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Decoding Cardiogenic Shock Complexity: Validation and Prognostic Significance of Machine-Learning Phenotypes in a Portuguese Patient Cohort
Session:
Comunicações Orais - Sessão 01 - Choque cardiogénico e transplante cardíaco
Speaker:
Joana Certo Pereira
Congress:
CPC 2024
Topic:
D. Heart Failure
Theme:
11. Acute Heart Failure
Subtheme:
11.6 Acute Heart Failure - Clinical
Session Type:
Comunicações Orais
FP Number:
---
Authors:
Joana Certo Pereira; Miguel Domingues; João Presume; Rita Carvalho; Rita Bello; Rita Lima; Rita Barbosa; Mariana Paiva; Catarina Brízido; Christopher Strong; Jorge Ferreira; António Tralhão
Abstract
<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong>Introduction:</strong></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif">Accurate characterization of Cardiogenic Shock (CS) is imperative for enhancing our comprehension of this intricate syndrome and tailoring effective therapies. The CS Working Group (CSWG) has delineated three distinct clinical phenotypes—non-congested (I), cardiorenal (II), and cardiometabolic (III)—using machine learning. While these phenotypes may exhibit prognostic implications, their reproducibility necessitates further validation. This study sought to validate the relevance of CS phenotypes in a real-world cohort from Portugal.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong>Methods:</strong></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif">Retrospective, single-center study enrolling consecutive CS patients in a cardiac intensive care unit, from December 2014 to October 2023. Patient phenotyping utilized the CSWG Calculator based on the following specific characteristics: age, serum creatinine, serum bicarbonate, alanine transaminase, lactate, platelet count, and white-cell count. The co-primary outcomes were in-hospital and 30-day mortality.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong>Results:</strong></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif">A total of 269 patients (66% men, mean age 67±16 years) were analyzed. CS etiology included ischemic (45%), chronic heart failure (35%), and secondary causes (20%). Admission SCAI stages were C (67%), D (22%), and E (7%). During hospitalization, progression to SCAI D or E occurred in 58% of cases, of whom 32% required mechanical circulatory support. In-hospital mortality was 48%.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif">Overall, 26% (n=71) of patients were classified as phenotype I, 41% (n=111) as phenotype II and 32% (n=87) as phenotype III. In-hospital mortality rates were 21%, 50%, and 66%, respectively (Figure 1A). Crude odds-ratio for in-hospital mortality were 3.88 (95% CI: 1.95-7.69; p < 0.001) and 6.80 (95% CI: 3.27-14.15; p < 0.001) for phenotypes II and III, when compared to phenotype I. Kaplan-Meier curves for overall 30-day mortality are depicted in Figure 1B.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif">The risk of progressing to stage D or E shock during hospitalization was lowest in phenotype I and highest in phenotype III (Figure 1C). In a bivariate Cox regression model adjusted for SCAI staging, CS phenotyping remained significantly associated with 30-day mortality (OR 1.94 [1.47; 2.54]; p < 0.001).</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif"><strong>Conclusion:</strong></span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,sans-serif">This retrospective study validated the CSWG phenotyping categorization in a Portuguese CS cohort, establishing a significant association with in-hospital mortality while adding prognostic information to the SCAI shock classification. Our findings support the applicability of these phenotypes, offering nuanced risk stratification with potential therapeutic implications.</span></span></p>
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