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Logistic Regression and Elastic Net Regularization for the Diagnosis of Fibromyalgia (LEDF)

12. september 2019 opdateret af: Dinesh Kumbhare, Toronto Rehabilitation Institute

Logistic Regression and Elastic Net Regularization for the Diagnosis of Fibromyalgia: A Quantitative Approach Using B-Mode Ultrasound

This study will utilize ultrasound image texture variables to construct an elastic net regularized, logistic regression model to differentiate between healthy and Fibromyalgia patients. The collected ultrasound data will be from participants who are healthy, and from participants who have Fibromyalgia. The predicted performance accuracy of the diagnostic model will be validated and this will confirm or deny the hypothesis that differentiation between the two cohorts is possible.

Studieoversigt

Status

Afsluttet

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

Fibromyalgia (FM) diagnosis remains a challenge for clinicians due to a lack of objective diagnostic tools. One proposed solution is the use of quantitative ultrasound (US) techniques, such as image texture analysis, which has demonstrated discriminatory capabilities with other chronic pain conditions. The investigators propose the use of US image texture variables to construct an elastic net regularized, logistic regression model, for differentiating between the trapezius muscle in the healthy and FM patients. 162 Ultrasound videos of the right and left trapezius muscle were acquired from healthy participants and participants with FM. The videos will then be put through a mutli-step processing pipe including converting them into skeletal muscle regions of interest (ROI). The ROI's will be then filtered by an algorithm utilizing the complex wavelet structural similarity index (CW-SSIM), which removes ROI's that are too similar to one another. Eighty-eight texture variables will be extracted from the ROI's, which will be used in nested cross-validation to construct a logistic regression model with and without elastic net regularization. The generalized performance accuracy of both models will be estimated and confirmed with a final validation on a holdout test set. Depending on the predicted, generalized performance accuracy it will be validated or not by the final, holdout test set (confirming the model construction is accurate). These models should then confirm or deny the hypothesis that a regularized logistic regression model built on ultrasound texture features can accurately differentiate between healthy trapezius muscle and that of patients with FM.

Undersøgelsestype

Observationel

Tilmelding (Faktiske)

81

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiesteder

  • Canada
    • Ontario
      • Toronto, Ontario, Canada, M5G2A2
        • Toronto Rehabilitation Institute

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

20 år til 65 år (Voksen, Ældre voksen)

Tager imod sunde frivillige

Ja

Køn, der er berettiget til at studere

Alle

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

Patients diagnosed with Fibromyalgia and healthy age-matched controls.

Beskrivelse

Inclusion Criteria:

  • gender independent; chronic widespread pain, fitting the 2016 FM criteria, absence of myofascial pain syndrome trigger points and between the ages of 20 and 65 years (44.3 ± 13.9 years).
  • Healthy asymptomatic volunteers who were age matched (n = 17) with no physical complaints or abnormality on physical examination also participated.

Exclusion Criteria:

  • Participants were excluded if they demonstrated clinical evidence of another cause for widespread pain, such as polymyositis, dermatomyositis, endocrine disorders, etc. None of the participants had performed any physical exercise during the two to three days prior to entry into the study.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
Intervention / Behandling
Fibromyalgia
Patients who display symptoms and have a history of Fibromyalgia, between 20-65 years of age.
Diagnostisk test: Ultrasound Imaging
B-mode ultrasound pictures of the upper Trapezius were collected from both left and right sides.
Healthy Controls
Age-matched, healthy controls, between 20-65 years of age who present no signs of chronic pain.
Diagnostisk test: Ultrasound Imaging
B-mode ultrasound pictures of the upper Trapezius were collected from both left and right sides.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Ultrasound Image Texture Variables
Tidsramme: 1 hour
91 statistical image texture variables are extracted from the B mode ultrasound images from both cohorts in order to construct a diagnostic model. The texture variables will be extracted using MATLAB.
1 hour
Fibromyalgia Diagnostic Criteria
Tidsramme: 10 minutes
This evaluates symptoms related to Fibromyalgia and determines a score to assess the severity. This score is comprised of the Widespread Pain Index(WPI), which quantifies the regions of pain, and the Symptom Severity Scale(SSS), which measures qualitative aspects of pain such as fatigue and cognitive symptoms. The WPI scale ranges from 0-19 (0- no areas of body pain, 19- all body regions have pain), whereas the SSS ranges from 0-12 (0-no qualitative aspects of pain, 12-many qualitative aspects of pain). This criteria was evaluated on each patient to determine which cohort they belong to. According to the Fibromyalgia Diagnostic Criteria, one is diagnosed with Fibromyalgia if they have a WPI score of 7 or higher, and a SSS score of 5 or higher. Fibromyalgia is also diagnosed with a score of 3-6 on the WPI score, and a score of 9 or higher on the SSS score.
10 minutes
Central Sensitization Inventory
Tidsramme: 10 minutes
This is a self reported outcome measure designed to identify patients that experience central sensitization. It involves 25 questions which include symptomatic experiences. The subject must answer on a scale of 0(never) to 5(always) corresponding to how often they experience these. The maximum score is 100 and a score of more than 40 indicates the presence of Central Sensitization. This criteria was evaluated on each patient to determine which cohort they belong to.
10 minutes

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Toronto Rehabilitation Institute

Efterforskere

  • Ledende efterforsker: Dinesh Kumbhare, MD,PhD, Toronto Rehabilitation Institute

Publikationer og nyttige links

Den person, der er ansvarlig for at indtaste oplysninger om undersøgelsen, leverer frivilligt disse publikationer. Disse kan handle om alt relateret til undersøgelsen.

Generelle publikationer

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

1. september 2018

Primær færdiggørelse (Faktiske)

6. september 2019

Studieafslutning (Faktiske)

6. september 2019

Datoer for studieregistrering

Først indsendt

11. september 2019

Først indsendt, der opfyldte QC-kriterier

12. september 2019

Først opslået (Faktiske)

13. september 2019

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

17. september 2019

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

12. september 2019

Sidst verificeret

1. september 2019

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Yderligere relevante MeSH-vilkår

Andre undersøgelses-id-numre

  • FibromyalgiaDiagnosis

Plan for individuelle deltagerdata (IPD)

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INGEN

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