-CoV-2 infection, known as long COVID, is providing a new challenge to healthcare systems. The cardinal features are fatigue and reduced exercise tolerance. Vitamin D is known to have pleotropic effects far beyond bone health and is associated with immune modulation and autoimmunity. We hypothesize that vitamin D levels are associated with persistent symptoms following COVID-19. Herein, we investigate the relationship between vitamin D and fatigue and reduced exercise tolerance, assessed by the Chalder Fatigue Score, six-minute walk test and modified Borg scale. Multivariable linear and logistic regression models were used to evaluate the relationships. A total of 149 patients were recruited at a median of 79 days after COVID-19 illness. The median vitamin D level was 62 nmol/L, with n = 36 (24%) having levels 30-49 nmol/L and n = 14 (9%) with levels <30 nmol/L. Fatigue was common, with n = 86 (58%) meeting the case definition. The median Borg score was 3, while the median distance covered for the walk test was 450 m. No relationship between vitamin D and the measures of ongoing ill-health assessed in the study was found following multivariable regression analysis. These results suggest that persistent fatigue and reduced exercise tolerance following COVID-19 are independent of vitamin D.

Age and outcome in acute emergency medical admissions.

BACKGROUND: there is a lack of outcome information with respect to older health service users. The purpose of this study was to examine 30-day in-hospital mortality and its predictors in all elderly patients admitted as a medical emergency to our hospital. METHODS: all patients admitted between 2002 and 2008 were studied, linking anonymised clinical, administrative, laboratory and mortality data. Significant univariate predictors of outcome, including co-morbidity and illness severity score, were entered into a multivariate logistic regression model, adjusting the univariate estimates of the effect of age on in-hospital mortality. RESULTS: we admitted 23,114 consecutive acute medical admissions between 2002 and 2008; 30-day in-hospital mortality was 20.7% in the over 75 age category versus 4.5% in those younger. The unadjusted OR for a 30-day in-hospital mortality in the over 75 category of 5.21 (95% CI 4.73, 5.73) fell to 4.69 (95% CI 4.04, 5.44) when adjusted for outcome predictors excluding acute illness severity and 2.93 (95% CI 2.50, 3.42) when acute illness severity was added as a covariate. When the interaction between age and co-morbidity is examined, the odds ratio adjusts to 3.22 (95% CI 2.63, 3.6). CONCLUSION: acute illness severity is more important than co-morbidity in explaining the outcome in older patients admitted as medical emergencies. Service planning for acute elderly care should be based on effective disease management programmes but recognise the contribution of acute illness severity to outcome when conditions deteriorate.

Comparative influence of Acute Illness Severity and comorbidity on mortality.

BACKGROUND: The extent to which illness severity and comorbidity determine the outcome of an emergency medical admission is uncertain. We aim to quantitate the relative effect of these factors on mortality. METHODS: We evaluated all emergency medical admission to our institution between 2002 and 2018. We derived an Acute Illness Severity Score (AISS) and Comorbidity Score from admission data and International Classification of Diseases codings. We employed a multivariable logistic regression model to relate both to 30-day in-hospital mortality. RESULTS: There were 113,807 admissions in 58,126 patients. Both AISS, Odds Ratio (OR) 4.4 (95%CI 3.5, 5.5), and Comorbidity Score, OR 1.91 (95%CI 1.67, 2.18), independently predicted 30-day in-hospital mortality. The two highest AISS risk groups encompassed 46.5% of admissions with predicted mortality of 5.9% (95%CI 5.7%, 6.1%) and 14.4% (95%CI 13.9%, 14.8%) respectively. Comorbidity Score >=10 occurred in 17.9% of admissions with a predicted mortality of 13.3%. AISS and Comorbidity Score interacted to adversely influence mortality; the threshold effect for Comorbidity Score was reduced at high levels of AISS. CONCLUSION: High AISS and Comorbidity Scores were predictive of 30-day in-hospital mortality and relatively common in emergency medical admissions. There is a strong interaction between the two scores.