ArticleJournal of healthcare engineering2022
Diagnostic Value of Model-Based Iterative Algorithm in Tuberculous Pleural Effusion.
Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- ADA as main biochemical marker in patients with tuberculous effusion.Journal of medical biochemistry · 2023Article
- Retracted: Diagnostic Value of Model-Based Iterative Algorithm in Tuberculous Pleural Effusion.Journal of healthcare engineering · 2023Article
- Morphological manifestation of tuberculous pleurisy in children under medical thoracoscope and diagnostic value.Annals of thoracic medicineArticle
Corrections and comments
- Retraction · 2023-12-06Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although there are several diagnostic modalities for tuberculous pleurisy, there is still a lack of easy, cost-effective, and rapid methods for confirming the diagnosis. In order to facilitate clinicians to diagnose patients with tuberculous pleurisy at an early stage, help patients to obtain treatment early, and reduce lung damage, it is hoped that new techniques will be available in the future to help diagnose tuberculous pleurisy rapidly in the clinic. To this end, this paper investigates the problem of bidirectional consistency based on event-triggered iterative learning. Firstly, a dynamic linearized data model of TB pleurisy intelligent system is established using compact-form dynamic linearization method, and a parameter estimation algorithm of TB pleurisy data model is proposed; then, based on this data model, an output observer and a dead zone controller are designed, and an event-triggered distributed model-free iterative learning bidirectional consistency control strategy is constructed by combining with signal graph theory. In this paper, 112 patients with pleural effusion were collected, including 76 patients with confirmed or clinically diagnosed tuberculous pleural effusion and 36 patients with nontuberculous pleural effusion. Pleural effusion T-SPOT.TB, blood T-SPOT.TB, pleural effusion Xpert MTB/RIF, and pleural effusion adenosine deaminase (ADA) tests were performed before treatment in the included patients. The sensitivity of pleural effusion T-SPOT.TB was higher than that of peripheral blood T-SPOT.TB (76.32%, 58/76), pleural effusion Xpert MTB/RIF (65.79%, 50/76), and pleural effusion ADA (28.95%, 22/76); the differences were statistically significant (
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Identifiers
What OpenQuestion holds
Registered trials
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.