Temporal Trends in Comorbidity Burden and Impact on Prognosis in Patients With Acute Coronary Syndrome Using the Elixhauser Comorbidity Index Score

The clinical characteristics, managements, and outcomes of acute myocardial infarction in osteoarthritis patients; a cross-sectional analysis of 6.5 million patients

OBJECTIVES

The prevalence of osteoarthritis (OA) and cardiovascular disease are increasing and both conditions share similar risk factors. We investigated the association between OA and receipt of invasive managements and clinical outcomes in patients with acute myocardial infarction (AMI).

METHODS

Using the National Inpatient Sample, adjusted binary logistic regression determined the association between OA and each outcome variable.

RESULTS

Of 6,561,940 AMI hospitalizations, 6.3% had OA. OA patients were older and more likely to be female. OA was associated with a decreased odds of coronary angiography (adjusted odds ratio 0.91; 95% confidence interval 0.90, 0.92), PCI (0.87; 0.87, 0.88), and coronary artery bypass grafting (0.98; 0.97, 1.00). OA was associated with a decreased odds of adverse outcomes (in-hospital mortality: 0.68; 0.67, 0.69; major acute cardiovascular and cerebrovascular events: 0.71; 0.70, 0.72; all-cause bleeding: 0.76; 0.74, 0.77; and stroke/TIA: 0.84; 0.82, 0.87).

CONCLUSIONS

This study of a representative sample of the US population highlights that OA patients are less likely to be offered invasive interventions following AMI. OA was also associated with better outcomes post-AMI, possibly attributed to a misclassification bias where unwell patients with OA were less likely to receive an OA code because codes for serious illness took precedence.

Transplanting candidates with stacked risks negatively affects outcomes

BACKGROUND

Lung transplant (LT) centers are increasingly evaluating patients with multiple risk factors for adverse outcomes. The effects of these stacked risks remains unclear. Our aim was to determine the relationship between the number of comorbidities and post-transplant outcomes.

METHODS

We performed a retrospective cohort study using the National Inpatient Sample (NIS) and UNOS Starfile (USF). We applied a probabilistic matching algorithm using 7 variables (transplant: month, year, and type; recipient: age, sex, race, payer). We matched recipients in the USF to transplant patients in the NIS between 2016 and 2019. The Elixhauser methodology was used to identify comorbidities present on admission. We determined the associations between mortality, length of stay (LOS), total charges, and disposition with comorbidity numbers using penalized cubic splines, Kaplan-Meier, and linear and logistic regression methods.

RESULTS

From 28,484,087 NIS admissions, we identified 1,821 LT recipients. Matches were exact in 76.8% of the cohort. While the remaining cohort had a probability match of ≥0.94. Penalized splines of Elixhauser comorbidity number identified 3 knots defining 3 groups of stacked risk: low (<3), medium (3-6), and high risk (>6). Inpatient mortality increased from low to medium to high-risk categories: (1.6%, 3.9%, and 7.0%; p < 0.001), as did LOS (16, 21, 29 days, p < 0.001), total charges ($553,057, $666,791, $821,641.5; p = 0.004) and discharge to a skilled nursing facility (15%, 20%, 31%; p < 0.001).

CONCLUSIONS

Stacked risks adversely affect post-LT mortality, LOS, charges, and discharge disposition. Further study to understand the details of specific stacked risks is warranted.

Key predictors and burden of meticillin-resistant Staphylococcus aureus in comparison with meticillin-susceptible S. aureus infections in an Australian hospital setting

BACKGROUND

Staphylococcus aureus is associated with significant mortality and increased burden on the healthcare system. Relatively few reliable estimates are available regarding the impact of meticillin-resistant Staphylococcus aureus (MRSA) compared to meticillin-susceptible Staphylococcus aureus (MSSA) infections.

AIM

To compare patients with MRSA and MSSA infection to identify differences in inpatient mortality, length of stay and cost of hospital services, and identify predictors of MRSA as a cause of Staphylococcus aureus infection.

METHODS

An analytical, retrospective, longitudinal study using non-identifiable linked data on adults admitted to hospitals of a health district in Australia with a diagnosis of Staphylococcus aureus infection over a 10-year period. The main outcome measure was 30-day inpatient mortality. Secondary endpoints included total overnight stays, all-cause inpatient mortality, and hospitalisation cost within 1 year of index admission.

FINDINGS

Inpatient mortality at 30, 100, and 365 days was estimated to be significantly greater for patients with MRSA infections. The mean additional cost of MRSA infections when controlling for additional factors was $5,988 and 4 nights' additional hospital stay per patient within 1 year of index admission. Key predictors of MRSA infection were: date of index admission, higher comorbidity score, greater socio-economic disadvantage, admission to hospital other than via the emergency department, older age, and prior admission to hospital within 28-days of index admission.

CONCLUSIONS

MRSA infections are associated with increased inpatient mortality, cost and hospital length of stay, compared to those caused by MSSA. Efforts are required to alleviate the additional burden of MRSA infections on patients and healthcare systems.

Depression and the risk of hospitalization in type 2 diabetes patients: A nested case-control study accounting for non-persistence to antidiabetic treatment

INTRODUCTION

Depression is one of the most common comorbidities of type 2 diabetes. The relationship between these two diseases seems to be bidirectional. Both conditions separately lead to significant morbidity and mortality, including hospitalization. Moreover, depression is associated with non-persistence with antidiabetic drugs.

OBJECTIVES

To measure the effect of depression on morbidity and particularly on all-cause, diabetes-related, cardiovascular-related and major cardiovascular events-related hospitalization, adjusting for non-persistence to antidiabetic drugs and other confounders.

METHODS

We performed a nested case-control study within a cohort of type 2 diabetic individuals initiating antidiabetic drugs. Using the health administrative data of the province of Quebec, Canada, we identified all-cause, diabetes-related, cardiovascular-related and major cardiovascular hospitalizations during a maximum follow-up of eight years after the initiation of antidiabetic drug treatment. A density sampling method matched all cases with up to 10 controls by age, sex, and the Elixhauser comorbidity index. The effect of depression on hospitalization was estimated using conditional logistic regressions adjusting for non-persistence to antidiabetic drug treatment and other variables.

RESULTS

We identified 41,550 all-cause hospitalized cases, of which 34,437 were related to cardiovascular (CV) diseases, 29,584 to diabetes, and 13,867 to major CV events. Depression was diagnosed in 2.51% of all-cause hospitalizations and 1.16% of matched controls. 69.11% of cases and 72.59% of controls were on metformin monotherapy. The majority (71.62% vs 75.02%, respectively) stayed on metformin monotherapy without adding or switching drugs during follow-up. Non-persistence was at similar rates (about 30%) in both groups. In the multivariable analyses, depression was associated with an increased risk for all-cause hospitalizations, with odds ratios (ORs) ranging from 2.21 (95% CI: 2.07-2.37) to 1.32 (95% CI: 1.22-1.44) according to the model adjustment (from the univariate to the fully adhjusted).

CONCLUSION

Depression increased the risk of all-cause hospitalizations among patients treated for diabetes, even after accounting for non-persistence and other potentially confounding factors. These results stress the impact of depression on diabetic patients' use of health care resources.

Is the contemporary care of the older persons with acute coronary syndrome evidence-based?

Globally, ischaemic heart disease is the leading cause of death, with a higher mortality burden amongst older adults. Although advancing age is associated with a higher risk of adverse outcomes following acute coronary syndrome (ACS), older patients are less likely to receive evidence-based medications and coronary angiography. Guideline recommendations for managing ACS are often based on studies that exclude older patients, and more contemporary trials have been underpowered and produced inconsistent findings. There is also limited evidence for how frailty and comorbidity should influence management decisions. This review focuses on the current evidence base for the medical and percutaneous management of ACS in older patients and highlights the distinct need to enrol older patients with ACS into well-powered, large-scale randomized trials.

Prognostic impact of comorbidity measures on outcomes following acute coronary syndrome: A systematic review

AIM

To identify existing comorbidity measures and summarise their association with acute coronary syndrome (ACS) outcomes.

METHODS

We searched published studies from MEDLINE (OVIDSP) and EMBASE from inception to March 2021, studies of the pre-specified conference proceedings from Web of Science since May 2017, and studies included in any relevant systematic reviews. Studies that reported no comorbidity measures, no association of comorbid burden with ACS outcomes, or only used a comorbidity measure as a confounder without further information were excluded. After independent screening by three reviewers, data extraction and risk of bias assessment of each included study was undertaken. Results were narratively synthesised.

RESULTS

Of 4166 potentially eligible studies identified, 12 (combined n = 6 885 982 participants) were included. Most studies had a high risk of bias at quality assessment. Six different types of comorbidity measures were identified with the Charlson comorbidity index (CCI) the most widely used measure among studies. Overall, the greater the comorbid burden or the higher comorbidity scores recorded, the greater was the association with the risk of mortality.

CONCLUSION

The review summarised different comorbidity measures and reported that higher comorbidity scores were associated with worse ACS outcomes. The CCI is the most widely measure of comorbid burden and shows additive value to clinical risk scores in use.

Elixhauser outperformed Charlson comorbidity index in prognostic value after ACS: insights from a national registry

OBJECTIVE

To compare the performance of risk adjustment models using the Elixhauser and Charlson comorbidity scores in predicting in-hospital outcomes of ACS patients from a nationwide administrative database.

STUDY DESIGN AND SETTING

All hospitalizations for ACS in the United States between 2004 and 2014 (n = 7,201,900) were retrospectively analyzed. We used ECS and CCI score based on ICD-9 codes to define comorbidity variables. Logistic regression models were fitted to three in-hospital outcomes, including mortality, Major Acute Cardiovascular & Cerebrovascular Events (MACCE) and bleeding. The prognostic values of ECS and CCI after adjusting for known confounders, were compared using the C-statistic, Akaike information criterion (AIC), and Bayesian information criterion (BIC).

RESULTS

The statistical performance of models predicting all in-hospital outcomes demonstrated that the ECS had superior prognostic value compared to the CCI, with higher C-statistics and lower AIC and BIC values associated with the former.

CONCLUSION

This is the first study that compared the prognostic value of the ECS and CCI scores in predicting multiple ACS outcomes, based on their scoring systems. Better discrimination and goodness of fit was achieved with the Elixhauser method across all in-hospital outcomes studied.

Long-term risk of death and recurrent cardiovascular events following acute coronary syndromes

Estimates of the risk of recurrent cardiovascular events (residual risk) among patients with acute coronary syndromes have largely been based on clinical trial populations. Our objective was to estimate the residual risk associated with common comorbidities in a large, unselected, population-based cohort of acute coronary syndrome patients. 31,056 ACS patients (49.5%—non-ST segment elevation myocardial infarction [NSTEMI], 34.0%—ST segment elevation myocardial infarction [STEMI] and 16.5%—unstable angina [UA]) hospitalised in Alberta between April 2010 and March 2016 were included. The primary composite outcome was major adverse cardiovascular events (MACE) including: death, stroke or recurrent myocardial infarction. The secondary outcome was death from any cause. Cox-proportional hazard models were used to identify the impact of ACS type and commonly observed comorbidities (heart failure, hypertension, peripheral vascular disease, renal disease, cerebrovascular disease and diabetes). At 3.0 +/- 3.7 years, rates of MACE were highest in the NSTEMI population followed by STEMI and UA (3.58, 2.41 and 1.68 per 10,000 person years respectively). Mortality was also highest in the NSTEMI population followed by STEMI and UA (2.23, 1.38 and 0.95 per 10,000 person years respectively). Increased burden of comorbidities was associated with an increased risk of MACE, most prominently seen with heart failure (adjusted HR 1.83; 95% CI 1.73–1.93), renal disease (adjusted HR 1.52; 95% CI 1.40–1.65) and diabetes (adjusted HR 1.51; 95% CI 1.44–1.59). The cumulative presence of each of examined comorbidities was associated with an incremental increase in the rate of MACE ranging from 1.7 to 9.98 per 10,000 person years. Rates of secondary prevention medications at discharge were high including: statin (89.5%), angiotensin converting enzyme inhibitor/angiotensin receptor blocker (84.1%) and beta-blockers (85.9%). Residual cardiovascular risk following an acute coronary syndrome remains high despite advances in secondary prevention. A higher burden of comorbidities is associated with increased residual risk that may benefit from aggressive or novel therapies.