IN REPLY TO DRS. PARASHAR AND VARMA
Bibliographic record
Abstract
To the Editor: We wish to thank Drs. Parashar and Varma for their interest in the results of our cross-sectional study, which identified an association between appropriate angiotensin-converting enzyme (ACE) inhibitor dosing and use of antidepressants in long-term care (LTC) residents with heart failure (HF) and a prior history of depression.1 Acknowledging that our results were preliminary, we advanced a number of hypotheses to explain this association. Drs. Parashar and Varma comment on one of the proposed hypotheses, namely that appropriate ACE inhibitor doses alleviate nonspecific HF symptoms misattributed to depression. Although Drs. Parashar and Varma are correct to point out that appropriate ACE inhibitor dosing alone does not reflect optimal HF therapy, our observation is consistent with the results of the Assessment of Treatment with Lisinopril and Survival Trial, in which fewer HF hospitalizations occurred in patients receiving higher doses of the ACE inhibitor lisinopril.2 Drs. Parashar and Varma also suggest that this explanation would be more credible if prescription of antidepressants was also associated with improvements in New York Heart Association (NYHA) functional class. Because ours was a cross-sectional study, longitudinal assessments of NYHA functional class were not possible. Furthermore, the NYHA functional assessment is unlikely to be suitable for use in such a frail group of patients in whom functional capacity is impaired by a multitude of other comorbidities, including dementia, and in whom atypical disease presentation is often more commonplace than symptoms such as dyspnea.3 The effect on mood of upward ACE inhibitor dose titration in elderly LTC residents with HF might be better assessed by determining whether changes in functional measures such as gait velocity or ability to perform basic activities of daily living, or physiological markers such as serum natriuretic peptide levels, are correlated with changes in mood as measured with appropriate quantitative instruments such as the Cornell Scale for Depression in Dementia.4 The question of what represents appropriate HF therapy for frail elderly residents of LTC remains open. Concerns have been raised about the generalizability of major HF therapy trials to frail older people, in whom symptom control and the preservation of neuropsychiatric health and functional abilities may be more relevant than extending life.5 Research focusing on such outcomes in these patients is required. Financial Disclosure: We declare that there is no financial interest relating to the subject discussed in this letter. Author Contributions: All authors contributed to the content of this letter. Sponsor's Role: None.
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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 | 0.006 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.024 | 0.046 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".