Renaissance of Modified Charlson Comorbidity Index in Prediction of Short- and Long-Term Survival After Liver Transplantation?

An Integrative Review of Frailty, Patient Mortality and Graft Failure in Solid Organ Transplant

IntroductionCharacteristics and the impact of frailty on adult solid organ transplant recipients have not been clearly described. The purpose of this integrative review was to identify characteristics of frailty and associations between frailty and patient mortality and graft failure in adult solid organ transplant recipients.MethodsAn integrative literature review was performed using Cooper's integrative methodology. PubMed, Excerpta Medica, and the Cumulative Index of Nursing and Allied Health Literature databases were searched using the terms frailty and transplant. Inclusion criteria were primary research reports, written in English, focusing on adult solid organ transplant recipients, and including graft or patient survival outcomes.ResultsThe review included 35 articles, were largely retrospective, and published between 2015 and 2023 in 11 different countries. Most studies were single-center studies that were not theory-based, and liver transplant recipients were highly represented. Males outnumbered females in the majority of studies and White race was represented in half of the studies. Most studies used one strategy to measure frailty, and modified versions of the Physical Frailty Phenotype were the measurement used most often. Of the 35 articles that investigated the association of frailty with patient mortality, 44 measures were used, and of those, 32 showed a significant association. For graft failure, of the 10 studies included, half showed a significant association between frailty and graft failure.ConclusionThis integrative review offers insights into the characteristics and the association between frailty, patient mortality, and graft failure.

[Abdominal organ transplantation in multimorbid patients]

Patients with an indication for transplantation of abdominal organs often suffer from terminal organ failure with a relevant number of comorbidities. This can be complicated by acute and underlying disease-related events or age-related comorbidities. The diagnostic assignment of symptoms is difficult and the available treatment options have to be adapted. During the evaluation, the waiting time for suitable donor organs and immediately prior to surgery, the treatment team, consisting of the referring physician and the interdisciplinary transplantation team needs to decide whether the transplantation can be performed.

Impact of Pretransplant Diabetes on Outcomes After Liver Transplantation: An Updated Meta-analysis With Systematic Review

BACKGROUND

Preliver transplant diabetes mellitus (pre-LT DM) is a common comorbidity in LT recipients associated with poorer post-transplant survival. However, its relationship with other important outcomes, including cardiovascular and renal outcomes, remains unclear. This meta-analysis aims to provide an updated analysis of the impact of pre-LT DM on key post-LT outcomes.

METHODS

A search was conducted in Medline and Embase databases for articles comparing the post-transplant outcomes between patients with and without pre-LT DM. Pairwise analysis using random effects with hazard ratios (HRs) was used to assess the longitudinal post-LT impacts of pre-LT DM. In the absence of HR, pooled odds ratios analysis was conducted for secondary outcomes.

RESULTS

Forty-two studies involving 77,615 LT recipients were included in this analysis. The pooled prevalence of pre-LT DM amongst LT recipients was 24.79%. Pre-LT DM was associated with significantly lower overall survival (HR, 0.65; 95% confidence interval, 0.52-0.81; P <0.01) and significantly increased cardiovascular disease-related mortality (HR, 1.78; 95% confidence interval, 1.11-2.85; P =0.03). Meta-regression of other patient characteristics identified Asian ethnicity and hypertension to be significant predictors of worse overall survival, whereas African-American ethnicity was associated with significantly improved overall survival in patients with pre-LT DM. Further analysis of secondary outcomes revealed pre-LT DM to be a significant predictor of post-LT cardiovascular events and end-stage renal disease.

CONCLUSIONS

The present study illustrates the impact of pre-LT DM on post-LT survival, and cardiovascular and renal outcomes and provides a sound basis for revision of preoperative management of pre-LT DM.

Machine learning-based models for prediction of the risk of stroke in coronary artery disease patients receiving coronary revascularization

BACKGROUND

To construct several prediction models for the risk of stroke in coronary artery disease (CAD) patients receiving coronary revascularization based on machine learning methods.

METHODS

In total, 5757 CAD patients receiving coronary revascularization admitted to ICU in Medical Information Mart for Intensive Care IV (MIMIC-IV) were included in this cohort study. All the data were randomly split into the training set (n = 4029) and testing set (n = 1728) at 7:3. Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO) regression model were applied for feature screening. Variables with Pearson correlation coefficient<9 were included, and the regression coefficients were set to 0. Features more closely related to the outcome were selected from the 10-fold cross-validation, and features with non-0 Coefficent were retained and included in the final model. The predictive values of the models were evaluated by sensitivity, specificity, area under the curve (AUC), accuracy, and 95% confidence interval (CI).

RESULTS

The Catboost model presented the best predictive performance with the AUC of 0.831 (95%CI: 0.811-0.851) in the training set, and 0.760 (95%CI: 0.722-0.798) in the testing set. The AUC of the logistic regression model was 0.789 (95%CI: 0.764-0.814) in the training set and 0.731 (95%CI: 0.686-0.776) in the testing set. The results of Delong test revealed that the predictive value of the Catboost model was significantly higher than the logistic regression model (P<0.05). Charlson Comorbidity Index (CCI) was the most important variable associated with the risk of stroke in CAD patients receiving coronary revascularization.

CONCLUSION

The Catboost model was the optimal model for predicting the risk of stroke in CAD patients receiving coronary revascularization, which might provide a tool to quickly identify CAD patients who were at high risk of postoperative stroke.

Validation of a comorbidity questionnaire in patients with neurological disorders

Rational

Several tools exist to assess comorbidities in neurological disorders, the most widely used being the Charlson Comorbidity Index (CCI), but it has several limitations. The Comorbidity and General Health Questionnaire (CGHQ) is a newly designed tool, which includes additional comorbidities associated with health-related quality of life (HR-QOL) and outcomes in neurological disorders.

Aims and objectives

To assess the feasibility and validity of the CGHQ in patients with neurological disease.

Method

Two hundred patients attending a general neurological clinic were invited to complete the CGHQ along with the EQ-5D-5L questionnaire. The CCI was simultaneously completed by the assessor. CGHQ comorbidity scores were compared with CCI, symptom burden and EQ-5D-5L scores.

Results

The CGHQ captured 22 additional comorbidities not included on the CCI and more comorbidities were endorsed on the CGHQ. The CGHQ correlated weakly to moderately with CCI comorbidity scores. While both the CGHQ and CCI correlated negatively with the EQ-5D-5L Visual Analogue Scale, only the CGHQ correlated negatively with the EQ-5D-5L summary index. The CGHQ but not the CCI correlated strongly and positively with symptom burden scores.

Conclusion

The CGHQ allows a more comprehensive assessment of comorbidities than the CCI and better correlates with patients' overall symptom burden and HR-QOL in neurological patients.

Modified Charlson comorbidity index as a survival prediction tool for older patients after liver transplantation

Purpose

An increasing number of older patients now undergo liver transplantation (LT). Although the overall outcomes in older patients are not different from those of younger patients, there is no tool to predict LT prognosis in older patients. We hypothesized that a modified Charlson comorbidity index (mCCI) and 5-factor modified frailty index (mFI-5) can predict outcomes in older patients after LT.

Methods

This retrospective study included 155 patients (aged >65 years) who underwent LT at Seoul National University Hospital. The recipients were subcategorized into 2 groups based on the mCCI score and mFI-5: the low (0-1) and high (2-5) mCCI groups, and low (≤0.4) and high (>0.4) mFI-5 groups. The independent effect of each variable on post-LT survival was determined using the mCCI subgroup, age at transplantation, sex, Child-Turcotte-Pugh score, model for end-stage liver disease (MELD) score, and mFI-5 subgroup.

Results

The high-mCCI group (41 patients) showed significantly lower 1- and 3-month and 1-, 3-, and 5-year survival than the low-mCCI group. Using the Cox regression model, the mCCI, sex, and MELD score remained significant. The mFI-5 was not a significant factor to predict patients' survival.

Conclusion

The mCCI and MELD scores could be used to predict post-LT survival in older patients.