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Record W3157792387 · doi:10.1002/ejhf.2213

Optimizing evidence‐based heart failure medication: every contact counts

2021· letter· en· W3157792387 on OpenAlexaboutno aff
Loreena Hill, Ekaterini Lambrinou, Sotiris Antoniou

Bibliographic record

VenueEuropean Journal of Heart Failure · 2021
Typeletter
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEjection fractionHeart failureGuidelineAcute coronary syndromeCanadian Cardiovascular SocietyClinical trialRandomized controlled trialHealth careEmergency medicineIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

This article refers to ‘Virtual optimization of guideline-directed medical therapy in hospitalized patients with heart failure with reduced ejection fraction: the IMPLEMENT-HF pilot study’ by A.S. Bhatt et al., published in this issue on pages 1191–1201. During 2020, the delivery of traditional health care across Europe had to adapt, in response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Virtual consultations became integrated into the daily fabric of heart failure (HF) management, changing patients' and health care professionals' attitudes towards remote management. This paradigm shift towards an increased use of telemonitoring or remote monitoring was supported by expert consensus papers and results from clinical trials, such as the TIM-HF2 trial.1, 2 This trial enrolled 1571 symptomatic patients with HF reduced ejection fraction (HFrEF) from hospitals and cardiology settings, who were randomly assigned to receive 24 h access to physician-led management and support, facilitated through ‘predefined algorithms and biomarker values’ or usual care. The study concluded that a structured remote patient management system reduced the percentage of days lost due to unplanned cardiovascular hospital admissions and all-cause mortality.3 The innovative prospective, pre-post pilot interventional study by Bhatt et al.,4 represented by the acronym IMPLEMENT-HF, recruited 118 hospitalized patients to either usual care (n = 29) or a guideline-directed medical therapy (GDMT) Team intervention (n = 89), according to the month the patient was admitted. Criteria for exclusion were de novo HFrEF, recent acute coronary syndrome or stroke, recent cardiac surgery, systolic blood pressure <90 mmHg within the past 24 h, or coronavirus 2. The intervention involved cardiology-trained pharmacists and physicians providing remote recommendations to optimize each patient's pharmaceutical HF treatment according to a guideline-derived algorithm and clinical parameters. These recommendations were provided to and actioned by the non-specialist physician, caring for the patient admitted onto a non-cardiac ward. The increasing prevalence of HF, associated with an ageing population and multiple comorbidities, has resulted in many patients needing inter-specialty multidisciplinary management (i.e. renal, endocrine, respiratory) for the treatment of illness, control of symptoms, monitoring of polypharmacy and planning future care.5, 6 There is a trend towards more patients presenting to hospital, as a result of their comorbidities, requiring admission and treatment by professionals not specialist in HF or cardiology, for example geriatricians, respiratory physicians, etc. It is globally recognized that patients with HF admitted to a non-cardiology ward do not have as favourable outcomes as those reviewed by cardiac specialists. The national audit of HF care in England and Wales found lower in-hospital mortality rates for patients treated on cardiology wards (7.8%), than on general medical wards (13.2%) or on other wards (17.4%).7 A similar picture was found in North America, whereby patients with HF had a reduced mortality at 30 days and 1 year when treated by a cardiologist, compared to patients treated by other specialist healthcare professionals.8 Why this may be can be partially explained by evidence from studies showing guideline-based therapies (beta-blockers, angiotensin receptor blockers) are either not initiated, or prescribed at a low dose in ‘high-risk patients’, including older patients, those with frailty, or patients with a number of comorbidities.9, 10 Innovations in the provision of care should not only address HF management but also comorbidities, which are often interlinked, thereby offering an improved coordinated and comprehensive programme, optimizing chronic disease management, irrespective of clinical setting. The study by Bhatt et al.,4 aimed to address the inequality of treatment provision to HF patients managed on a general medical ward, following a non-cardiovascular admission. This was accomplished through a shared care model, with development and implementation of a pharmaceutical guideline-based protocol, provision of education to non-HF specialists, coordination of care and delineation of roles between physician, GDMT Team and cardiology team for future follow-up. The multicomponent nature of the intervention would challenge whether the GDMT protocol, professional education or management by a multidisciplinary team in hospital and on discharge, had the greatest impact.11 Further research would be beneficial to evaluate the impact of each component to enable replication and more widespread implementation of findings. There is also the debate regarding managing the patient according to an algorithm vs. the provision of a person-centred and tailored approach to management. A holistic approach to care should target the management and treatment of all health concerns, be they physical, psychological, or social in nature. By doing so, it can have a positive impact on the clinical outcome and quality of life for patients with HF, particularly those of advanced age with supportive and palliative needs.12 Every patient brings his/her own complexity of comorbidities, sensitivity and contraindications to medications, cultural and health beliefs. In this modern era, health professionals must recognise the value of interdisciplinary working, with clear lines and systems of communication, delegation and responsibility. It has been suggested that there is underreporting in the use of treatment protocols within telemedicine.13 Protocols have been used successfully by specialist nurses in the titration of evidence-based medications, leading to an improvement in the clinical outcome and echocardiographic results of patients up to 18 months post-discharge.14 Furthermore, the use of telemedicine to increase communication between general practitioner (GP) and HF multidisciplinary team was illustrated in the TEMA-HF 1 study.15 Within this Belgium study, 160 patients were randomized to 6 months of intense follow-up of either telemonitoring or usual care. Any alerts arising from the set parameters were sent to the patient's GP and HF clinic to enable early intervention. Results indicated significant reduction in all-cause mortality between the intervention and control group (5% vs. 17.5%, P = 0.01), in addition to less days lost to hospitalization, dialysis, or death (13 vs. 30 days, P = 0.02), with a trend (P = 0.06) towards a reduction in hospitalizations as a result of the intervention. Similar to the IMPLEMENT-HF study by Bhatt et al.,4 medication changes were communicated to the primary cardiologist responsible for reviewing the patient after hospital discharge; however, a key step was absent, that being communication with the patient's GP. In doing so ensures a ‘seamless’ transition no matter where the patient begins or continues their healthcare journey. Pharmacists are important members of the multidisciplinary team and numerous studies have evaluated their impact as part of their involvement within the multidisciplinary HF team on patient care. Jain et al.16 assessed the impact of a protocol-driven HF clinic (staffed by nurses and pharmacists) in improving guideline-driven use of pharmacotherapy and patient symptoms. Of the 234 patients in the study, 127 (57%) were receiving none or only one guideline-driven evidence-based therapy during their first clinic visit. This was reduced to 25 patients (11%) after being managed by the clinic for 1 year. In addition, the improvement in prescription rates was accompanied by significant up-titration of dose. The proportion of patients on ‘medium’ or ‘high’ doses increased for beta-blockers from 43 (18%) to 134 (57%) and for angiotensin-converting enzyme inhibitors/angiotensin receptor blockers from 129 (55%) to 201 (86%). Symptom improvement was demonstrated by the reduction of patients categorized in the New York Heart Association functional classes III and IV [from 93 (40%) to 53 (23%)]. A systematic review of randomized controlled trials by Koshman et al.17 categorized the role of the pharmacist as providing either pharmacist-directed care or pharmacist collaborative care. Overall, pharmacist care (both directed and collaboration) was associated with significant reductions in the rate of all-cause hospitalizations (11 studies with 2026 patients) and HF-related hospitalizations (11 studies with 1977 patients), and a non-significant reduction in mortality (12 studies involving 2060 patients). Pharmacist collaborative care led to greater reductions in the rate of HF hospitalizations [odds ratio (OR) 0.42; 95% confidence interval (CI) 0.24–0.74] compared to pharmacist-directed care (OR 0.89; 95% CI 0.68–1.17). Recent data from a randomized controlled trial – PHARM-CHF that enrolled 237 elderly patients (mean age 74 years) – found the involvement of a community pharmacist increased medication adherence for evidence-based HF medications (OR 2.9, 95% CI 1.4–5.9, P = 0.005), with an improvement in patient-reported quality of life (Minnesota Living with Heart Failure Questionnaire scores; P = 0.02), compared to usual care.18 It can therefore be concluded that involving a pharmacist in the management of patients with HF can improve patient outcomes, especially in collaboration with a HF multidisciplinary team. In conclusion, patients with HF will continue to place a high requirement on modern healthcare resources. As healthcare systems continue to bring forward innovative approaches to manage these often complex patients, minimizing HF disease burden, collaborative multidisciplinary team working across primary and secondary care settings should be prioritized to improve outcomes and care quality.19 In 2020, coronavirus 2 brought many personal and professional challenges; however, it also opened up new and different ways for professionals to work efficiently, which now should be embraced to ensure every contact with a patient with HF counts. Conflict of interest: none declared.

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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.085
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.021
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.085
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0070.006
Open science0.0020.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0210.004

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.

Opus teacher head0.045
GPT teacher head0.283
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations2
Published2021
Admission routes1
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