Mortality risk prediction in elderly patients with cardiogenic shock: results from the CardShock study

Hongisto, Mari; Lassus, Johan; Tarvasmäki, Tuukka; Sionís, Alessandro; Sans‐Roselló, Jordi; Tolppanen, Heli; Kataja, Anu; Jäntti, Toni; Sabell, Tuija; Lindholm, Matias Greve; Banaszewski, Marek; Silva-Cardoso, José; Parissis, John; Somma, Salvatore Di; Carubelli, Valentina; Jurkko, Raija; Masip, Josep; Harjola, Veli‐Pekka; Investigators, CardShock Study

doi:10.1002/ehf2.13224

Cited by 17 publications

(7 citation statements)

References 23 publications

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“…These variables were selected based on clinical and scientific knowledge. [9][10][11][12] To analyse the association between sex and outcome, a Cox regression model with 30 day in-hospital mortality as the dependent variable and sex as the independent variable was fitted, adjusted for the same variables as mentioned earlier. Median follow-up time was estimated by the reverse Kaplan-Meier estimator.…”

Section: Discussionmentioning

confidence: 99%

“…To analyse the association between sex and use of selected treatments (catecholamines, vasopressors, va‐ECMO, or pLVAD), a logistic regression model with the respective treatment as the dependent variable and sex as the independent variable was fitted, adjusted for age, prior cardiac arrest and time to return of spontaneous circulation, shock index (heart rate divided by systolic blood pressure) ≥1, baseline lactate, and baseline pH. These variables were selected based on clinical and scientific knowledge 9–12 …”

Section: Methodsmentioning

confidence: 99%

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Sex differences in patients with cardiogenic shock

Yan¹,

Schrage

Weimann³

et al. 2021

ESC Heart Failure

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Aims Differences between female and male patients in clinical presentation, causes and treatment of cardiogenic shock (CS) are poorly understood. We aimed to investigate sex differences in presentation with and treatment of CS. Methods and results We analysed data of 978 patients presenting with CS to a tertiary care hospital between October 2009 and October 2017. Multivariable adjusted logistic/Cox regression models were fitted to investigate the association between sex and clinical presentation, use of treatments and 30 day mortality. Median age was 70 years (interquartile range 58-79 years), and 295 (30.2%) patients were female. After adjustment for multiple relevant confounders, female patients were more likely to be older [odds ratio (OR) 1.21, 95% confidence interval (CI) 1.02-1.42, P = 0.027], but other relevant presentation characteristics did not differ between both sexes. Despite the similar presentation, female patients were less likely to be treated with percutaneous left ventricular assist devices (OR 0.78, 95% CI 0.64-0.94, P = 0.010), but more likely to be treated with catecholamines (OR 1.21, 95% CI 1.02-1.44, P = 0.033) or vasopressors (OR 1.26, 95% CI 1.05-1.50, P = 0.012). A 30 day mortality risk in female patients was as high as in male patients (hazard ratio 1.08, 95% CI 1.00-1.18, P = 0.091). Conclusions In this large, contemporary cohort, clinical presentation was comparable in female and male patients, and both sexes were associated with a comparably high mortality risk. Nevertheless, female patients received different treatment for CS and were most importantly less likely to be treated with percutaneous left ventricular assist devices.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Sex differences in patients with cardiogenic shock

Yan¹,

Schrage

Weimann³

et al. 2021

ESC Heart Failure

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“…In AMI-CS, age, initial systolic blood pressure, evidence of congestive cardiac failure and requirement of mechanical circulatory support have been welldescribed as independent predictors of 30-day mortality. [14,18,19] We demonstrated an increased adjusted risk of 30-day mortality in those aged ≥ 70 years, as shown in the cubic spline by visual assessment (Figure 3). Our study's findings are consistent with these data, demonstrating the powerful adverse prognostic impact of older age in patients with CS.…”

Section: Discussionmentioning

confidence: 78%

Age as a predictor of clinical outcomes and determinant of therapeutic measures for emergency medical services treated cardiogenic shock

Xiao

Bloom

Andrew

et al. 2023

Journal of Geriatric Cardiology

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BACKGROUND The impact of age on outcomes in cardiogenic shock (CS) is poorly described in the pre-hospital setting. We assessed the impact of age on outcomes of patients treated by emergency medical services (EMS). METHODSThis population-based cohort study included consecutive adult patients with CS transported to hospital by EMS. Successfully linked patients were stratified into tertiles by age (18-63, 64-77, and > 77 years). Predictors of 30-day mortality were assessed through regression analyses. The primary outcome was 30-day all-cause mortality.RESULTS A total of 3523 patients with CS were successfully linked to state health records. The average age was 68 ± 16 years and 1398 (40%) were female. Older patients were more likely to have comorbidities including pre-existing coronary artery disease, hypertension, dyslipidemia, diabetes mellitus, and cerebrovascular disease. The incidence of CS was significantly greater with increasing age (incidence rate per 100,000 person years 6.47 [95% CI: 6.1-6.8] in age 18-63 years, 34.34 [32.4-36.4] in age 64-77 years, 74.87 [70.6-79.3] in age > 77 years, P < 0.001). There was a step-wise increase in the rate of 30-day mortality with increasing age tertile. After adjustment, compared to the lowest age tertile, patients aged > 77 years had increased risk of 30-day mortality (adjusted hazard ratio = 2.26 [95% CI: 1.96-2.60]). Older patients were less likely to receive inpatient coronary angiography.CONCLUSION Older patients with EMS-treated CS have significantly higher rates of short-term mortality. The reduced rates of invasive interventions in older patients underscore the need for further development of systems of care to improve outcomes for this patient group.

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“…The CardShock risk score (10) need complicated calculation and scoring when it is used and partly depend on the subjective judgment of clinicians. Hongisto et al evaluated the prognostic ability of two models in elderly patients with CS and the results showed that the predictive power was not very good (28). The CoxBoost model was applicable to all types of elderly patients, and external verification showed that its prediction ability was better than the CardShock risk score.…”

Section: Model Presentationmentioning

confidence: 99%

Machine Learning for Prediction of Outcomes in Cardiogenic Shock

Rong

Xiang

Lü

et al. 2022

Front. Cardiovasc. Med.

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ObjectiveThe management of cardiogenic shock (CS) in the elderly remains a major clinical challenge. Existing clinical prediction models have not performed well in assessing the prognosis of elderly patients with CS. This study aims to build a predictive model, which could better predict the 30-day mortality of elderly patients with CS.MethodsWe extracted data from the Medical Information Mart for Intensive Care III version 1.4 (MIMIC-III) as the training set and the data of validation sets were collected from the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University. Three models, including the cox regression model, the Least Absolute Shrinkage and Selection Operator (LASSO) regression model, and the CoxBoost model, were established using the training set. Through the comparison of area under the receiver operating characteristic (ROC) curve (AUC), C index, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and median improvement in risk score, the best model was selected. Then for external validation, compared the best model with the simplified acute physiology score II (SAPSII) and the CardShock risk score.ResultsA total of 919 patients were included in the study, of which 804 patients were in the training set and 115 patients were in the verification set. Using the training set, we built three models: the cox regression model including 6 predictors, the LASSO regression model including 4 predictors, and the CoxBoost model including 16 predictors. Among them, the CoxBoost model had good discrimination [AUC: 0.730; C index: 0.6958 (0.6657, 0.7259)]. Compared with the CoxBoost model, the NRI, IDI, and median improvement in risk score of other models were all<0. In the validation set, the CoxBoost model was also well-discriminated [AUC: 0.770; C index: 0.7713 (0.6751, 0.8675)]. Compared with the CoxBoost model, the NRI, IDI, and median improvement in risk score of SAPS II and the CardShock risk score were all < 0. And we constructed a dynamic nomogram to visually display the model.ConclusionIn conclusion, this study showed that in predicting the 30-day mortality of elderly CS patients, the CoxBoost model was superior to the Cox regression model, LASSO regression model, SAPS II, and the CardShock risk score.

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Mortality risk prediction in elderly patients with cardiogenic shock: results from the CardShock study

Cited by 17 publications

References 23 publications

Sex differences in patients with cardiogenic shock

Sex differences in patients with cardiogenic shock

Age as a predictor of clinical outcomes and determinant of therapeutic measures for emergency medical services treated cardiogenic shock

Machine Learning for Prediction of Outcomes in Cardiogenic Shock

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