Bibliographic record
Abstract
When discussing therapies with patients, physicians tend to focus more on side effects rather than on benefits. In this issue of the journal, Zaman et al.1 describe a novel, specular, approach based on the benefits of treatment and the risks, namely increased mortality, of its deferral. The Authors undertook a meta-analysis of randomized controlled trials to calculate the excess mortality caused by deferral of medical therapy for 1 year with angiotensin-converting enzyme inhibitors, beta-blockers and aldosterone antagonists. It was then calculated that in patients who might achieve a 1-year survival rate of 90% if treated, a 1-year deferral of all these three classes of drugs would reduce survival to 78%. Thus, 1-year deferral of treatment for heart failure (HF) causes an annual absolute increase in mortality of 12 in 100 patients, 1% of the patients each month, a value much higher than that perceived as worth to be mentioned by referring physicians to patients and to be included in patients' information leaflets.1 Deferral of treatment may be caused by lack of prescription by the physician or lack of adherence by the patient. Komajda et al.2, 3 report the results of QUality of Adherence to guideline recommendations for LIFe-saving treatment in heart failure surveY (QUALIFY), an international, prospective, observational, longitudinal survey of 6669 outpatients with HF and reduced ejection fraction (HFrEF). Based on the prescription and dosing of evidence-based treatment, adherence to medication was classified as good, moderate, and poor in 23%, 55%, and 22% of patients, respectively. The study shows the independent prognostic value of adherence to treatment. At 6-month follow-up, poor adherence was associated with higher overall mortality (relative risk [RR], 2.21, 95% confidence interval [CI] 1.42–3.44) with similar results for cardiovascular and HF mortality alone and for the combined endpoint of mortality and hospitalization.3 The effects of different disease management programmes is still controversial.4–6 Such programmes should be of greater benefit in the so-called transitional phase, e.g. the period immediately after discharge from hospital, a time of heightened vulnerability for readmissions and death.7, 8 Van Spall et al.9 performed a systematic review and network meta-analysis of randomized controlled trials evaluating the efficacy of transitional care services in decreasing all-cause death and all-cause readmissions following hospitalization for HF. The analysis included 53 trials (12 356 patients). Among services that significantly decreased all-cause mortality compared with usual care, nurse home visits were the most effective (RR 0.78; 95% CI 0.62–0.98). Similarly, nurse home visits were the most effective service decreasing rehospitalizations (RR 0.65; 95% CI 0.49–0.86), followed by nurse case management and disease management clinics. Nurse home visits had the greatest pooled cost-savings. Telephone, telemonitoring, pharmacist, and education interventions did not improve clinical outcomes.9 Web based resources are new tools that can improve disease management. The Heart Failure Association of the European Society of Cardiology established a website, heartfailurematters.org, dedicated to patients, their carers, health care professionals and the general public, and aimed to inform and educate regarding HF. Its clinical impact is evaluated in a prospective clinical trial.10 In this issue, Wagenaar et al.11 show its use in the years 2010 to 2015. Although the annual number of visits increased from 416 345 in 2010 to 1 636 368 in 2015, the site seems to have greater potential considering that the number of people living with HF worldwide is estimated to be 23 million. Ivabradine is indicated for the treatment of HFrEF.12 The prEserveD left ventricular ejectIon fraction chronic heart Failure with ivabradine studY (EDIFY) included 179 patients with HF with preserved ejection fraction (HFpEF) in sinus rhythm, a heart rate of ≥70 b.p.m and NT-proBNP of ≥220 pg/mL who were randomized to ivabradine or placebo and followed for 8 months. Ivabradine treatment caused a reduction in heart rate but no change in any of the three co-primary endpoints: E/e', 6-minute walk test distance and NT-proBNP plasma levels.13 Although the study was preliminarly terminated, this is the largest randomized trial of ivabradine in HFpEF and the results seemed unlikely to differ in a larger study group. Pulsatile arterial load and, namely, wave reflections originating at the periphery and conducted back to the heart can cause left ventricular diastolic dysfunction, hypertrophy and fibrosis.14 Chirinos et al.15 compared the haemodynamic effects of organic nitrates (sublingual nitroglycerin) and inorganic nitrates in patients with HFpEF. Nitroglycerin caused profound vasodilatation in the carotid territory with blood pressure reduction but no change in wave reflection. In contrast, inorganic nitrate reduced wave reflections across the first three harmonics with no change in blood pressure and carotid bed vascular resistance.15 These haemodynamic differences may underlie the different effects on exercise capacity and side effect profile of inorganic vs. organic nitrate in HFpEF. Teerlink et al.16 report the long-term effects of the intramyocardial administration of bone-marrow-derived, lineage-directed, autologous cardiopoietic mesenchymal stem cells on left ventricular remodelling in patients with HFrEF enrolled in Congestive Heart Failure Cardiopoietic Regenerative Therapy (CHART-1), the largest phase II/III, cardiac stem cell trial to date. Patients (n=351) were randomized to stem cell administration or a sham procedure. After 1 year, delivery of cardiopoietic stem cells was associated with a progressive decrease in both left ventricular end-diastolic and end-systolic volume, both significant compared with the sham procedure. The largest reverse remodelling was evident in the patients receiving a moderate number of injections (<20).
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.080 | 0.022 |
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".