Dataset Information

Clinical Frailty Scale classes are independently associated with 6-month mortality for patients after acute myocardial infarction.

ABSTRACT:

Aims

Data on the prognostic value of frailty to guide clinical decision-making for patients with myocardial infarction (MI) are scarce. To analyse the association between frailty classification, treatment patterns, in-hospital outcomes, and 6-month mortality in a large population of patients with MI.

Methods and results

An observational, multicentre study with a retrospective analysis of prospectively collected data using the SWEDEHEART registry. In total, 3381 MI patients with a level of frailty assessed using the Clinical Frailty Scale (CFS-9) were included. Of these patients, 2509 (74.2%) were classified as non-vulnerable non-frail (CFS 1-3), 446 (13.2%) were vulnerable non-frail (CFS 4), and 426 (12.6%) were frail (CFS 5-9). Frailty and non-frail vulnerability were associated with worse in-hospital outcomes compared with non-frailty, i.e. higher rates of mortality (13.4% vs. 4.0% vs. 1.8%), cardiogenic shock (4.7% vs. 2.5% vs. 1.9%), and major bleeding (4.5% vs. 2.7% vs. 1.1%) (all P < 0.001), and less frequent use of evidence-based therapies. In Cox regression analyses, frailty was strongly and independently associated with 6-month mortality compared with non-frailty, after adjustment for age, sex, the GRACE risk score components, and other potential risk factors [hazard ratio (HR) 3.32, 95% confidence interval (CI) 2.30-4.79]. A similar pattern was seen for vulnerable non-frail patients (fully adjusted HR 2.07, 95% CI 1.41-3.02).

Conclusion

Frailty assessed with the CFS was independently and strongly associated with all-cause 6-month mortality, also after comprehensive adjustment for baseline differences in other risk factors. Similarly, non-frail vulnerability was independently associated with higher mortality compared with those with preserved functional ability.

SUBMITTER: Ekerstad N

PROVIDER: S-EPMC8826894 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Clinical Frailty Scale classes are independently associated with 6-month mortality for patients after acute myocardial infarction.

Ekerstad Niklas N Javadzadeh Dariush D Alexander Karen P KP Bergström Olle O Eurenius Lars L Fredrikson Mats M Gudnadottir Gudny G Held Claes C Ängerud Karin Hellström KH Jahjah Radwan R Jernberg Tomas T Mattsson Ewa E Melander Kjell K Mellbin Linda L Ohlsson Monica M Ravn-Fischer Annica A Svennberg Lars L Yndigegn Troels T Alfredsson Joakim J

European heart journal. Acute cardiovascular care 20220201 2

<h4>Aims</h4>Data on the prognostic value of frailty to guide clinical decision-making for patients with myocardial infarction (MI) are scarce. To analyse the association between frailty classification, treatment patterns, in-hospital outcomes, and 6-month mortality in a large population of patients with MI.<h4>Methods and results</h4>An observational, multicentre study with a retrospective analysis of prospectively collected data using the SWEDEHEART registry. In total, 3381 MI patients with a ...[more]

PMID: 34905049

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Project description:BackgroundOlder adults with acute myocardial infarction (AMI) have higher prevalence of functional impairments, including deficits in cognition, strength, and sensory domains, than their younger counterparts.ObjectiveTo develop and evaluate the prognostic utility of a risk model for 6-month post-AMI mortality in older adults that incorporates information about functional impairments.DesignProspective cohort study. (ClinicalTrials.gov: NCT01755052).Setting94 hospitals throughout the United States.Participants3006 persons aged 75 years or older who were hospitalized with AMI and discharged alive.MeasurementsFunctional impairments were assessed during hospitalization via direct measurement (cognition, mobility, muscle strength) or self-report (vision, hearing). Clinical variables associated with mortality in prior risk models were ascertained by chart review. Seventy-two candidate variables were selected for inclusion, and backward selection and Bayesian model averaging were used to derive (n = 2004 participants) and validate (n = 1002 participants) a model for 6-month mortality.ResultsParticipants' mean age was 81.5 years, 44.4% were women, and 10.5% were nonwhite. There were 266 deaths (8.8%) within 6 months. The final risk model included 15 variables, 4 of which were not included in prior risk models: hearing impairment, mobility impairment, weight loss, and lower patient-reported health status. The model was well calibrated (Hosmer-Lemeshow P > 0.05) and showed good discrimination (area under the curve for the validation cohort = 0.84). Adding functional impairments significantly improved model performance, as evidenced by category-free net reclassification improvement indices of 0.21 (P = 0.008) for hearing impairment and 0.26 (P < 0.001) for mobility impairment.LimitationThe model was not externally validated.ConclusionA newly developed model for 6-month post-AMI mortality in older adults was well calibrated and had good discriminatory ability. This model may be useful in decision making at hospital discharge.Primary funding sourceNational Heart, Lung, and Blood Institute of the National Institutes of Health.

Project description:BackgroundFrailty has been recognized as an important prognostic indicator in patients with acute myocardial infarction (AMI). However, no study has focused on critical AMI patients. We aimed to determine the impact of frailty on short- and long-term mortality risk in critical AMI patients.MethodsData from the Medical Information Mart for Intensive Care (MIMIC)-IV database was used. Frailty was assessed using the Hospital Frailty Risk Score (HFRS). Outcomes were in-hospital mortality and 1-year mortality. Logistic regression and Cox proportional-hazards models were used to investigate the association between frailty and outcomes.ResultsAmong 5,003 critical AMI patients, 2,176 were non-frail (43.5%), 2,355 were pre-frail (47.1%), and 472 were frail (9.4%). The in-hospital mortality rate was 13.8%, and the 1-year mortality rate was 29.5%. In our multivariable model, frailty was significantly associated with in-hospital mortality [odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.20-1.41] and 1-year mortality [hazard ratio (HR) = 1.29, 95% CI: 1.24-1.35] as a continuous variable (per five-score increase). When assessed as categorical variables, pre-frailty and frailty were both associated with in-hospital mortality (OR = 2.80, 95% CI: 2.19-3.59 and OR = 2.69, 95% CI: 1.93-3.73, respectively) and 1-year mortality (HR = 2.32, 95% CI: 2.00-2.69 and HR = 2.81, 95% CI: 2.33-3.39, respectively) after adjustment for confounders. Subgroup analysis showed that frailty was only associated with in-hospital mortality in critically ill patients with non-ST-segment elevation myocardial infarction (STEMI) but not STEMI (p for interaction = 0.012). In addition, frailty was associated with 1-year mortality in both STEMI and non-STEMI patients (p for interaction = 0.447). The addition of frailty produced the incremental value over the initial model generated by baseline characteristics for both in-hospital and 1-year mortality.ConclusionFrailty, as assessed by the HFRS, was associated with both in-hospital and 1-year mortality in critical AMI patients. Frailty improves the prediction of short- and long-term mortality in critical AMI patients and may have potential clinical applications.

Project description:Abstract Aims To investigate the additional prognostic value of myocardial work (MW) parameters following acute myocardial infarction (AMI). Methods and results Between 2018 and 2020, 244 patients admitted in the cardiac intensive care unit in Lille University Hospital for AMI were included. One-month following AMI, comprehensive transthoracic echocardiography (TTE) was performed to assess parameters of myocardial function. Patients were then followed for major events (ME): cardiovascular death, heart failure, and unplanned coronary revascularization. At 1-month, half of the population was symptomatic (NYHA ≥ II), and medical therapy was almost optimized (angiotensin-converting enzyme inhibitor/angiotensin 2 receptor blocker in 95.5%, beta-blockers in 96.3%, DAPT in 94.7%, and statins in 97.1%). After a median follow-up of 681 (interquartile range: 538–840) days, ME occurred in 26 patients (10.7%). Patients presenting ME were older (65.5 ± 14.2 vs. 58.1 ± 12.1years, P = 0.005) with a higher prevalence of hypertension (65.4 vs. 36.2%, P = 0.004), more impaired left ventricular (LV) function as assessed by LV ejection fraction (P = 0.07), global longitudinal strain (P = 0.03), or MW parameters [P = 0.01 for global work efficiency (GWE)], and greater LV and left atrium dilatations (P = 0.06 for left ventricular end-diastolic volume index and P = 0.03 for left atrial volume index). After adjustment, GWE was the only TTE parameter independently associated with long-term occurrence of ME (P = 0.02). A GWE value <91% was selected to identify patients at higher ME risk (hazard ratio: 95% confidence interval) = 2.94 (1.36–6.35), P = 0.0041). Conclusion Lower GWE at 1 month after AMI is independently associated with higher ME rates. A GWE <91% can improve the post-AMI patient risk stratification. Graphical Abstract Graphical abstract Flow chart summarizing the prognostic value of global work efficiency (GWE) 1-month after myocardial infarction (MI). GWE <91% was independently associated with adverse events.

Project description:BackgroundThere is limited information about the long-term survival of older patients after myocardial infarction (MI).Methods and resultsCRUSADE (Can rapid risk stratification of unstable angina patients suppress adverse outcomes with early implementation of the ACC/AHA guidelines) was a registry of MI patients treated at 568 US hospitals from 2001 to 2006. We linked MI patients aged ≥65 years in CRUSADE to their Medicare data to ascertain long-term mortality (defined as 8 years post index event). Long-term unadjusted Kaplan-Meier mortality curves were examined among patients stratified by revascularization status. A landmark analysis conditioned on surviving the first year post-MI was conducted. We used multivariable Cox regression to compare mortality risks between ST-segment-elevation myocardial infarction and non-ST-segment-elevation myocardial infarction patients. Among 22 295 MI patients ≥ age 65 years (median age 77 years), we observed high rates of evidence-based medication use at discharge: aspirin 95%, β-blockers 94%, and statins 81%. Despite this, mortality rates were high: 24% at 1 year, 51% at 5 years, and 65% at 8 years. Eight-year mortality remained high among patients who underwent percutaneous coronary intervention (49%), coronary artery bypass graft (46%), and among patients who survived the first year post-MI (59%). Median survival was 4.8 years (25th, 75th percentiles 1.1, 8.5); among patients aged 65-74 years it was 8.2 years (3.3, 8.9) while for patients aged ≥75 years it was 3.1 years (0.6, 7.6). Eight-year mortality was lower among ST-segment-elevation myocardial infarction than non-ST-segment-elevation myocardial infarction patients (53% versus 67%); this difference was not significant after adjustment (hazard ratio 0.94, 95% confidence interval, 0.88-1.00).ConclusionsLong-term mortality remains high among patients with MI in routine clinical practice, even among revascularized patients and those who survived the first year.

Project description:BackgroundPrevious studies have shown that the frailty index based on laboratory tests (FI-Lab) can identify older adults at increased risk of adverse health outcomes. This study aimed to determine whether the FI-Lab is associated with mortality risk and can provide incremental improvements in risk stratification of patients with critical acute myocardial infarction (AMI).Materials and methodsWe conducted a secondary analysis of data from the Medical Information Mart for Intensive Care (MIMIC)-IV database. A 33-item FI-Lab was constructed. Outcomes of interest were in-hospital and 1-year mortality. Logistic regression models were used to investigate the association between the FI-Lab and outcomes. For the assessment of the incremental predictive value, the FI-Lab was added to several risk stratification scoring systems for critically ill patients, and the following indices were calculated: Δ C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI).ResultsOut of 2,159 patients, 477 died in hospital (22.1%), and 898 died during the 1-year follow-up period. After adjustment for confounders, the FI-Lab was associated with increased in-hospital mortality [odds ratio (OR) = 1.06, 95% confidence interval (CI): 1.05-1.07] and 1-year mortality (OR = 1.05, 95% CI: 1.04-1.06) when assessed as a continuous variable (per 0.01-score increase). When assessed as a categorical variable, the FI-Lab was associated with in-hospital mortality (2nd Quartile: OR = 1.89, 95% CI: 1.18-3.03; 3rd Quartile: OR = 3.46, 95% CI: 2.20-5.46; and 4th Quartile: OR = 5.79, 95% CI: 3.61-9.28 compared to 1st Quartile) as well as 1-year mortality (2nd Quartile: OR = 1.66, 95% CI: 1.23-2.24; 3rd Quartile: OR = 2.40, 95% CI: 1.76-3.26; and 4th Quartile: OR = 3.76, 95% CI: 2.66-5.30 compared to 1st Quartile) after adjustment for confounders. The addition of the FI-Lab to all disease severity scores improved discrimination and significantly reclassified in-hospital and 1-year mortality risk.ConclusionThe FI-Lab was a strong predictor of short- and long-term mortality in patients with critical AMI. The FI-Lab improved the ability to predict mortality in patients with critical AMI and therefore might be useful in the clinical decision-making process.

Project description:BackgroundPreclinical data suggest that an acute inflammatory response following myocardial infarction (MI) accelerates systemic atherosclerosis. Using combined positron emission and computed tomography, we investigated whether this phenomenon occurs in humans.Methods and resultsOverall, 40 patients with MI and 40 with stable angina underwent thoracic 18F-fluorodeoxyglucose combined positron emission and computed tomography scan. Radiotracer uptake was measured in aortic atheroma and nonvascular tissue (paraspinal muscle). In 1003 patients enrolled in the Global Registry of Acute Coronary Events, we assessed whether infarct size predicted early (≤30 days) and late (>30 days) recurrent coronary events. Compared with patients with stable angina, patients with MI had higher aortic 18F-fluorodeoxyglucose uptake (tissue-to-background ratio 2.15±0.30 versus 1.84±0.18, P<0.0001) and plasma C-reactive protein concentrations (6.50 [2.00 to 12.75] versus 2.00 [0.50 to 4.00] mg/dL, P=0.0005) despite having similar aortic (P=0.12) and less coronary (P=0.006) atherosclerotic burden and similar paraspinal muscular 18F-fluorodeoxyglucose uptake (P=0.52). Patients with ST-segment elevation MI had larger infarcts (peak plasma troponin 32 300 [10 200 to >50 000] versus 3800 [1000 to 9200] ng/L, P<0.0001) and greater aortic 18F-fluorodeoxyglucose uptake (2.24±0.32 versus 2.02±0.21, P=0.03) than those with non-ST-segment elevation MI. Peak plasma troponin concentrations correlated with aortic 18F-fluorodeoxyglucose uptake (r=0.43, P=0.01) and, on multivariate analysis, independently predicted early (tertile 3 versus tertile 1: relative risk 4.40 [95% CI 1.90 to 10.19], P=0.001), but not late, recurrent MI.ConclusionsThe presence and extent of MI is associated with increased aortic atherosclerotic inflammation and early recurrent MI. This finding supports the hypothesis that acute MI exacerbates systemic atherosclerotic inflammation and remote plaque destabilization: MI begets MI.Clinical trial registrationURL: https://www.clinicaltrials.gov. Unique identifier: NCT01749254.

Dataset Information

Clinical Frailty Scale classes are independently associated with 6-month mortality for patients after acute myocardial infarction.

Aims

Methods and results

Conclusion

Publications

Clinical Frailty Scale classes are independently associated with 6-month mortality for patients after acute myocardial infarction.

Similar Datasets

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