Development of an Electronic Frailty Index for Predicting Mortality and Complications Analysis in Pulmonary Hypertension Using Random Survival Forest Model

Impact of diabetes mellitus on mortality in pulmonary hypertension: A systematic review and meta-analysis

BACKGROUND

Pulmonary hypertension (PH) is a progressive disease characterized by endothelial dysfunction and vascular remodeling and is a leading cause of mortality worldwide. Although it is independently associated with multiple comorbidities, the impact of diabetes mellitus (DM) on mortality in patients with PH remains uncertain. To address this issue, we conducted a systematic review and meta-analysis to investigate the effect of DM on survival in patients with pulmonary hypertension.

AIM

To investigate the impact of diabetes mellitus on mortality in pulmonary hypertension patients.

METHODS

We conducted a comprehensive search of four major electronic bibliographic databases like PubMed, Google Scholar, Scopus, and Embase, and identified 106 relevant studies, out of 1561 articles, published since the year 2000 for full-text review. Fourteen retrospective and prospective cohort studies that compared survival between patients with DM and those without DM in the context of PH were deemed eligible for inclusion in our meta-analysis. The study was registered on PROSPERO with the identifier CRD42023390232.

RESULTS

A total of 116455 patients with PH were included in the meta-analysis, of whom 41228 suffered from DM and 75227 did not. The results of our meta-analysis indicate an elevated mortality rate among PH patients with diabetes mellitus in comparison to those without DM [odds ratio (OR) = 1.40, 95%CI: 1.15-1.70, P = 0.0006]. The meta-regression analysis unveiled a statistically significant negative association between mean age and effect size (coefficient = -0.036, P value = 0.018). Conversely, a statistically significant positive association was detected between female proportion and effect size (coefficient = 0.000, P value < 0.001).

CONCLUSION

Our meta-analysis, which included approximately 116500 PH patients, revealed that the presence of diabetes mellitus was associated with increased odds of mortality when compared to non-diabetic patients. The meta-regression analysis indicates that studies with older participants and lower proportions of females tend to exhibit smaller effect sizes. Clinically, these findings underscore the importance of incorporating diabetes status into the risk stratification of patients with PH with more aggressive monitoring and early intervention to improve prognosis potentially.

Development and validation of an electronic frailty index in a national health maintenance organization

BACKGROUND

Frailty constitutes a major factor that puts the elderly at risk of health and functional deterioration.

OBJECTIVES

To develop and validate an Electronic Frailty Index based on electronic data routinely collected in the HMO.

STUDY DESIGN AND SETTING

A retrospective cohort of the HMO members.

PARTICIPANTS

120,986 patients, aged 65 years and over at the beginning of 2023.

PREDICTORS

A cumulative frailty index including 36 medical, functional, and social deficits.

OUTCOMES

One-year all-cause mortality or hospitalization.

STATISTICAL ANALYSIS

One-year hazard ratios were estimated for composite outcome of mortality or hospitalization using multivariable hierarchical Cox regression.

RESULTS

The mean EFI score increased with the Social Security Nursing Benefit. Compared to fit patients, mild, moderate, and severe frailty patients had 2.07, 3.35, and 4.4-fold increased risks of mortality or hospitalization, after controlling for covariates.

CONCLUSIONS

The findings showed that the Electronic Frailty Index version we created is valid in predicting mortality or hospitalization. In addition, the Electronic Frailty Index converged with an independent measurement produced by National Social Security.

Prevalence of frailty among chronic respiratory disease patients

BACKGROUND

Although frailty is one of the aging syndromes, it can occur at a younger age and in individuals with organ diseases. Identifying frailty and pre-frailty in patients with chronic respiratory diseases (CRDs) is an emerging assessment in the field of pulmonary medicine and rehabilitation. The aim of this study was to find out the prevalence of frailty among chronic respiratory disease patients.

METHODS

A single centre cross-sectional survey study with a total population of 381 patients, adults aged 18-90 years presenting to the pulmonology OPD was included based on the inclusion and exclusion criteria. Primary data collected were demographics, medical history, including comorbidities, use of long-term oxygen therapy (LTOT), BiPAP (Bilevel Positive Airway Pressure), previous hospital admissions, medication history and frailty assessment were done using the Fried frailty index.

RESULTS

Univariate analysis showed that sex, ECHO abnormality, patients using LTOT, BiPAP, home nebulizers and patients who did not attend the pulmonary rehabilitation programme had a significant association with frailty. Multivariate analysis showed that female sex, LTOT use and older age were significantly associated with frailty.

CONCLUSION

Frailty is frequent in CRD patients regardless of age. The prevalence of frailty has an association with female sex, patients using LTOT, and home BiPAP.

Machine learning in a real-world PFO study: analysis of data from multi-centers in China

PURPOSE

The association of patent foreman ovale (PFO) and cryptogenic stroke has been studied for years. Although device closure overall decreases the risk for recurrent stroke, treatment effects varied across different studies. In this study, we aimed to detect sub-clusters in post-closure PFO patients and identify potential predictors for adverse outcomes.

METHODS

We analyzed patients with embolic stroke of undetermined sources and PFO from 7 centers in China. Machine learning and Cox regression analysis were used.

RESULTS

Using unsupervised hierarchical clustering on principal components, two main clusters were identified and a total of 196 patients were included. The average age was 42.7 (12.37) years and 64.80% (127/196) were female. During a median follow-up of 739 days, 12 (6.9%) adverse events happened, including 6 (3.45%) recurrent stroke, 5 (2.87%) transient ischemic attack (TIA) and one death (0.6%). Compared to cluster 1 (n = 77, 39.20%), patients in cluster 2 (n = 119, 60.71%) were more likely to be male, had higher systolic and diastolic blood pressure, higher body mass index, lower high-density lipoprotein cholesterol and increased proportion of presence of atrial septal aneurysm. Using random forest survival (RFS) analysis, eight top ranking features were selected and used for prediction model construction. As a result, the RFS model outperformed the traditional Cox regression model (C-index: 0.87 vs. 0.54).

CONCLUSIONS

There were 2 main clusters in post-closure PFO patients. Traditional cardiovascular profiles remain top ranking predictors for future recurrence of stroke or TIA. However, whether maximizing the management of these factors would provide extra benefits warrants further investigations.