The Effect of Age on Characteristics and Mortality of Intracerebral Hemorrhage in the Oldest-Old
Bibliographic record
Abstract
BACKGROUND: Incidence of acute intracerebral hemorrhage (ICH) increases with age, but there is a lack of information about ICH characteristics in the oldest-old (age ≥85 years). In particular, there is a need for information about hematoma volume, which is included in most clinical scales for prediction of mortality in ICH patients. Many of these scales also assume that, independent of ICH characteristics, the oldest-old have a higher mortality than younger elderly patients (age 65-74 years). However, supporting evidence from cohort studies is limited. We investigated ICH characteristics of oldest-old subjects compared to young (<65 years), young-old (65-74 years) and old-old (75-84 years) subjects. We also investigated whether age is an independent mortality predictor in elderly (age ≥65 years) subjects with acute ICH. METHODS: We retrospectively collected clinical and neuroimaging data of 383 subjects (age 34-104 years) with acute supratentorial primary ICH who were admitted to an Italian Stroke Unit (SU) between October 2007 and December 2014. Measured ICH characteristics included hematoma location, volume and intraventricular extension of hemorrhage on admission CT scan; admission Glasgow Coma Scale ≤8 and hematoma expansion (HE) measured on follow-up CT-scans obtained after 24 h. General linear models and logistic models were used to investigate the association of age with ICH characteristics. These models were adjusted for pre-admission characteristics, hematoma location and time from symptom onset to admission CT scan. Limited to elderly subjects, Cox models were used to investigate the association of age with in-SU and 1-year mortality: the model for in-SU mortality adjusted for pre-admission and ICH admission characteristics and the model for 1-year mortality additionally adjusted for functional status and disposition at SU discharge. RESULTS: Independent of pre-admission characteristics, hematoma location and time from symptom onset to admission CT-scan, oldest-old subjects had the highest admission hematoma volume (p < 0.01). Age was unrelated to all other ICH characteristics including HE. In elderly patients, multivariable adjusted risk of in-SU and 1-year mortality did not vary across age categories. CONCLUSIONS: Oldest-old subjects with acute supratentorial ICH have higher admission hematoma volume than young and young-old subjects but do not differ for other ICH characteristics. When taking into account confounding from ICH characteristics, risk of in-SU and 1-year mortality in elderly subjects with acute supratentorial ICH does not differ across age categories. Our findings question use of age as an independent criterion for stratification of mortality risk in elderly subjects with acute ICH.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".