Clinical, Electrocardiographic, and Echocardiographic Features in Hospitalized Nonagenarians (90+): Comparison between the Genders
Bibliographic record
Abstract
OBJECTIVES: We investigated the clinical, electrocardiographic, and echocardiographic determinants of the cardiac status in nonagenarian patients. METHODS: We consecutively examined 654 Caucasian patients (232 males and 422 females) aged ≥90 years. All patients underwent clinical examination, ECG, and transthoracic echocardiography. RESULTS: Their average age was 92.5 ± 2.5 years. Patients were predominately female of older age (p < 0.0001 and p = 0.02, respectively). A history of cardiovascular disease was present in 78.4% of the participants. One third of the patients was hospitalized for cardiovascular causes, with females being twice as many (p < 0.0001). Females showed higher levels of serum cholesterol, triglycerides, and glycemia (p < 0.0001, p< 0.0001, and p = 0.04 respectively). Sinus rhythm was detected in 65%, and atrial fibrillation in 31% of the overall population. Heart rate, PR and corrected QT (QTc) intervals, right bundle branch block (RBBB) and RBBB associated with left anterior fascicular block (LAFB) were higher in males (p < 0.0001, p = 0.036, p = 0.009, p = 0.001, and p = 0.004, respectively). Aortic root dimension, left ventricular (LV) mass index, and indexed LV systolic-diastolic volumes were higher in males (p < 0.001, p < 0.0001, p < 0.001, and p < 0.0001, respectively). Women showed fewer LV segmental kinetic disorders (p = 0009) and higher LV ejection fraction (LVEF; p< 0.0001). Hyperuricemia was positively associated with a history of cardiovascular disease (r = 0.15), glycemia (r = 19), creatininemia (r = 0.50), uremia (r = 0.51), triglycerides (r = 0.19), PR interval (r = 0.14), and left bundle branch block (r = 0.11), and inversely associated with sinus rhythm (r = -0.14) and LVEF (r = -0.17). Diabetes was positively correlated with PR and QTc intervals (r = 0.14 and r = 0.10, respectively), and RBBB with LFAB (r = 0.10), and inversely correlated with LVEF (r = -0.10). CONCLUSIONS: We found a remarkable presence of cardiovascular risk factors, ECG, and structural alterations in hospitalized nonagenarians, which presents more commonly in males.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".