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Analysis of the characteristic changes of macular thickness in patients with Parkinson′s disease

2019· article· en· W3031644729 on OpenAlex
Jiahao Zhao, Na Wu, Ying Wan, Lu Song, Gan Jing

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueChin J Neurol · 2019
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOphthalmologyReceiver operating characteristicParkinson's diseaseMacular degenerationNeurologyMontreal Cognitive AssessmentQuadrant (abdomen)Internal medicineDiseaseSurgeryCognitive impairmentPsychiatry

Abstract

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Objective To analyze the characteristic changes of macular thickness in patients with Parkinson′s disease by spectral-domain optical coherence tomography (SD-OCT), and find out the association between macular thickness and disease progression, cognitive dysfunction, visuospatial impairment and asymmetry of motor symptoms. Methods Seventy-one Parkinson′s disease (PD) patients who were admitted to the Department of Neurology, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine from January 2016 to May 2018 and sixty-one healthy controls who volunteered to participate for the same period were enrolled and underwent SD-OCT examination. The macular thickness of all retinal quadrant segments, foveal thickness, and macular volume between the two groups were comparatively analyzed. Associations between macular measurements and clinical parameters such as disease duration, Unified Parkinson′s Disease Rating Scale part Ⅲ (UPDRS-Ⅲ) scores, Montreal Cognitive Assessment (MoCA) total scores, and visuospatial subscores were analyzed using generalized estimated equation fitted with linear regression models. Results Mean macular thickness in the PD group was significantly reduced compared with those in the control group ((261.94±12.90) μm vs (270.96±10.71) μm, B=-8.135, P<0.01). All quadrants of macular thickness (except fovea and 1 mm central zone) in the PD group were reduced compared with those in the control group. Receiver operating characteristic (ROC) curve analysis revealed that inner superior thickness could predict the presence of PD with an area under ROC of 0.727 (95%CI 0.662-0.792, P<0.01). UPDRS-Ⅲscores were negatively correlated with foveal thickness (B=-9.132, P=0.034), 1 mm central zone thickness (B=6.963, P=0.036) and all quadrants of the inner ring (superior (B=-7.727, P<0.01), inferior (B=-5.169, P=0.044), nasal (B=-5.960, P<0.01) and temporal (B=-5.905,P<0.01)) macular thickness. The disease duration had no relationship with any quadrant of macular measurements. No statistically significant difference was found between the macula parameters of the hemiretinae corresponding to more and less severely affected cerebral hemisphere. MoCA total scores were positively correlated with all quadrants of the inner ring (superior (B=2.693, P=0.007), inferior (B=3.391, P=0.002), nasal (B=2.609, P=0.001) and temporal (B=2.115, P=0.013)) macular thickness. MoCA visuospatial subscores were positively associated with average macular thickness (B=4.368, P=0.042), macular volume (B=0.161, P=0.004), inferior (B=8.582, 6.541), nasal (B=8.130, 6.017) and temporal (B=5.938, 5.316) quadrants of outer and inner rings macular thickness (all P<0.05). Conclusions In PD patients, the macular thickness and macular volume were decreased. Asymmetry was not identified between hemiretinae in PD. Some quadrants of macular thickness were associated with disease progression, cognitive dysfunction, and visuospatial impairment. Key words: Parkinson disease; Optical coherence tomography; Macular retina; Asymmetry; Visuospatial impairment

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.217
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it