Evaluation of prognostic indices in elderly hospitalized patients

Validation and Comparison of Four Mortality Prediction Models in a Geriatric Ward in China

Purpose

The efficacy of mortality risk prediction models among older patients in China remains uncertain. We aimed to validate and compare the performances of the Walter Index, Geriatric Prognostic Index (GPI), Charlson Comorbidity Index (CCI), and FRAIL Scale in predicting 1-year all-cause mortality post-discharge in geriatric inpatients in China.

Patients and Methods

This study was conducted at a geriatric ward of a tertiary Hospital in Beijing, including patients aged 70 years or older with a documented comprehensive geriatric assessment, discharged between January 1, 2016, and December 31, 2021. Patients with a hospital stay ≤24 h or >60 days were excluded. All-cause mortality data within one year of discharge were collected from medical files and telephone interviews between August 2022 and February 2023. Multiple imputation, Logistic regression analysis, Brier scores, C-statistics, Hosmer-Lemeshow goodness-of-fit-test, and calibration plots were employed for statistical analysis.

Results

We included 832 patients with a median (interquartile range) age of 77 (74-82) years. One-hundred patients (12.0%) died within one year. After adjusting for covariates-marital status, social support, cigarette use, length of stay, number of medications, hemoglobin levels, handgrip strength, and Short Physical Performance Battery-CCI scores of 3-4 and >4, and increased Walter Index, GPI, and FRAIL Scale scores were significantly associated with 1-year mortality risk. The Brier scores varied from 0.07 (Walter Index) to 0.10 (FRAIL Scale). The C-statistic ranged from 0.74 (95% confidence interval, 0.69-0.78) for FRAIL Scale to 0.88 (95% confidence interval, 0.84-0.91) for the Walter Index. Calibration curves showed that the Walter Index, GPI, and FRAIL Scale were well calibrated, while the CCI was poor.

Conclusion

Combining the Brier score, discrimination and calibration, the Walter Index was confirmed for the first time to be the best model to predict the 1-year mortality risk of geriatric inpatients in China among the four models.

The prognostic value of the NECPAL instrument, Palliative Prognostic Index, and PROFUND index in elderly residents of nursing homes with advanced chronic condition

BACKGROUND

It is essential to assess the need for palliative care and the life prognosis of elderly nursing home residents with an advanced chronic condition, and the NECPAL ICO-CCOMS©4.0 prognostic instrument may be adequate for both purposes. The objective of this study was to examine the predictive capacity of NECPAL, the Palliative Prognosis Index, and the PROFUND index in elderly residents with advanced chronic condition with and without dementia, comparing their results at different time points.

METHODS

This prospective observational study was undertaken in eight nursing homes, following the survival of 146 residents with advanced chronic condition (46.6% with dementia) at 3, 6, 12, and 24 months. The capacity of the three instruments to predict mortality was evaluated by calculating the area under the receiver operating characteristic curve (AUC), with 95% confidence interval, for the global population and separately for residents with and without dementia.

RESULTS

The mean age of residents was 84.63 years (± 8.989 yrs); 67.8% were female. The highest predictive capacity was found for PROFUND at 3 months (95%CI: 0.526-0.756; p = 0.016), for PROFUND and NECPAL at 12 months (non-significant; AUC > 0.5), and NECPAL at 24 months (close-to-significant (AUC = 0.624; 95% CI: 0.499-0.750; p = 0.053). The highest capacity at 12 months was obtained using PROFUND in residents with dementia (AUC = 0.698; 95%CI: 0.566-0.829; p = 0.003) and NECPAL in residents without dementia (non-significant; AUC = 0.649; 95%CI: 0.432-0.867; p = 0.178). Significant differences in AUC values were observed between PROFUND at 12 (p = 0.017) and 24 (p = 0.028) months.

CONCLUSIONS

PROFUND offers the most accurate prediction of survival in elderly care home residents with advanced chronic condition overall and in those with dementia, especially over the short term, whereas NECPAL ICO-CCOMS©4.0 appears to be the most useful to predict the long-term survival of residents without dementia. These results support early evaluation of the need for palliative care in elderly care home residents with advanced chronic condition.

Identification and Prognostication of End-of-Life State Using a Japanese Guideline-Based Diagnostic Method: A Diagnostic Accuracy Study

Purpose

Prognostic uncertainty can be a barrier to providing palliative care. Accurate prognostic estimation for patients at the end of life is challenging. This study aimed to evaluate the accuracy of end-of-life diagnosis using our unique diagnostic method.

Patients and Methods

A retrospective longitudinal observational study was conducted through collaboration among three medical facilities in a rural super-aged community in Japan. In 2007, we established a unique end-of-life diagnostic process comprising (1) physicians' judgement, (2) disclosure to patients, and (3) discussion at an end-of-life case conference (EOL-CC), based on Japanese end-of-life-related guidelines. Research subjects were consecutive patients discussed in EOL-CC between January 1, 2010, and September 30, 2017. The primary outcome was mortality within 6 months after the initial EOL-CC decision. Sensitivity, specificity, and diagnostic odds ratio were calculated using EOL-CC diagnosis (end-of-life or non-end-of-life) as an index test and overall survival (<6 months or ≥6 months) as a reference standard.

Results

In total, 315 patients were eligible for survival analysis (median age 89, range 54-107). The study population was limited to patients with severe conditions such as advanced cancer, organ failures, advanced dementia with severe deterioration in functioning. EOL-diagnosis by our methods was associated with much lower survival rate at 6 months after EOL-CC than non-EOL-diagnosis (6.9% vs 43.5%; P < 0.001). Of the patients, 297 were eligible for diagnostic accuracy analysis (median age 89, range 54-107). The EOL-diagnosis showed high sensitivity (0.95; 95% confidence interval [CI] 0.92-0.97) but low specificity (0.35; 95% CI 0.20-0.53) against the outcomes. It also showed a high diagnostic odds ratio (10.32; 95% CI 4.08-26.13).

Conclusion

The diagnostic process using the Japanese end-of-life guidelines had tolerable accuracy in identification and prognostication of end of life.

Mortality risk factors in elderly patients in intensive care without limitation of therapeutic effort

OUTCOME

To determine mortality prognostic factors in elderly patients who are admitted to intensive care units (ICUs) due to acute critical illness.

DESIGN

A prospective cohort study was carried out.

SETTING

A polyvalent Intensive Care Unit at a University Hospital in Argentina.

PATIENTS OR PARTICIPANTS

We included 249 patients over 65years of age who were consecutively admitted to the ICU and required mechanical ventilation for more than 48hours, between January 2011 and December 2012. Patients with degenerative neurological disease, limitation of therapeutic effort or on chronic mechanical ventilation were excluded.

PRINCIPAL VARIABLES OF INTEREST

In-hospital mortality, comorbidity (Charlson index), APACHEII score, and pre-acute illness status were recorded: nutritional status (subjective global assessment), functionality (activities of daily living [ADL] and Barthel index), cognitive abilities (Short Reporting Questionnaire on Cognitive Decline in the Elderly [S_IQCODE]) and quality of life (EQ-5D).

RESULTS

The in-hospital mortality rate was 52%. Logistic regression analysis, after adjusting for APACHEII score and age, identified the following independent variables associated to mortality: male gender (OR: 2.46, 95%CI: 1.37-4.42), moderate malnutrition (OR: 2.07, 95%CI: 1.09-3.94), severe malnutrition (OR: 2.20, 95%CI: 1.06-4.59), and ADL<6 (OR: 2.35, 95%CI: 1.16-4.75).

CONCLUSIONS

In our study, chronological age was not associated to in-hospital mortality. However, loss of functional independence (assessed by ADL) and malnourishment were shown to be strong prognostic factors; knowing these baseline characteristics from ICU admission would be useful when making decisions regarding the intensity of treatment.