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Vertigo And Dizziness Related Disorders: Clinical Spectrum and Management in A Clinic Based Otolaryngology Practice in an Urban Centre

2022· preprint· en· W4309521284 on OpenAlexaff
VISHWANATH NATESH

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsASTER
Fundersnot available
KeywordsVertigoMedicineBenign paroxysmal positional vertigoOtorhinolaryngologyObservational studyPhysical therapyTinnitusMedical historyPopulationPhysical examinationNauseaPediatricsRetrospective cohort studyQuality of life (healthcare)SurgeryAudiologyInternal medicine

Abstract

fetched live from OpenAlex

• Background: Vertigo / dizziness is a common problem encountered in clinical practice. It is described in different ways by each patient. Hence, it becomes difficult for the clinician to interpret and manage dizziness suffered by the patients. • Objective: To study demographics, types of vertigo / dizziness, its impact on the quality of life and management in a UAE otolaryngology clinic • Method: This is a retrospective, observational, descriptive study of patients presenting with dizziness in our medical facility, between September 2019 to March 2022. • Result: In the present study, 58.61% of the patients were male. Average age of the study population was 42.69 years. Vertigo/spinning type of dizziness was the most reported symptom. Most reported associated symptom was nausea, and the trigger was ‘head movement’. 56.30% of the study population was diagnosed with benign paroxysmal positional vertigo (BPPV). Most used diagnostic tool was Dix-Hallpike maneuver, and the management method was particle repositioning maneuver. The average baseline Dizziness Handicap Inventory (DHI) score was 19.37 (± 13.46), which reduced to 9.22 (±10.94) three weeks after treatment (p value <0.0001). • Conclusion: Vertigo / dizziness related to peripheral causes accounts for a significant proportion of cases in routine otolaryngology practice. From our study we can easily conclude that vertigo / dizziness related disorders negatively affect QOL. Proper diagnosis and management would help to improve the symptoms and QOL. Simple office-based, patient-oriented detail history taking, and clinical examination is important in the diagnosis and management of the dizziness. History taking or questions should focus on the type of dizziness, associated features, duration, and triggers which would help in pinpointing differential diagnosis and the management. Red flags like focal neurological signs should be taken seriously and investigated further. Keywords: Dizziness, vertigo, Dix-Hallpike maneuver, particle repositioning maneuver, DHI

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.336
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2022
Admission routes1
Has abstractyes

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