Evidence map›Paper›PMID 31517841›Full record

SynthesisMedicine2019

The rate of missed diagnosis of lower-limb DVT by ultrasound amounts to 50% or so in patients without symptoms of DVT: A meta-analysis.

Yuhong Zhang, Haifa Xia, Yaxin Wang, Lin Chen, Shengnan Li, Idrees Ali Hussein, Yan Wu, You Shang, Shanglong Yao, Ruofei Du

Erratum issuedAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  6. Automatic robotic doppler sonography of leg arteries.International journal of computer assisted radiology and surgery · 2024
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  18. Deep venous thrombosis after Achilles tendon rupture is associated with poor patient-reported outcome.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2020
    Article
  19. Article
  20. Point-of-care ultrasound for deep venous thrombosis of the lower limb.Australasian journal of ultrasound in medicine · 2020
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Yuhong ZhangDepartment of Anesthesiology.
Haifa XiaDepartment of Anesthesiology.
Yaxin WangDepartment of Critical Care Medicine, Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.
Lin ChenDepartment of Anesthesiology.
Shengnan LiDepartment of Anesthesiology.
Idrees Ali HusseinDepartment of Anesthesiology.
Yan WuDepartment of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
You ShangDepartment of Critical Care Medicine, Institute of Anesthesiology and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology.
Shanglong YaoDepartment of Anesthesiology.
Ruofei DuUniversity of New Mexico Comprehensive Cancer, Albuquerque, NM, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo assess whether the ultrasound (US) is a reliable approach in detecting lower-limb deep-vein thrombosis (DVT) in patients without symptoms of DVT.

methodsThe research team performed a systematic search in PubMed, Ovid, Cochrane, and Web of Science without language or date restrictions. Full-text reports on prospective diagnostic studies involve the detection of lower-limb proximal and distal DVT in patients without symptoms of DVT using US and venography. A meta-analysis was performed using Meta-DiSc (version 1.4), providing the pooled sensitivity, specificity, positive (LR+) and negative (LR-) likelihood ratios of the detection accuracy of US. There were 4 different classes of subgroup analysis-the class of patients stratified by location of US exam (proximal, distal, whole leg), the class stratified by technique (color/doppler, compression, both modalities), the class stratified by kind of surgery (orthopedic, otherwise hospitalized) and the class stratified by era of publishing (1980s, 1990s, 2000s). The study quality and the risk of bias were evaluated using QUADAS-2, with heterogeneity was assessed and quantified by the Q score and I statistics, respectively.

resultsThe meta-analysis included 26 articles containing 41 individual studies with a total of 3951 patients without symptoms of DVT. Using venography as the gold standard, US for proximal DVT had a pooled sensitivity of 59% (95% confidence interval (CI) = 51%-66%) and a pooled specificity of 98% (95% CI = 97%-98%), US for distal DVT had a poor sensitivity of 43% (95% CI = 38%-48%) and a pooled specificity of 95% (95% CI = 94%-96%), US for whole-leg DVT had a pooled sensitivity of 59% (95% CI = 54%-64%) and a pooled specificity of 95% (95% CI = 94%-96%), US for post-major orthopedic surgery patients had a pooled sensitivity of 52% (95% CI = 49%-55%), and US for other types of patients had a pooled sensitivity of 58% (95% CI = 43%-72%). Pure compression technique for DVT had a poor sensitivity of 43% (95% CI = 39%-48%), pure color/doppler technique for DVT had a pooled sensitivity of 58% (95% CI = 53%-63%), compression and color/doppler technique for DVT had a pooled sensitivity of 61% (95% CI = 48%-74%).

conclusionUS could be a useful tool for diagnosing DVT, but it has a lower positive rate and a higher false negative rate. The rate of missed diagnosis of lower-limb DVT by US amounts to 50% or so in the patients without symptoms of DVT. The negative results do not preclude the possibility of DVT and if appropriate heightened surveillance and continued monitoring or try a more accurate inspection method is warranted. The whole leg evaluation and color/doppler technique should be the preferred approach.

Indexed as

Delayed DiagnosisHumansLower ExtremityUltrasonographyVenous Thrombosis

Identifiers

PMID31517841
PMCPMC6750306

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.