Evidence map›Paper›PMID 36721595›Full record

ArticleCureus2022

Measurement of Lag-Screw Anteversion With an iPhone During Trochanteric Fracture Surgery.

Yo Kinami, Joe Hasei, Kazuo Fujiwara

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 3 institutions in 1 country.

Yo KinamiDepartment of Orthopaedic Surgery, Okayama City Hospital, Okayama, JPN.
Joe HaseiDepartment of Medical Information and Assistive Technology Development, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, JPN.
Kazuo FujiwaraDepartment of Orthopedic Surgery, Okayama City Hospital, Okayama, JPN.
Okayama Medical Center · JPOkayama Prefecture · JPOkayama University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction  A useful way to easily evaluate femoral rotation during surgery for trochanteric fractures is not known. Hence, this pilot study aimed to develop an intraoperative indicator to evaluate anteversion in femoral trochanteric fractures. Material and methods Prospectively, from June 2021 to January 2022, all patients with femoral trochanteric fractures (Orthopaedic Trauma Association classification: 31A1-3) treated using a cephalo-medullary nail with a lag-screw neck-shaft angle of 125° were included in this study. During surgery, lag-screw anteversion (LS-AV) was measured using the goniometer application in an iPhone with the fractured femur table-top-plane level with the traction table floor. Accuracy was analyzed by comparing axial-projected lag-screw anteversion (AxP-LS-AV) and three-dimensional computed tomography lag-screw anteversion (3DCT-LS-AV) measurements after surgery. Results Fifty patients (14 males and 36 females) were included in the study. The mean age was 87 (range; 69-98) years; the Orthopaedic Trauma Association classifications were A1 (28 patients), A2 (18 patients), and A3 (4 patients). The mean LS-AV was 10.7° ± 6.9°, the mean AxP-LS-AV was 12.8° ± 8.3°, and the mean 3DCT-LS-AV was 13.1° ± 8.6°. The median difference between AxP-LS-AV and 3DCT-LS-AV was 3.0° (range: 0°-12°), and 40 (80%) patients had differences of ≤5° (Bland-Altman plot: inside of limit of agreement = 86%, paired

Indexed as

anteversionfemoral rotationiphonelag screwmalrotationsmartphonetable-to-planetrochanteric fracture

Identifiers

PMID36721595
PMCPMC9884309
OpenAlexW4313409315

What OpenQuestion holds

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LicenceCC BY
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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.