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Record W4240291950 · doi:10.14740/jnr574

May Neutrophil to Lymphocyte Ratio Serve a Role in the Prediction of Clinical Features of Migraine?

2020· article· en· W4240291950 on OpenAlexvenueno aff
Halil Önder, Muhammed Mustafa Deliktas

Bibliographic record

VenueJournal of Neurology Research · 2020
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMigraineChronic MigraineInternal medicineFibromyalgiaNeurologyChronic fatigue syndromePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

Background: We aimed to investigate the possible association between the value of neutrophil to lymphocyte ratio ( NLR) and some specific features of migraine. Methods: We have included initially all the patients with migraine who applied to our neurology clinic in Yozgat City Hospital during December 2019 and agreed to participate in this study. The demographic and clinical characteristics including migraine subtype (episodic/chronic), headache frequency per month, headache characteristics of all patients were interrogated. Besides, the presence of fibromyalgia (FM) and chronic fatigue syndrome (CFS) was also noted. The severity of migraine was assessed using the headache impact test (HIT-6) and the severity of chronic fatigue was assessed using the Functional Assessment of Chronic Illness Therapy (FACIT) fatigue scale. A hemogram was performed upon admission to the clinic. The patients with migraine attacks during the clinic visits were excluded from the study. Results: Ultimately, 52 migraineurs were included in this study. The mean age was 37.34 ± 11.80 and the female/male (F/M) ratio was 49/3. Thirty-six patients (69%) were diagnosed with episodic migraine (EM), and 16 of them (31%) were diagnosed with chronic migraine (CM). The results of the comparative analyses between EM and CM groups showed that the NLR did not differ between groups. To evaluate the possible association of the NLR with other clinical parameters, additional comparative analyses evaluating the presence of FM, CFS, cognitive symptoms and tinnitus were also conducted, which showed no significant differences. The results of the correlation analyses to evaluate the possible associations between the NLR value and other clinical parameters were also unremarkable. Conclusions: We suggest that the NLR cannot be a specific marker to be used in the differential diagnosis or prediction of any features of migraines during the interictal period. However, in light of the previous reports, the utility of this value in the differentiating of migraine attacks from other causes of headache attacks can be investigated in future related studies. J Neurol Res. 2020;10(2):38-43 doi: https://doi.org/10.14740/jnr574

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.003
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 score0.307
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.214
GPT teacher head0.466
Teacher spread0.252 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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