Frailty index based on laboratory tests improves prediction of short-and long-term mortality in patients with critical acute myocardial infarction

Impact of frailty assessment on outcomes in critical acute myocardial infarction: Insights from the hospital frailty risk measure (HFRM)

BACKGROUND

Frailty impacts outcomes in critical Acute Myocardial Infarction (AMI). This study evaluates three Hospital Frailty Risk Measure (HFRM) formats-continuous score, 8 risk groups, and binary classification-for predicting clinical outcomes.

METHODS

Using 2129 critical AMI patients' data from MIMIC-IV, logistic and COX regression models assessed associations between HFRM formats and outcomes (ICU mortality, in-hospital mortality, discharge with nursing support, one-year mortality), adjusted for age, gender, smoking, and NSTEMI.

RESULTS

All HFRM formats consistently predicted adverse outcomes. The continuous score showed increased adjusted odds/hazard ratios for ICU mortality (OR 1.289, 95 % CI:1.065-1.516), in-hospital mortality (OR 1.343, 95 % CI:1.161-1.554), nursing support discharge (2.389, 95 % CI: 1.960-2.912), and one-year mortality (1.709, 95 % CI:1.533-1.904). The binary measure (groups 4-8 as frail) demonstrated higher adjusted risks for all outcomes except ICU mortality.

CONCLUSION

HFRM effectively predicts adverse outcomes in critical AMI. The binary classification offers robust risk stratification, underscoring frailty assessment's role in personalized care planning.

Impact of Laboratory-Derived Frailty Index on Clinical Outcomes in Critical Care Patients with COPD: A Retrospective Analysis Using the MIMIC-IV Database

Background and Objective

Chronic obstructive pulmonary disease (COPD) is associated with high mortality and morbidity worldwide. Notably, 20% of COPD patients are admitted to the ICU, and among them, there is a 25% mortality rate. Therefore, identifying novel risk factors for effective intervention is crucial for managing COPD. This research aims to investigate the relationship between the physiological and laboratory - based frailty index (FI - Lab) and mortality among critical care patients with COPD.

Methods

The FI-Lab was constructed using 33 items. This index was used to quantify the frailty level of critically ill patients with COPD in the ICU. We analyzed data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. Our study group consisted of 6825 COPD patients with an average age of 65.8 ± 14.8 years, and 52.2% of them were male. The primary outcomes were 30-day and 90-day mortality rates. Multivariable Cox regression was used for statistical analysis. Propensity score matching (PSM) was applied to ensure robustness.

Results

In total, 6825 patients were included in the study, and the PSM cohort had 1282 patients. Both continuous and categorical increases in the FI-Lab were significantly associated with higher mortality (P < 0.001). These results were further validated by PSM. Subgroup analyses corroborated these findings. Restricted cubic splines illustrated a linear relationship between the FI-Lab and mortality. Kaplan-Meier analysis revealed significantly reduced 90-day survival with increasing FI-Lab (Log rank test, P < 0.001).

Conclusion

Elevated FI-Lab is an independent predictor of increased mortality in critical care patients with COPD. Further randomized controlled trials are required to confirm these results and refine patient management strategies.

Association between a laboratory-based frailty index and mortality of critically ill patients with acute pancreatitis: a retrospective study

Background

Acute pancreatitis (AP) is associated with significant global mortality and morbidity. Frailty, which can be assessed through clinical indicators and life history, is known to impact adverse outcomes across different medical conditions. The frailty index derived from laboratory tests (FI-Lab) is a novel approach to the quantification of frailty. This study sought to investigate the relationship between the FI-Lab and mortality among critically ill patients with AP.

Methods

We utilized data on patients diagnosed with AP from the Medical Information Mart for Intensive Care-IV database. The FI-Lab was calculated using a specific set of laboratory parameters indicative of physiological disturbances. The primary outcomes examined were 30-day and 90-day mortality rates. Multivariate Cox regression was used for the statistical analysis, with adjustments for age, gender, Acute Physiology and Chronic Health Evaluation II scores, and other variables. Propensity matching scores were used to ensure the robustness of our findings.

Results

A total of 1,116 AP patients were included in the analysis (mean age = 58.4 years; 57.9% male). Each 0.1 increment of FI-Lab was found to increase the risks of 30-day and 90-day mortality by 30% (hazard ratio (HR) = 1.30, p < 0.001 for both). The propensity score matching (PSM) analysis validated these results. The FI-Lab demonstrated an association with acute kidney injury and the requirement for continuous renal replacement therapy. However, these associations were not significant after the PSM analysis.

Conclusion

An elevated FI-Lab was associated with higher mortality rates among critically ill AP patients. Randomized controlled trials are needed to confirm these findings and to explore their clinical implications.

The stress hyperglycemia ratio as a predictor of short- and long-term mortality in patients with acute brain injury: a retrospective cohort study

Background

This study examines the Stress Hyperglycemia Ratio (SHR) as a predictor of mortality in acute brain injury (ABI) patients using the MIMIC-IV v3. 1 database.

Methods

In this retrospective cohort study of 2,423 ABI patients, SHR was calculated as SHR = [Admission blood glucose (mg/dL)] / [28.7 × HbA1c (%) - 46.7]. Mortality outcomes included ICU, in-hospital, 30, 60, 90, and 365-day mortality. Cox regression models adjusted for covariates assessed the association between SHR and mortality risk, with restricted cubic splines confirming linearity. Predictive performance was evaluated using ROC curves, incorporating SHR, Glasgow Coma Scale (GCS), and first-day ventilation status.

Results

SHR was significantly associated with mortality across all outcomes, showing a linear relationship. Adjusted hazard ratios (HR) for in-hospital and ICU mortality were 1.18 (95% CI: 1.06-1.32, p = 0.003) and 1.16 (95% CI: 1.02-1.32, p = 0.029), respectively. Dichotomized SHR indicated increased in-hospital mortality risk (HR: 1.44, 95% CI: 1.13-1.83, p = 0.003). Combining SHR with GCS and ventilation status improved predictive accuracy, achieving AUCs of 0.817 for ICU mortality and 0.788 for in-hospital mortality. Robustness was supported by E-values of 2.24 and 2.37 for in-hospital and ICU mortality.

Conclusion

SHR independently predicts short- and long-term mortality in ABI patients, with enhanced utility when combined with GCS and ventilation status, supporting its role in clinical risk stratification.

Relationship between the laboratory test-based frailty index and overall mortality in critically ill patients with acute pancreatitis: a retrospective study based on the MIMIC-IV database

Background and aims

The frailty index, based on laboratory assessments, helps identify individuals at risk for adverse health outcomes. However, its relationship with overall mortality in acute pancreatitis patients in ICUs remains unclear. This study aims to investigate the association between the frailty index and all-cause mortality and assess its prognostic value for these patients.

Methods

We carried out a retrospective observational investigation utilizing data from the Medical Information Mart for Intensive Care IV (MIMIC-IV 2.2) database. Extract data from the database for all ICU patients (first-time ICU admissions, age ≥ 18 years) who meet the diagnostic criteria for acute pancreatitis. The frailty index derived from laboratory tests (FI-lab) encompassed three vital sign indicators and 30 laboratory test indicators. Patients were categorized into four groups based on quartiles of the FI-lab score. To assess the differences in 28-day all-cause mortality among these groups, we employed Kaplan-Meier analysis, whereas the relationship between FI-lab scores and 28-day mortality was explored through Cox proportional hazards analysis. In addition, we applied Harrell's C statistic, Integrated Discrimination Improvement (IDI), and Net Reclassification Improvement (NRI) to assess the additional predictive capability of FI-lab scores compare to traditional disease severity metrics.

Results

The study included a total of 741 patients (all age ≥ 18 years, 19.84% age > 75 years, 41.16% Female). The Kaplan-Meier analysis demonstrated that individuals with elevated FI-lab scores exhibited a significantly heightened risk of all-cause mortality (log-rank p < 0.0001). The multivariate Cox regression analysis suggested that treating FI-lab as a continuous variable (per 0.01 increment) was linked to an increased risk of 28-day all-cause mortality [hazard ratio (HR) 1.072, 95% confidence interval (CI) (1.055-1.089), p < 0.001]. Moreover, when FI-lab was analyzed as a categorical variable, patients in the fourth quartile of FI-lab had a notably greater risk of 28-day all-cause mortality in comparison to those in the first quartile [HR 9.933, 95% CI (4.676-21.104), p < 0.001]. Additionally, the integration of FI-lab scores with conventional disease severity scores improved the predictive performance for 28-day mortality.

Conclusion

In patients in the ICU who have been diagnosed with acute pancreatitis, the FI-lab score functions as a reliable indicator of short-term mortality. Early detection of patients at high risk for acute pancreatitis through the implementation of the FI-lab score, along with prompt interventions, is essential for enhancing these individuals' prognoses.

Association between frailty index based on laboratory tests and all-cause mortality in critically ill patients with heart failure

BACKGROUND

The frailty index based on laboratory tests (FI-lab) can identify individuals at increased risk for adverse health outcomes. The association between the FI-lab and all-cause mortality in patients with heart failure (HF) in the intensive care unit (ICU) remains unknown. This study aimed to determine the correlation between FI-lab and all-cause mortality to evaluate the impact of FI-lab on the prognosis of critically ill patients with HF.

METHODS

This retrospective observational study utilized data extracted from the Medical Information Mart for Intensive Care IV database. The FI-lab, which consists of 33 laboratory tests, was constructed. Patients were then grouped into quartiles (Q1-Q4) based on their FI-lab scores. Kaplan-Meier analysis was used to compare all-cause mortality among the four groups. A Cox proportional hazard analysis was conducted to examine the association between the FI-lab score and all-cause mortality. The incremental predictive value of adding FI-lab to classical disease severity scores was assessed using Harrell's C statistic, integrated discrimination improvement (IDI) and net reclassification improvement (NRI).

RESULTS

Among 3021 patients, 838 (27.74%) died within 28 days, and 1400 (46.34%) died within a 360 day follow-up period. Kaplan-Meier analysis indicated that patients with higher FI-lab scores had significantly higher risks of all-cause mortality (log-rank P < 0.001). Multivariable Cox regression suggested that FI-lab, evaluated as a continuous variable (for each 0.01 increase), was associated with increased 28 day mortality [hazard ratio (HR) 1.02, 95% confidence interval (CI) (1.01-1.03), P < 0.001] and 360 day mortality [HR 1.02, 95% CI (1.01-1.02), P < 0.001]. When assessed in quartiles, the 28 day mortality risk [HR 1.66, 95% CI (1.28-2.15), P < 0.001] and 360 day mortality risk [HR 1.48, 95% CI (1.23-1.8), P < 0.001] were significantly higher for FI-lab Q4 compared with FI-lab Q1. FI-lab significantly improved the predictive capability of classical disease severity scores for 28 and 360 day mortality.

CONCLUSIONS

In ICU patients diagnosed with HF, the FI-lab is a potent predictor of short-term and long-term mortality in critically ill patients with HF. The active use of FI-lab to identify high-risk groups among critically ill HF patients and initiate timely interventions may have significant value in improving the prognosis of critically ill patients with HF.

Association between arteriosclerosis, hemodynamic indices, and the risk of falls: receiver operating characteristic curve analysis for different indices in older individuals

Objective

This study aimed to assess the risk factors for falls and evaluate the correlation between arteriosclerosis, hemodynamic indices, and the risk of falls in older individuals.

Method

This cross-sectional study included 920 individuals aged 60 and above from the cadre ward of the First Hospital of Jilin University. Data were obtained from the comprehensive geriatric assessment database of the cadre ward. Ankle-brachial indices (ABI) and brachial-ankle pulse wave velocity (baPWV) were measured using an OMRON arteriosclerosis detection device. Hemodynamic indices were assessed using the CSM3100 thoracic impedance hemodynamic detection system. Fall risk was evaluated with the fall risk assessment tool.

Results

Significant differences in age, weight, education, smoking status, alcohol consumption, cognitive impairment, malnutrition, daily living abilities, depressive state, baPWV, ABI (all p < 0.001), systolic pressure, heart rate, cardiac stroke volume, and systemic vascular resistance were observed among the three groups (p = 0.011, p = 0.035, p = 0.005, p = 0.016). Ordinal logistic regression analysis indicated that the probability of an increase in fall risk by one level was 2.069 times higher for each unit decrease in educational background. Additionally, fall risk increased by 2.492 times for each additional year of age, 55.813 times for each unit of weight, 3.208 times for smoking status, 3.610 times for alcohol consumption, 4.665 times for cognitive impairment, 2.247 times for malnutrition, 2.596 times for ABI, 2.092 times for heart rate, and 1.586 times for cardiac stroke volume. The receiver operating characteristic curve analysis for fall risk in older individuals demonstrated that ABI was superior to heart rate and systemic vascular resistance in predicting the occurrence of falls.

Conclusion

Our findings indicate that age, weight, educational background, smoking status, alcohol consumption, cognitive impairment, malnutrition, ABI, systolic blood pressure, heart rate, and cardiac stroke volume are associated with an increased risk of falls in older adults. Moreover, arteriosclerosis and hemodynamic parameters may aid in the early identification of fall risk among older individuals.

The association between frailty and the risk of mortality in critically ill congestive heart failure patients: findings from the MIMIC-IV database

Background

Frailty is a severe, common co-morbidity associated with congestive heart failure (CHF). This retrospective cohort study assesses the association between frailty and the risk of mortality in critically ill CHF patients.

Methods

Eligible patients with CHF from the Medical Information Base for Intensive Care IV database were retrospectively analyzed. The frailty index based on laboratory tests (FI_Lab) index was calculated using 33 variables to assess frailty status. The primary outcomes were in-hospital mortality and one-year mortality. The secondary outcomes were the incidence of acute kidney injury (AKI) and the administration of renal replacement therapy (RRT) in patients with concurrent AKI. Survival disparities among the FI_Lab subgroups were estimated with Kaplan-Meier survival analysis. The association between the FI_Lab index and mortality was examined with Cox proportional risk modeling.

Results

A total of 3273 adult patients aged 18 years and older were enrolled in the study, with 1820 men and 1453 women included. The incidence rates of in-hospital mortality and one-year mortality rate were 0.96 per 1,000 person-days and 263.8 per 1,000 person-years, respectively. Multivariable regression analysis identified baseline FI_Lab > 0.45 as an independent risk factor predicting in-hospital mortality (odds ratio = 3.221, 95% CI 2.341-4.432, p < 0.001) and one-year mortality (hazard ratio=2.152, 95% CI: 1.730-2.678, p < 0.001). In terms of predicting mortality, adding FI_Lab to the six disease severity scores significantly improved the overall performance of the model (all p < 0.001).

Conclusions

We established a positive correlation between the baseline FI_Lab and the likelihood of adverse outcomes in critical CHF patients. Given its potential as a reliable prognostic tool for such patients, further validation of FI_Lab across multiple centers is recommended for future research.

Association of frailty and sarcopenia with short-term mortality in older critically ill patients

BACKGROUND

There is still no study on the use of the SARC-CalF questionnaire for older critically ill patients. Moreover, there is limited evidence on whether a combination of sarcopenia and frailty can provide incremental improvements in risk stratification for older critically ill patients.

METHODS

A total of 653 patients older than 60 years were recruited. We used the clinical frailty scale (CFS) and SARC-CalF questionnaire to assess the frailty status and sarcopenia risk, respectively, of older patients shortly after admission to the ICU. The effect of frailty and sarcopenia risk on ICU mortality and 30-day mortality was evaluated.

RESULTS

A total of 147 (22.5%) patients died in the ICU, and 187 (28.6%) patients died within 30 days after ICU admission. The CFS score was associated with increased ICU mortality [per 1-score increase: odds ratio (OR) = 1.222, 95% confidential interval (CI): 1.003-1.489] and 30-day mortality (per 1-score increase: OR = 1.307, 95% CI: 1.079-1.583). The SARC-CalF score was also associated with increased ICU mortality (per 1-score increase: OR = 1.204, 95% CI: 1.120-1.294) and 30-day mortality (per 1-score increase: OR = 1.247, 95% CI: 1.163-1.337). The addition of the CFS + SARC-CalF score to Acute Physiology and Chronic Health Evaluation (APACHE) II improved discrimination and reclassified ICU and 30-day mortality risk.

CONCLUSIONS

Sarcopenia risk assessed by the SARC-CalF questionnaire provided independent prognostic information for older critically ill patients. A combination of sarcopenia and frailty improved the prediction of mortality for older critically ill patients and thus might be useful in the clinical decision-making process.

The association of a frailty index derived from laboratory tests and vital signs with clinical outcomes in critical care patients with septic shock: a retrospective study based on the MIMIC-IV database

PURPOSE

Frailty is a vulnerable state to stressors due to the loss of physiological reserve as a result of multisystem dysfunction. The physiological and laboratory-based frailty index (FI-Lab), depending on laboratory values and vital signs, is a powerful tool to capture frailty status. The aim of this study was to assess the relationship between FI-Lab and in-hospital mortality in patients with septic shock.

METHODS

Baseline data for patients with sepsis in the intensive care unit were retrieved from the Critical Care Medicine Database (MIMIC-IV, v2.2). The primary outcome was mortality during hospitalization. The propensity score matching (PSM) method was used to analyze the basic conditions during hospitalization between groups.The FI-Lab was analysed for its relationship with in-hospital mortality using logistic regression according to continuous and categorical variables, respectively, and described using the restricted cubic spline (RCS). Survival was compared between groups using Kaplan-Meier (KM) curves. Subgroup analyses were used to improve the stability of the results.

RESULTS

A total of 9219 patients were included. A cohort score of 1803 matched patients was generated after PSM. The analyses showed that non-surviving patients with septic shock in the ICU had a high FI-Lab index (P<0.001). FI-Lab, whether used as a continuous or categorical variable, increased with increasing FI-Lab and increased in-hospital mortality (P<0.001).Subgroup analyses showed similar results. RCS depicts this non-linear relationship. KM analysis shows the cumulative survival time during hospitalisation was significantly lower as FI-Lab increased (log-rank test, P<0.001).

CONCLUSION

Elevated FI-Lab is associated with increased in-hospital mortality in patients with septic shock.

Relationship between the Ratio of Red Cell Distribution Width to Albumin and 28-Day Mortality among Chinese Patients over 80 Years with Atrial Fibrillation

INTRODUCTION

Atrial fibrillation (AF) is a prevalent heart arrhythmia in elderly adults aged 80 years or older. The red cell distribution width (RDW) to albumin ratio has been acknowledged as a reliable prognostic marker for poor outcomes in a variety of disorders. However, there exists limited scientific evidence on the association of RDW to albumin (RAR) with mortality in geriatric individuals with AF.

METHODS

From January 2015 to June 2020, a retrospective study was conducted in a tertiary academic institution that diagnosed 1,141 elderly adults with AF. The RAR value was calculated as the ratio of RDW (%) to albumin (g/dL). The potential association between RAR and cardiovascular mortality and the risk of all-cause mortality within 28 days was evaluated by means of multivariable Cox regression analysis.

RESULTS

The 28-day all-cause and cardiovascular mortality rates were 8.7% and 3.3%, respectively. Increased RAR tertiles were found to be significantly associated with greater all-cause mortality (T1: 1.6%; T2: 6.2%; T3: 18.1%, p < 0.001) and cardiovascular mortality (T1: 0.8%; T2: 2.9%; T3: 6.3%, p < 0.001) using Kaplan-Meier analysis. Continuous RAR had a positive association with all-cause mortality (hazard ratios [HR] = 1.42, 95% confidence interval [CI] 1.23-1.65) and cardiovascular mortality (HR = 1.31, 95% CI: 1.05-1.64), even after accounting for numerous confounding variables. In comparison to the T1 group, individuals with the highest RAR levels displayed a greater risk of all-cause mortality (HR = 2.73, 95% CI: 1.11-6.74) and cardiovascular mortality (HR = 2.59, 95% CI: 0.69-9.78). Increased RAR levels were related to higher rates of cardiovascular and all-cause mortality across almost all subgroups.

CONCLUSION

RAR is independently correlated with 28-day all-cause mortality and cardiovascular mortality in AF-affected individuals aged ≥80.

Association between Frailty Assessed Using Two Electronic Medical Record-Based Frailty Assessment Tools and Long-Term Adverse Prognosis in Older Critically Ill Survivors

OBJECTIVES

Frailty has become an independent risk factor for adverse outcomes in critically ill patients. This study aimed to explore the predictive ability of two electronic medical record-based frailty assessment tools, the Hospital Frailty Risk Score (HFRS) and Frailty Index based on physiological and laboratory tests (FI-lab), for long-term adverse prognosis in older critically ill survivors.

DESIGN

Retrospective observational study.

SETTING AND PARTICIPANTS

9,082 critically ill survivors aged ≥ 65 years.

MEASUREMENTS

The HFRS and the 33-item FI-lab were constructed based on the published literature. Cox and logistic regression models assessed the association between frailty and 1-year mortality and post-discharge care needs.

RESULTS

2,586 patients died within 1 year of follow-up. In fully adjusted models, frailty assessed using both the HFRS (per point, hazard ratio [HR] 1.06, 95% confidential interval [CI] 1.05-1.06; intermediate frailty risk, HR 2.00, 95% CI 1.78-2.25; high frailty risk, HR 3.06, 95% CI 2.68-3.50) and FI-lab (per 0.01 points, HR 1.03, 95% CI 1.03-1.03; intermediate frailty risk, HR 1.59, 95% CI 1.44-1.76; high frailty risk, HR 2.30, 95% CI 2.06-2.57) was associated with mortality. Addition of frailty indicators improved the predictive validity of the Sequential Organ Failure Assessment score for mortality (HFRS alone ∆ C-index 0.034; FI-lab alone ∆ C-index 0.016; HFRS and FI-lab combined ∆ C-index 0.042). The HFRS but not the FI-lab was associated with higher probability of post-discharge care needs.

CONCLUSION

Both the HFRS and FI-lab could independently predict 1-year mortality in older critically ill survivors. Adding the HFRS to the SOFA score model improved it more than adding the FI-lab. The greatest improvement was achieved when both frailty indicators were used together. These findings suggest that electronic medical record-based frailty assessment methods can be useful tools for predicting long-term outcomes in older critically ill patients.