Bibliographic record
Abstract
Sir, With reference to the review article “Heart failure with Preserved Ejection Fraction in the Indian Context” published in your journal volume 15, issue 2, April–June 2025, certain views by the authors appear in disagreement with the current understanding of heart failure with preserved ejection fraction (HFpEF). In the introduction of the article, the authors have mentioned that HFpEF is a clinical diagnosis, however, heart failure (HF) irrespective of ejection fraction (EF) is a clinical diagnosis on basis of symptoms and signs. HFpEF is a phenotype of HF which can only be diagnosed after determination of left ventricular (LV) EF which is by definition more than 50%.[1] The definition given by authors that “suboptimal amount of blood pumped into circulation despite normal or near-normal EF” does not fit to the actual definition. Elevated LV filling pressure despite normal or near-normal EF would be more appropriate.[2] Out of the hallmarks of HFpEF described by authors, ‘evidence of increased intravascular volume load’ also appear inappropriate, the more appropriate hallmark would be evidence of systemic and/or pulmonary congestion instead of intravascular volume load.[3] The case vignette described does not fit to a “provisional diagnosis of HF” in the absence of symptom (lying flat for two nights), normal jugular venous pulse, and lower zone haziness on chest X-ray. X-ray in HF typically produces prominent vascularity in the upper zones due to pulmonary venous hypertension secondary to increased LV filling pressure.[3] Echo findings are grossly inadequate, instead of slightly increased left atrial (LA) dimension, it would have been better to express the LA volume index. Looking at the standard diastolic Doppler parameters, ‘diastolic relaxation time 200 ms’ as mentioned by authors is not clear. Two relaxation times are measured commonly such as the isovolumic relaxation time and mitral E-wave deceleration time (DT). In the absence of a tissue Doppler study which is integral to diastolic function assessment and mitral inflow measurement showing only grade I diastolic dysfunction E/A 0.70 (E < A), DT 200 ms, if the authors mean the diastolic relaxation time is actually the DT, a diagnosis of HFpEF is not tenable whether the presentation is early or relatively late.[4] In Table 1 of the article, what the authors mentioned about current guidelines are in fact older, the American College of Cardiology (ACC)/American Heart Association (AHA) 2013 guidelines are updated in 2022 as ACC/AHA/Heart Failure Society of America (HFSA) guidelines for management of HF. The European Society of Cardiology guideline 2016 has been updated in 2021 and 2023. The Canadian Cardiovascular Society 2017 guidelines are also updated in 2021. What the authors claimed as our strategy is in fact is the recommendation of ACC/AHA/HFSA guidelines recommendation including the drug categories and class of recommendations as Class 1 and Class 2b.[1] Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.
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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 | 0.018 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.028 |
| Scholarly communication | 0.007 | 0.021 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.028 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".