Evidence map›Paper›PMID 35411782›Full record

ArticleJournal of the American Heart Association2022

Cost-Effectiveness of Monitoring Patients Post-Stroke With Mobile ECG During the Hospital Stay.

Lan Gao, Marj Moodie, Ben Freedman, Christina Lam, Hans Tu, Corey Swift, Sze-Ho Ma, Vincent C T Mok, Yi Sui, David Sharpe and 5 more

Open access · goldAbstract read
In one paragraph

Article in Journal of the American Heart Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

15 authors at 10 institutions in 3 countries.

Lan GaoFaculty of Health Deakin Health Economics Institute for Health TransformationDeakin University Melbourne Australia.ORCID 0000-0001-9734-1140
Marj MoodieFaculty of Health Deakin Health Economics Institute for Health TransformationDeakin University Melbourne Australia.ORCID 0000-0001-6890-5250
Ben FreedmanHeart Research Institute Charles Perkins Centre, and Concord Hospital CardiologyUniversity of Sydney Sydney Australia.ORCID 0000-0002-3809-2911
Christina LamThe Melbourne Brain Centre at the Royal Melbourne Hospital and the University of Melbourne Parkville Australia.
Hans TuDepartment of Neurology and Medicine Western HealthThe University of Melbourne Footscray Australia.
Corey SwiftThe Melbourne Brain Centre at the Royal Melbourne Hospital and the University of Melbourne Parkville Australia.
Sze-Ho MaDivision of Neurology Department of Medicine and Therapeutics Gerald Choa Neuroscience Centre Lui Che Woo Institute of Innovative Medicine Faculty of Medicine Prince of Wales HospitalThe Chinese University of Hong Kong Hong Kong China.ORCID 0000-0003-0609-758X
Vincent C T MokDivision of Neurology Department of Medicine and Therapeutics Gerald Choa Neuroscience Centre Lui Che Woo Institute of Innovative Medicine Faculty of Medicine Prince of Wales HospitalThe Chinese University of Hong Kong Hong Kong China.
Yi SuiDepartment of Neurology Shenyang First People's Hospital Shenyang China.ORCID 0000-0002-2898-7877
David SharpeNeurology Department Concord General Hospital Sydney Australia.
Darshan GhiaFiona Stanley Hospital and University of Western Australia Perth Australia.
Jim JannesDepartment of Neurology Royal Adelaide Hospital Adelaide Australia.
Stephen DavisThe Melbourne Brain Centre at the Royal Melbourne Hospital and the University of Melbourne Parkville Australia.ORCID 0000-0003-0962-2300
Xinfeng LiuDepartment of Neurology Jinling HospitalMedical School of Nanjing University Nanjing China.ORCID 0000-0002-8182-9632
Bernard YanThe Melbourne Brain Centre at the Royal Melbourne Hospital and the University of Melbourne Parkville Australia.ORCID 0000-0001-8802-9606
The Royal Melbourne Hospital · AUChinese University of Hong Kong · HKDeakin University · AUConcord Repatriation General Hospital · AUNanjing General Hospital of Nanjing Military Command · CNRoyal Adelaide Hospital · AUShenyang First People's Hospital · CNThe University of Melbourne · AUThe University of Sydney · AUThe University of Western Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background The effectiveness of a nurse-led in-hospital monitoring protocol with mobile ECG (iECG) was investigated for detecting atrial fibrillation in patients post-ischemic stroke or post-transient ischemic attack. The study aimed to assess the cost-effectiveness of using iECG during the initial hospital stay compared with standard 24-hour Holter monitoring. Methods and Results A Markov microsimulation model was constructed to simulate the lifetime health outcomes and costs. The rate of atrial fibrillation detection in iECG and Holter monitoring during the in-hospital phase and characteristics of modeled population (ie, age, sex, CHA2DS2-VASc) were informed by patient-level data. Costs related to recurrent stroke, stroke management, medications (new oral anticoagulants), and rehabilitation were included. The cost-effectiveness analysis outcome was calculated as an incremental cost per quality-adjusted life-year gained. As results, monitoring patients with iECG post-stroke during the index hospitalization was associated with marginally higher costs (A$31 196) and greater benefits (6.70 quality-adjusted life-years) compared with 24-hour Holter surveillance (A$31 095 and 6.66 quality-adjusted life-years) over a 20-year time horizon, with an incremental cost-effectiveness ratio of $3013/ quality-adjusted life-years. Monitoring patients with iECG also contributed to lower recurrence of stroke and stroke-related deaths (140 recurrent strokes and 20 deaths avoided per 10 000 patients). The probabilistic sensitivity analyses suggested iECG is highly likely to be a cost-effective intervention (100% probability). Conclusions A nurse-led iECG monitoring protocol during the acute hospital stay was found to improve the rate of atrial fibrillation detection and contributed to slightly increased costs and improved health outcomes. Using iECG to monitor patients post-stroke during initial hospitalization is recommended to complement routine care.

Indexed as

Atrial FibrillationStrokeAnticoagulantsCost-Benefit AnalysisElectrocardiography, AmbulatoryHumansLength of StayMarkov ChainsQuality-Adjusted Life YearsAnticoagulantsatrial fibrillationcost‐effectiveness analysisiECG monitoringstroke

Identifiers

PMID35411782
PMCPMC9238470
OpenAlexW4223484360

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.