Development and internal validation of a new life expectancy estimator for multimorbid older adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: As populations are aging, the number of older patients with multiple chronic diseases demanding complex care increases. Although clinical guidelines recommend care to be personalized accounting for life expectancy, there are no tools to estimate life expectancy among multimorbid patients. Our objective was therefore to develop and internally validate a life expectancy estimator specifically for older multimorbid adults. METHODS: We analyzed data from the OPERAM (OPtimising thERapy to prevent avoidable hospital admissions in multimorbid older people) study in Bern, Switzerland. Participants aged 70 years old or more with multimorbidity (3 or more chronic medical conditions) and polypharmacy (use of 5 drugs or more for > 30 days) were included. All-cause mortality was assessed during 3 years of follow-up. We built a 3-year mortality prognostic index and transformed this index into a life expectancy estimator. Mortality risk candidate predictors included demographic variables (age, sex), clinical characteristics (metastatic cancer, number of drugs, body mass index, weight loss), smoking, functional status variables (Barthel-Index, falls, nursing home residence), and hospitalization. We internally validated and optimism corrected the model using bootstrapping techniques. We transformed the mortality prognostic index into a life expectancy estimator using the Gompertz survival function. RESULTS: Eight hundred five participants were included in the analysis. During 3 years of follow-up, 292 participants (36%) died. Age, metastatic cancer, number of drugs, lower body mass index, weight loss, number of hospitalizations, and lower Barthel-Index (functional impairment) were selected as predictors in the final multivariable model. Our model showed moderate discrimination with an optimism-corrected C statistic of 0.70. The optimism-corrected calibration slope was 0.96. The Gompertz-predicted mean life expectancy in our sample was 5.4 years (standard deviation 3.5 years). Categorization into three life expectancy groups led to visually good separation in Kaplan-Meier curves. We also developed a web application that calculates an individual's life expectancy estimation. CONCLUSION: A life expectancy estimator for multimorbid older adults based on an internally validated 3-year mortality risk index was developed. Further validation of the score among various populations of multimorbid patients is needed before its implementation into practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT02986425. First submitted 21/10/2016. First posted 08/12/2016.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it