In-hospital mortality of cardiogenic shock complicating ST-elevation myocardial infarction in Malaysia: a retrospective analysis of the Malaysian National Cardiovascular Database (NCVD) registry

Venkatason, Padmaa; Zubairi, Yong Zulina; Ahmad, Wan Azman Wan; Hafidz, Muhammad; Ismail, Muhammad Dzafir; Hadi, Mohd Firdaus; Zuhdi, Ahmad Syadi Mahmood

doi:10.1136/bmjopen-2018-025734

Cited by 14 publications

(12 citation statements)

References 17 publications

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“…More likely, increasing age is associated with higher mortality in CS, regardless of shock severity as shown in a recent analysis of a large cohort of the Cardiogenic Shock Work Group registry, 31 a cohort of shock patients out of the Utah Cardiac Recovery shock database, 32 broad analysis of risk scores based on the CULPRIT-shock cohort 33 and most other trials and registries. 26,34,35 These findings are supported by our observation, too, as age was found to be a strong predictor of mortality, especially in patients with cardiac arrest.…”

Section: Discussionsupporting

confidence: 86%

“…Although some studies report only a minor impact of age with respect to prognosis in cardiogenic shock, 29,30 this might be due to selection bias as older patients in these studies displayed less comorbidities, indicating a highly selected group of older patients. More likely, increasing age is associated with higher mortality in CS, regardless of shock severity as shown in a recent analysis of a large cohort of the Cardiogenic Shock Work Group registry, 31 a cohort of shock patients out of the Utah Cardiac Recovery shock database, 32 broad analysis of risk scores based on the CULPRIT‐shock cohort 33 and most other trials and registries 26,34,35 . These findings are supported by our observation, too, as age was found to be a strong predictor of mortality, especially in patients with cardiac arrest.…”

Section: Discussionsupporting

confidence: 81%

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PRospective REgistry of PAtients in REfractory cardiogenic shock—The PREPARE CardShock registry

Lewinski

Herold

Stoffel

et al. 2022

Cathet Cardio Intervent

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Aim Cardiogenic shock (CS) is a hemodynamically complex multisystem syndrome associated with persistently high morbidity and mortality. As CS is characterized by progressive failure to provide adequate systemic perfusion, supporting end‐organ perfusion using mechanical circulatory support (MCS) seems intriguing. Since most patients with CS present in the catheterization laboratory, percutaneously implantable systems have the widest adoption in the field. We evaluated feasibility, outcomes, and complications after the introduction of a full‐percutaneous program for both the Impella CP device and venoarterial extracorporeal membrane oxygenator (VA‐ECMO). Methods PREPARE CardShock (PRospective REgistry of PAtients in REfractory cardiogenic shock) is a prospective single‐center registry, including 248 consecutive patients between May 2019 and April 2021, who underwent cardiac catheterization and displayed advanced cardiogenic shock. The median age was 70 (58–77) years and 28% were female. Sixty‐five percent of the cases had cardiac arrest, of which 66% were out‐of‐hospital cardiac arrest. A local standard operating procedure (SOP) indicating indications as well as relative and absolute contraindications for different means of MCS (Impella CP or VA‐ECMO) was used to guide MCS use. The primary endpoint was in‐hospital death and secondary endpoints were spontaneous myocardial infarction and major bleedings during the hospital stay. Results Overall mortality was 50.4% with a median survival of 2 (0–6) days. Significant independent predictors of mortality were cardiac arrest during the index event (odds ratio [OR] with 95% confidence interval [CI]: 2.53 [1.43–4.51]; p = 0.001), age > 65 years (OR: 2.05 [1.03–4.09]; p = 0.036]), pH < 7.30 (OR: 2.69 [1.56–4.66]; p < 0.001), and lactate levels > 2 mmol/L (OR: 4.51 [2.37–8.65]; p < 0.001). Conclusions Conclusive SOPs assist target‐orientated MCS use in CS. This study provides guidance on the implementation, validation, and modification of newly established MCS programs to aid centers that are establishing such programs.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionsupporting

confidence: 81%

PRospective REgistry of PAtients in REfractory cardiogenic shock—The PREPARE CardShock registry

Lewinski

Herold

Stoffel

et al. 2022

Cathet Cardio Intervent

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“…Invasive treatment such as PCI received by STEMI patients showed a trend towards better outcomes for in-hospital and 30 days after discharge. Mortality risk at 1-year was reduced by 40% for patients who received PCI compared to those who did not [ 4 , 39 , 45 ].…”

Section: Discussionmentioning

confidence: 99%

Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach

et al. 2021

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Background Conventional risk score for predicting short and long-term mortality following an ST-segment elevation myocardial infarction (STEMI) is often not population specific. Objective Apply machine learning for the prediction and identification of factors associated with short and long-term mortality in Asian STEMI patients and compare with a conventional risk score. Methods The National Cardiovascular Disease Database for Malaysia registry, of a multi-ethnic, heterogeneous Asian population was used for in-hospital (6299 patients), 30-days (3130 patients), and 1-year (2939 patients) model development. 50 variables were considered. Mortality prediction was analysed using feature selection methods with machine learning algorithms and compared to Thrombolysis in Myocardial Infarction (TIMI) score. Invasive management of varying degrees was selected as important variables that improved mortality prediction. Results Model performance using a complete and reduced variable produced an area under the receiver operating characteristic curve (AUC) from 0.73 to 0.90. The best machine learning model for in-hospital, 30 days, and 1-year outperformed TIMI risk score (AUC = 0.88, 95% CI: 0.846–0.910; vs AUC = 0.81, 95% CI:0.772–0.845, AUC = 0.90, 95% CI: 0.870–0.935; vs AUC = 0.80, 95% CI: 0.746–0.838, AUC = 0.84, 95% CI: 0.798–0.872; vs AUC = 0.76, 95% CI: 0.715–0.802, p < 0.0001 for all). TIMI score underestimates patients’ risk of mortality. 90% of non-survival patients are classified as high risk (>50%) by machine learning algorithm compared to 10–30% non-survival patients by TIMI. Common predictors identified for short- and long-term mortality were age, heart rate, Killip class, fasting blood glucose, prior primary PCI or pharmaco-invasive therapy and diuretics. The final algorithm was converted into an online tool with a database for continuous data archiving for algorithm validation. Conclusions In a multi-ethnic population, patients with STEMI were better classified using the machine learning method compared to TIMI scoring. Machine learning allows for the identification of distinct factors in individual Asian populations for better mortality prediction. Ongoing continuous testing and validation will allow for better risk stratification and potentially alter management and outcomes in the future.

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“…3 It is more common in patients with ST-elevation myocardial infarctions (STEMI) than in those with non-ST-elevation myocardial infarctions (NSTEMI). 3,4 Despite advances in treatment options, CS mortality remains high at approximately 35 to 50 percent. 1,3,5 Several risk scores that help predict short-term mortality have been established.…”

Section: Introductionmentioning

confidence: 99%

Predictive Nomogram of the in-Hospital Mortality of Patients with Cardiogenic Shock

Tien¹,

Chen²,

Huang³

et al. 2021

Preprint

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BackgroundDespite advances in treatment, the mortality rates of patients with cardiogenic shock (CS) remain high. The aim of this study was to develop a risk-predictive model for in-hospital mortality in patients admitted to the cardiac care unit (CCU) because of CS. Methods This retrospective study enrolled 509 adult patients who received inotropic support at the emergency room with subsequent admission to the CCU from January 2017 to December 2019. Patients with out-of-hospital cardiac arrest, inotrope use for conduction disorders, and non-CS were excluded. A total of 246 patients were analyzed using multiple logistic regression. ResultsA history of coronary artery disease (OR 3.44), multiple inotropic use (OR 17.70), ejection fraction less than 40% (OR 0.27), longer cardiopulmonary resuscitation (CPR) duration (OR 1.11), albumin infusion (OR 4.66), and renal replacement therapy (OR 3.08) were associated with higher in-hospital mortality. These factors were used to develop a risk-predictive nomogram. A receiver operating characteristic (ROC) curve was drawn using scores from 0 to 198.5 (area under the curve [AUC] = 0.92), and the cut-off score of 65 was identified. The model accurately predicted mortality (AUC = 0.81) in a validation set of 68 patients, with a sensitivity of 81% and a specificity of 74%. Conclusion Factors were used to develop a highly accurate risk-predictive nomogram for the in-hospital mortality of patients with CS, which may aid physicians in making prognoses.

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In-hospital mortality of cardiogenic shock complicating ST-elevation myocardial infarction in Malaysia: a retrospective analysis of the Malaysian National Cardiovascular Database (NCVD) registry

Cited by 14 publications

References 17 publications

PRospective REgistry of PAtients in REfractory cardiogenic shock—The PREPARE CardShock registry

PRospective REgistry of PAtients in REfractory cardiogenic shock—The PREPARE CardShock registry

Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach

Predictive Nomogram of the in-Hospital Mortality of Patients with Cardiogenic Shock

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