What is suspected heart failure with preserved left ventricular systolic function?
Bibliographic record
Abstract
Editor—Caruana et al's study focuses on the well established difficulties in the diagnosis of diastolic heart failure in the community.1 I question the authors' conclusions that most patients in the community with a diagnosis of diastolic heart failure have unrelated conditions. Proposed criteria for the diagnosis of diastolic heart failure require definitive evidence of congestive heart failure by clinical criteria, physical examination, chest radiography, response to diuretics, etc as a starting point.2,3 The authors do not provide the indications that led the primary physicians to refer the patients for echocardiography; the clinical suspicion of diastolic heart failure should rely on more than symptoms of dyspnoea at rest or on exertion, for which the differential diagnosis is broad. The authors consider a history of coronary artery disease or electrocardiographic changes consistent with coronary disease to be an alternative explanation for the patients' symptoms. In patients with normal systolic function and without acute ischaemia, physiological stress testing would be mandatory to support this claim; however, no such evaluation was performed. Lastly, in an elderly population (mean age 71) an E:A ratio of <1.0 is a normal finding and should not be construed as indicating diastolic dysfunction.4 The use of mitral filling variables in the evaluation of diastolic heart failure is problematic, and it is to be hoped that newer echocardiographic techniques such as tissue Doppler and flow propagation will prove more accurate.5
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.019 | 0.022 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".