Evidence map›Paper›PMID 37662516›Full record

ArticleEClinicalMedicine2023

Prognosis, characteristics, and provision of care for patients with the unspecified heart failure electronic health record phenotype: a population-based linked cohort study of 95262 individuals.

Yoko M Nakao, Kazuhiro Nakao, Ramesh Nadarajah, Amitava Banerjee, Gregg C Fonarow, Mark C Petrie, Kazem Rahimi, Jianhua Wu, Chris P Gale

Open access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 3 countries.

Yoko M NakaoLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Kazuhiro NakaoLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Ramesh NadarajahLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
Amitava BanerjeeInstitute of Health Informatics, University College London, London, UK.
Gregg C FonarowDivision of Cardiology, Department of Medicine, University of California at Los Angeles, Los Angeles, USA.
Mark C PetrieInstitute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
Kazem RahimiNuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK.
Jianhua WuWolfson Institute of Population Health, Queen Mary University of London, London, UK.
Chris P GaleLeeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK.
University of Leeds · GBBarts Health NHS Trust · GBQueen Mary University of London · GBUniversity of California, Los Angeles · USUniversity of Glasgow · GBUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Whether the accuracy of the phenotype ascribed to patients in electronic health records (EHRs) is associated with variation in prognosis and care provision is unknown. We investigated this for heart failure (HF, characterised as HF with preserved ejection fraction [HFpEF], HF with reduced ejection fraction [HFrEF] and unspecified HF). Methods: We included individuals aged 16 years and older with a new diagnosis of HF between January 2, 1998 and February 28, 2022 from linked primary and secondary care records in the Clinical Practice Research Datalink in England. We investigated the provision of guideline-recommended diagnostic investigations and pharmacological treatments. The primary outcome was a composite of HF hospitalisation or all-cause death, and secondary outcomes were time to HF hospitalisation, all-cause death and death from cardiovascular causes. We used Kaplan-Meier curves and log rank tests to compare survival across HF phenotypes and adjusted for potential confounders in Cox proportional hazards regression analyses. Findings: Of a cohort of 95,262 individuals, 1271 (1.3%) were recorded as having HFpEF, 10,793 (11.3%) as HFrEF and 83,198 (87.3%) as unspecified HF. Individuals recorded as unspecified HF were older with a higher prevalence of dementia. Unspecified HF, compared to patients with a recorded HF phenotype, were less likely to receive specialist assessment, echocardiography or natriuretic peptide testing in the peri-diagnostic period, or receive angiotensin-converting enzyme inhibitors, beta blockers or mineralocorticoid receptor antagonists up to 12 months after diagnosis (risk ratios compared to HFrEF, 0.64, 95% CI 0.63-0.64; 0.59, 0.58-0.60; 0.57, 0.55-0.59; respectively) and had significantly worse outcomes (adjusted hazard ratios compared to HFrEF, HF hospitalisation and death 1.66, 95% CI 1.59-1.74; all-cause mortality 2.00, 1.90-2.10; cardiovascular death 1.77, 1.65-1.90). Interpretation: Our findings suggested that absence of specification of HF phenotype in routine EHRs is inversely associated with clinical investigations, treatments and survival, representing an actionable target to mitigate prognostic and health resource burden. Funding: Japan Research Foundation for Healthy Aging and British Heart Foundation.

Indexed as

Care qualityElectronic health recordsHeart failureOutcome

Identifiers

PMID37662516
PMCPMC10474358
OpenAlexW4386164873

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.