Evidence map›Paper›PMID 36614897›Full record

ArticleJournal of clinical medicine2022

Ankle Doppler for Cuffless Ankle Brachial Index Estimation and Peripheral Artery Disease Diagnosis Independent of Diabetes.

Alexander D Rodway, Darren Cheal, Charlotte Allan, Felipe Pazos-Casal, Lydia Hanna, Benjamin C T Field, Ajay Pankhania, Philip J Aston, Simon S Skene, Gary D Maytham and 1 more

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2022. 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
–field-weighted citation impact
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.

  1. Article
  2. Estimation of toe brachial index based on forefoot Doppler waveforms.European heart journal. Imaging methods and practice · 2025
    Article
  3. Review
  4. Article
  5. Article
  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

11 authors.

Alexander D RodwaySurrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.
Darren ChealBrighton and Sussex University Hospitals NHS Trust, Brighton BN2 5BE, UK.
Charlotte AllanSurrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.
Felipe Pazos-CasalSurrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.
Lydia HannaDepartment of Surgery and Cancer, Imperial College London, London SW7 2BX, UK.
Benjamin C T FieldSurrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.ORCID 0000-0002-1883-1588
Ajay PankhaniaSurrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.
Philip J AstonDepartment of Mathematics, University of Surrey, Guildford GU2 7XH, UK.
Simon S SkeneDepartment of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK.ORCID 0000-0002-7828-3122
Gary D MaythamSurrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.
Christian HeissSurrey and Sussex Healthcare NHS Trust, East Surrey Hospital, Redhill RH1 5RH, UK.ORCID 0000-0002-3212-8995

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ankle brachial pressure index (ABPI) is the first-line test to diagnose peripheral artery disease (PAD). Its adoption in clinical practice is poor and its validity, particularly in diabetes, is limited. We hypothesised that ABPI can be accurately and precisely estimated based on cuffless Doppler waveforms. Retrospective analysis of standard ABPI and handheld Doppler waveform characteristics (n = 200). Prospective analysis of angle-corrected Doppler acceleration index (AccI, n = 148) and standard ABPI with testing of performance to diagnose PAD as assessed with imaging reference standards in consecutive patients. The highest AccI from handheld Doppler at ankle arteries was significantly logarithmically associated with the highest standard ABPI (E[y] = 0.32 ln [1.71 ∗ x + 1], p < 0.001, R2 = 0.68, n = 100 limbs). Estimated ABPI (eABPI) based on AccI closely resembled ABPI (r = 0.81, p < 0.001, average deviation −0.01 ± 0.13 [SD], n = 100 limbs). AccI from angle-corrected Doppler in patients without overt media sclerosis (ABPI ≤ 1.1) improved ABPI prediction (E[y] = 0.297 ∗ ln[0.039 ∗ x + 1], R2 = 0.92, p = 0.006, average deviation 0.00 ± 0.08, n = 100). In a population (n = 148 limbs) including diabetes (56%), chronic limb-threatening ischaemia (51%) and media sclerosis (32%), receiver operating characteristics analysis of (angle-corrected) eABPI performed significantly better than standard ABPI to diagnose PAD defined by ultrasound (ROC AUC = 0.99 ± 0.01, p < 0.001; sensitivity: 97%, specificity: 96%) at the ≤0.9 cut-off. This was confirmed with CT angiography (ROC AUC = 0.98, p < 0.001, sensitivity: 97%, specificity: 100%) and was independent of the presence of diabetes (p = 0.608). ABPI can be estimated based on ankle Doppler AccI without compression, and eABPI performs better than standard ABPI to diagnose PAD independent of diabetes. eABPI has the potential to be included as a standard component of lower extremity ultrasound.

Indexed as

ankle brachial pressure indexDoppler waveformperipheral artery disease

Identifiers

PMID36614897
PMCPMC9821740

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Registered trials

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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.