Deaths in dementia: a scoping review of prognostic variables

Study protocol for the development and validation of a clinical prediction tool to estimate the risk of 1-year mortality among hospitalized patients with dementia

BACKGROUND

Patients with dementia and their caregivers could benefit from advance care planning though may not be having these discussions in a timely manner or at all. A prognostic tool could serve as a prompt to healthcare providers to initiate advance care planning among patients and their caregivers, which could increase the receipt of care that is concordant with their goals. Existing prognostic tools have limitations. We seek to develop and validate a clinical prediction tool to estimate the risk of 1-year mortality among hospitalized patients with dementia.

METHODS

The derivation cohort will include approximately 235,000 patients with dementia, who were admitted to hospital in Ontario from April 1st, 2009, to December 31st, 2017. Predictor variables will be fully prespecified based on a literature review of etiological studies and existing prognostic tools, and on subject-matter expertise; they will be categorized as follows: sociodemographic factors, comorbidities, previous interventions, functional status, nutritional status, admission information, previous health care utilization. Data-driven selection of predictors will be avoided. Continuous predictors will be modelled as restricted cubic splines. The outcome variable will be mortality within 1 year of admission, which will be modelled as a binary variable, such that a logistic regression model will be estimated. Predictor and outcome variables will be derived from linked population-level healthcare administrative databases. The validation cohort will comprise about 63,000 dementia patients, who were admitted to hospital in Ontario from January 1st, 2018, to March 31st, 2019. Model performance, measured by predictive accuracy, discrimination, and calibration, will be assessed using internal (temporal) validation. Calibration will be evaluated in the total validation cohort and in subgroups of importance to clinicians and policymakers. The final model will be based on the full cohort.

DISCUSSION

We seek to develop and validate a clinical prediction tool to estimate the risk of 1-year mortality among hospitalized patients with dementia. The model would be integrated into the electronic medical records of hospitals to automatically output 1-year mortality risk upon hospitalization. The tool could serve as a trigger for advance care planning and inform access to specialist palliative care services with prognosis-based eligibility criteria. Before implementation, the tool will require external validation and study of its potential impact on clinical decision-making and patient outcomes.

TRIAL REGISTRATION

NCT05371782.

Outcomes and cost analysis of patients with dementia in the intensive care unit: a population-based cohort study

BACKGROUND

Dementia is a neurological syndrome affecting the growing elderly population. While patients with dementia are known to require significant hospital resources, little is known regarding the outcomes and costs of patients admitted to the intensive care unit (ICU) with dementia.

METHODS

We conducted a population-based retrospective cohort study of patients with dementia admitted to the ICU in Ontario, Canada from 2016 to 2019. We described the characteristics and outcomes of these patients alongside those with dementia admitted to non-ICU hospital settings. The primary outcome was hospital mortality but we also assessed length of stay (LOS), discharge disposition, and costs.

RESULTS

Among 114,844 patients with dementia, 11,341 (9.9%) were admitted to the ICU. ICU patients were younger, more comorbid, and had less cognitive impairment (81.8 years, 22.8% had ≥ 3 comorbidities, 47.5% with moderate-severe dementia), compared to those in non-ICU settings (84.2 years, 15.0% had ≥ 3 comorbidities, 54.1% with moderate-severe dementia). Total mean LOS for patients in the ICU group was nearly 20 days, compared to nearly 14 days for the acute care group. Mortality in hospital was nearly three-fold greater in the ICU group compared to non-ICU group (22.2% vs. 8.8%). Total healthcare costs were increased for patients admitted to ICU vs. those in the non-ICU group ($67,201 vs. $54,080).

CONCLUSIONS

We find that patients with dementia admitted to the ICU have longer length of stay, higher in-hospital mortality, and higher total healthcare costs. As our study is primarily descriptive, future studies should investigate comprehensive goals of care planning, severity of illness, preventable costs, and optimizing quality of life in this high risk and vulnerable population.

Predicting mortality in patients diagnosed with advanced dementia presenting at an acute care hospital: the PROgnostic Model for Advanced DEmentia (PRO-MADE)

BACKGROUND

Challenges in prognosticating patients diagnosed with advanced dementia (AD) hinders timely referrals to palliative care. We aim to develop and validate a prognostic model to predict one-year all-cause mortality (ACM) in patients with AD presenting at an acute care hospital.

METHODS

This retrospective cohort study utilised administrative and clinical data from Tan Tock Seng Hospital (TTSH). Patients admitted to TTSH between 1st July 2016 and 31st October 2017 and identified to have AD were included. The primary outcome was ACM within one-year of AD diagnosis. Multivariable logistic regression was used. The PROgnostic Model for Advanced Dementia (PRO-MADE) was internally validated using a bootstrap resampling of 1000 replications and externally validated on a more recent cohort of AD patients. The model was evaluated for overall predictive accuracy (Nagelkerke's R² and Brier score), discriminative [area-under-the-curve (AUC)], and calibration [calibration slope and calibration-in-the-large (CITL)] properties.

RESULTS

A total of 1,077 patients with a mean age of 85 (SD: 7.7) years old were included, and 318 (29.5%) patients died within one-year of AD diagnosis. Predictors of one-year ACM were age > 85 years (OR:1.87; 95%CI:1.36 to 2.56), male gender (OR:1.62; 95%CI:1.18 to 2.22), presence of pneumonia (OR:1.75; 95%CI:1.25 to 2.45), pressure ulcers (OR:2.60; 95%CI:1.57 to 4.31), dysphagia (OR:1.53; 95%CI:1.11 to 2.11), Charlson Comorbidity Index ≥ 8 (OR:1.39; 95%CI:1.01 to 1.90), functional dependency in ≥ 4 activities of daily living (OR: 1.82; 95%CI:1.32 to 2.53), abnormal urea (OR:2.16; 95%CI:1.58 to 2.95) and abnormal albumin (OR:3.68; 95%CI:2.07 to 6.54) values. Internal validation results for optimism-adjusted Nagelkerke's R², Brier score, AUC, calibration slope and CITL were 0.25 (95%CI:0.25 to 0.26), 0.17 (95%CI:0.17 to 0.17), 0.76 (95%CI:0.76 to 0.76), 0.95 (95% CI:0.95 to 0.96) and 0 (95%CI:-0.0001 to 0.001) respectively. When externally validated, the model demonstrated an AUC of 0.70 (95%CI:0.69 to 0.71), calibration slope of 0.64 (95%CI:0.63 to 0.66) and CITL of -0.27 (95%CI:-0.28 to -0.26).

CONCLUSION

The PRO-MADE attained good discrimination and calibration properties. Used synergistically with a clinician's judgement, this model can identify AD patients who are at high-risk of one-year ACM to facilitate timely referrals to palliative care.

Development and External Validation of a Mortality Prediction Model for Community-Dwelling Older Adults With Dementia

Importance

Estimating mortality risk in older adults with dementia is important for guiding decisions such as cancer screening, treatment of new and chronic medical conditions, and advance care planning.

Objective

To develop and externally validate a mortality prediction model in community-dwelling older adults with dementia.

Design, Setting, and Participants

This cohort study included community-dwelling participants (aged ≥65 years) in the Health and Retirement Study (HRS) from 1998 to 2016 (derivation cohort) and National Health and Aging Trends Study (NHATS) from 2011 to 2019 (validation cohort).

Exposures

Candidate predictors included demographics, behavioral/health factors, functional measures (eg, activities of daily living [ADL] and instrumental activities of daily living [IADL]), and chronic conditions.

Main Outcomes and Measures

The primary outcome was time to all-cause death. We used Cox proportional hazards regression with backward selection and multiple imputation for model development. Model performance was assessed by discrimination (integrated area under the receiver operating characteristic curve [iAUC]) and calibration (plots of predicted and observed mortality).

Results

Of 4267 participants with probable dementia in HRS, the mean (SD) age was 82.2 (7.6) years, 2930 (survey-weighted 69.4%) were female, and 785 (survey-weighted 12.1%) identified as Black. Median (IQR) follow-up time was 3.9 (2.0-6.8) years, and 3466 (81.2%) participants died by end of follow-up. The final model included age, sex, body mass index, smoking status, ADL dependency count, IADL difficulty count, difficulty walking several blocks, participation in vigorous physical activity, and chronic conditions (cancer, heart disease, diabetes, lung disease). The optimism-corrected iAUC after bootstrap internal validation was 0.76 (95% CI, 0.75-0.76) with time-specific AUC of 0.73 (95% CI, 0.70-0.75) at 1 year, 0.75 (95% CI, 0.73-0.77) at 5 years, and 0.84 (95% CI, 0.82-0.85) at 10 years. On external validation in NHATS (n = 2404), AUC was 0.73 (95% CI, 0.70-0.76) at 1 year and 0.74 (95% CI, 0.71-0.76) at 5 years. Calibration plots suggested good calibration across the range of predicted risk from 1 to 10 years.

Conclusions and Relevance

We developed and externally validated a mortality prediction model in community-dwelling older adults with dementia that showed good discrimination and calibration. The mortality risk estimates may help guide discussions regarding treatment decisions and advance care planning.

Prediabetes and the incidence of dementia in general population: a systematic review and meta-analysis of prospective studies

BACKGROUND

Continuous hyperglycaemia has been related with dementia. However, it remains unclear whether prediabetes poses a higher risk of dementia. A meta-analysis was therefore conducted to comprehensively investigate the possible role of prediabetes as a risk factor of dementia.

METHODS

Prospective cohort studies reporting the association of prediabetes and dementia were identified from PubMed, Web of Science, and Embase databases. A random-effects model was applied to combine the results by incorporating the influence of heterogeneity. Subgroup analyses were also conducted to explore the influences of study features on the relationship. Sensitivity analysis re-estimated the combined effect size after excluding single studies separately to explore the robustness of the results.

RESULTS

Nine studies involving 29 986 adults from the general population, 6265 (20.9%) of whom had prediabetes, were included. It was shown that prediabetes was not independently associated with a higher incidence of dementia compared with normoglycaemia (adjusted risk ratio (RR): 1.01, 95% confidence interval (CI): 0.85-1.21, P = 0.89, I²  = 39%). Subgroup analyses according to the definitions of prediabetes, follow-up duration, method for diagnosis of dementia, and quality score produced similar findings (P for all subgroup differences >0.05). In addition, prediabetes was not independently associated with the incidence of Alzheimer's disease (RR: 1.24, 95% CI: 0.98-1.56, P = 0.07, I²  = 0%) or vascular dementia (RR: 1.16, 95% CI: 0.70-1.92, P = 0.56, I²  = 0%). Different definitions of prediabetes have the potential to influence the results, as reflected in the subgroup analysis for Alzheimer's disease (RR: 1.30, 95% CI: 1.06-1.60, P = 0.01, I²  = 0%).

CONCLUSIONS

Prediabetes may not be an independent risk factor of all-cause dementia or vascular dementia in the general adult population. However, changing the definition of prediabetes may have an impact on the outcome for Alzheimer's disease.