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Multicenter Study
. 2025 Jul 3;14(6):327-341.
doi: 10.1093/ehjacc/zuaf043.

Development and validation of a risk score in acute myocardial infarction-related cardiogenic shock

Elma J Peters  1 , Joakim B Kunkel  2 , Margriet Bogerd  1 , Sanne Ten Berg  1 , Marijke J C Timmermans  3 , Ole K L Helgestad  4 , Hanne B Ravn  5 , Adriaan O Kraaijeveld  6 , Luuk C Otterspoor  7   8 , Krischan D Sjauw  9   10 , Erik Lipšic  11 , Annemarie E Engström  12 , Alexander P J Vlaar  12 , Christian Hassager  2 , Jacob E Møller  2   4 , José P S Henriques  1
Affiliations
Multicenter Study

Development and validation of a risk score in acute myocardial infarction-related cardiogenic shock

Elma J Peters et al. Eur Heart J Acute Cardiovasc Care. .

Abstract

Aims: Mortality in patients with acute myocardial infarction-related cardiogenic shock (AMICS) is high, but a widely accepted tool for individual risk assessment is lacking. A reliable prediction model could assist in clinical decision-making, patient selection for clinical trials, and comparison of AMICS populations. Therefore, the aim of this study was to develop and externally validate a prediction model for 30-day mortality in AMICS patients.

Methods and results: This retrospective cohort study included patients from 2017 to 2021 (development cohort) and 2010-2017 (validation cohort). Patients with AMICS undergoing percutaneous coronary intervention in The Netherlands were identified using the Netherlands Heart Registration. International validation was performed in the Danish Retroshock registry. The main outcome was 30-day mortality. Among 2261 patients, the median age was 67 years [interquartile range (IQR) 58-75], and 1649 (73%) were male. The mortality rate at 30 days was 39% (n = 886). Significant predictors for mortality were: initial lactate, glucose, renal function, haemoglobin, age, blood pressure, heart rate, intubation prior to PCI, intervention in the left main coronary artery, and successful revascularization. The AUC of the initial model was 0.81 (0.79-0.83). The external validation cohort included 1393 patients with 1050 (75%) male and a median age of 67 years (IQR 59-75). The 30-day mortality rate was 49% (n = 680). The model showed good performance on the external validation with an AUC of 0.73 (0.70-0.76).

Conclusion: A prediction model was developed and externally validated using data from two large national registries. The model demonstrated good performance and is suitable for clinical decision-making and quality purposes in AMICS.

Keywords: Acute myocardial infarction; Cardiogenic shock; Mortality; Prediction model; Risk prediction.

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Conflict of interest statement

Conflict of interest: All authors have completed the ICMJE uniform disclosure form at http://www.icmje.org/disclosure-of-interest/ and declare: no support from any organization for the submitted work; O.K.L.H. has received a consultant fee from Abiomed, H.B.R. has received honoraria from Abiomed, A.O.K. declares an institutional research grant from Xenios AG, institutional lecture fees from Novartis and Inari, and travel support from Edwards, E.L. has received an educational institutional grant from Abbott Medical Nederland and a consulting fee from Dekra Certification BV and is a board member of the Interventional Cardiology Working group of the NVVC (Nederlandse Vereniging Voor Cardiologie), J.E.M. has received speakers fees from Abbott Vascular, Orion Corporation, and Boehringer Ingelheim and declares institutional research fees from Abiomed and Roche, J.P.S.H. reports receiving research grants from Health∼Holland, B. Braun, Infraredx/Nipro, ZonMw, Astra Zeneca, and Abbott Vascular and is a board member of the NVVC; no other relationships or activities that could appear to have influenced the submitted work.

Figures

Graphical Abstract
Graphical Abstract
Created with Biorender.com.
Figure 1
Figure 1
Calibration curve of the main model. Calibration curve of observed and predicted probabilities in external data of the main model.
Figure 2
Figure 2
Nomogram to calculate risk predictions. For each variable, find the corresponding value on its axis. Then, draw a vertical line from that point upward to intersect with the ‘points scale’ at the top of the nomogram to find the number of points assigned based on the patient's value for that variable. Repeat this process for each variable in the nomogram. Sum all the assigned points to get the total score. Plot the total score on the ‘total points’ axis and draw a vertical line downward to intersect with the ‘risk of mortality’ scale at the bottom. This point represents the estimated risk of mortality for the patient.
See this image and copyright information in PMC

References

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