Modified Shock Index as Simple Clinical Independent Predictor of In-Hospital Mortality in Acute Coronary Syndrome Patients: A Retrospective Cohort Study

Pramudyo, Miftah; Marindani, Vani; Achmad, Chaerul; Putra, Iwan Cahyo Santosa

doi:10.3389/fcvm.2022.915881

Cited by 9 publications

(8 citation statements)

References 22 publications

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“…According to a study by Vani et al, MSI has a sensitivity of 61.1% and a specificity of 73.7% for predicting hospital mortality as opposed to SI’s 49% and 85%. 6 In addition, MSI and GRACE do not significantly differ when compared, with AUCs of 0.715 and 0.815, respectively. 6 According to this study, the MSI had a normal value between 0.57 and 0.97.…”

Section: Discussionmentioning

confidence: 92%

“… 6 In addition, MSI and GRACE do not significantly differ when compared, with AUCs of 0.715 and 0.815, respectively. 6 According to this study, the MSI had a normal value between 0.57 and 0.97. This might be caused by the intricate process of the RAAS’s (Renin-Angiotensin-Aldosterone System) hemodynamic response to ACS.…”

Section: Discussionmentioning

confidence: 92%

“…But when it came to predicting death in ACS, MSI appeared to have higher sensitivity and specificity. 6 As a result, the goal of this study is to improve in-hospital mortality prediction in ACS patients by modifying the PADMA scoring system utilizing MSI in place of the SI.…”

Section: Introductionmentioning

confidence: 99%

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A Revised PADMA Scoring System for Predicting in-Hospital Mortality in Acute Coronary Syndrome Patient

Bernardus,

Pramudyo,

Akbar

2023

IJGM

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Background In order to predict in-hospital mortality in ACS (Acute Coronary Syndrome) patients based solely on clinical examination, this study compares the shock index (heart rate divided by systolic blood pressure) variable in PADMA (PADjadjaran Mortality in Acute Coronary Syndrome) with the modified shock index (heart rate divided by mean arterial pressure) score. The predictive efficacy of the PADMA score in predicting in-hospital mortality in ACS patients has been in doubt up until recently. Methods All ACS patients above the age of 18 who were admitted to Dr. Hasan Sadikin Central General Hospital between January 2018 and January 2023 were included in this retrospective observational cohort study. This study did not involve any interventions, and verbal informed permission was obtained with the Hasan Sadikin Hospital Ethic Committee’s approval. Multivariate logistic regression was used to gather and evaluate patient demographic, comorbidity, and clinical presentation data in order to provide two scoring systems (probability and cut-off models) that can be used to predict in-hospital all-cause death. The Fisher Z test was used to assess the area under the curve (AUC) between the PADMA SI (shock index) and PADMA MSI (modified shock index). Results Killip classifications III and IV, tachycardia, a high shock index, and older age were found to be independent mortality predictors and were included to the PADMA MSI score by multivariate regression analysis of 1504 people. PADMA SI score >8 has a sensitivity of 67.92% and a specificity of 84.01% for predicting all-cause death. The range of the PADMA SI score is 0 to 19. The AUC between the PADMA MSI and PADMA SI scores did not differ significantly (p=0.022). Conclusion Similar to the PADMA SI score, the PADMA MSI score >8 demonstrated an accurate discriminative power to forecast in-hospital mortality though it did not have significant statistic difference.

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Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 92%

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A Revised PADMA Scoring System for Predicting in-Hospital Mortality in Acute Coronary Syndrome Patient

Bernardus,

Pramudyo,

Akbar

2023

IJGM

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“…Patients with a combination 2 or 3 risk factors had a similar risk of recurrent ACS during the 3-year follow-up period. DM, CKD, and advanced age are important factors related to mortality in the ACS population [ 3 , 18 , 19 ]. In patients with ACS, a gradient of risk has been observed based on the presence or absence of DM and CKD, with those having both risk factors being at the highest risk [ 20 ].…”

Section: Discussionmentioning

confidence: 99%

Impact of Coexisting Risk Factors on Outcomes in Patients with Acute Coronary Syndrome: A Real-World Analysis Using the Taiwan Chang Gung Research Database

Lee

Tsai

et al. 2023

Med Sci Monit

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Background Diabetes mellitus (DM), chronic kidney disease (CKD), and advanced age are associated with poor outcomes in patients with acute coronary syndrome (ACS). This real-world study utilized data from the Taiwan Chang Gung Research Database (CGRD) to compare outcomes in ACS patients with DM, CKD, and the elderly. Material/Methods The study enrolled 28,613 ACS patients diagnosed based on CGRD medical records between January 2005 and December 2019. Baseline characteristics and clinical outcomes were compared among groups based on patient characteristics. Results Within the ACS cohort, 42.1% had DM, 48.2% had CKD, and 33.6% were elderly. Among them, 10.7% (3,070) were elderly patients with both DM and CKD. Elderly patients with DM and CKD had significantly higher risks of gastrointestinal bleeding (hazard ratio=11.32), cardiovascular events (HR=7.29), and all-cause mortality (HR=8.59). Patients with three or at least two of these risk factors had a 2.20–2.99-fold increased risk of recurrent ACS during the three-year follow-up period.. Conclusions Patients with the combination of DM, CKD, and advanced age (elderly) experienced an 11.32-fold increased risk of gastrointestinal bleeding, 7.29-fold increased risk of cardiovascular events, and 8.59-fold increased risk of all-cause mortality compared to those without these risk factors. Furthermore, patients with two or more of these risk factors had a 2- to 3-fold increased risk of recurrent ACS. These findings emphasize the importance of managing multiple risk factors in ACS patients to improve outcomes.

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“…8 SI and MSI are now used to estimate mortality in the population of the emergency department, including ACS patients. [9][10][11] In a study comparing MSI with SI, it was determined that MSI was more accurate than SI for predicting mortality and major cardiovascular events in patients with NSTEMI who received percutaneous coronary intervention (PCI). 12 The SIC score is calculated using the following formula: (SI×100)-estimated clearance ratio (CCr).…”

Section: Introductionmentioning

confidence: 99%

Shock Index Creatinine: A New Predictor of Mortality in Acute Coronary Syndrome Patients

Shariefuddin

Pramudyo

Martha

2023

Preprint

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Background The Shock Index Creatinine (SIC) scoring is a recently developed tool for risk stratification patients. These updated scoring was already used in ST-Elevation Myocardial Infarction (STEMI) patients. However its utility in predicting outcomes for patients with Acute Coronary Syndrome (ACS) remains unclear. This study aims to evaluate and update the current SIC score to predict in-hospital mortality among patients with ACS.Patients and methods: A retrospective cohort, Single-centered study enrolled 1393 ACS patients aged ≥ 18 years old diagnosed with ACS was conducted between January 2018 to January 2022. Study subjects were analyzed for in-hospital mortality and evaluated using binary linear regression analysis. The area under the curve (AUC) of SIC score was obtain to predict the sensitivity and specificity.Results Multivariate analysis showed that SIC score was significantly associated with in-hospital mortality. High SIC score (SIC ≥ 25) had significantly higher in-hospital mortality (p < 0.001) with odds ratio for (95% CIs) were 2.655 (1.6–4.31). Receiver operating characteristics (ROC) curve analysis determine the predictive power of SIC score for in-hospital mortality. SIC had an acceptable predictive value for in-hospital mortality (AUC = 0.789, 95% CI: 0.748–0.831, p < 0.001). The SIC score for sensitivity and specificity were, respectively, 71.5% and 74.4%, with optimal cutoff of SIC ≥ 25.Conclusion SIC had acceptable predictive value for in-hospital mortality in patients with all ACS spectrums. SIC was a useful parameter for predicting in-hospital mortality, particularly with a score ≥ 25. This is the first study to evaluate SIC in all spectrums of ACS.

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Modified Shock Index as Simple Clinical Independent Predictor of In-Hospital Mortality in Acute Coronary Syndrome Patients: A Retrospective Cohort Study

Cited by 9 publications

References 22 publications

A Revised PADMA Scoring System for Predicting in-Hospital Mortality in Acute Coronary Syndrome Patient

A Revised PADMA Scoring System for Predicting in-Hospital Mortality in Acute Coronary Syndrome Patient

Impact of Coexisting Risk Factors on Outcomes in Patients with Acute Coronary Syndrome: A Real-World Analysis Using the Taiwan Chang Gung Research Database

Shock Index Creatinine: A New Predictor of Mortality in Acute Coronary Syndrome Patients

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