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Record W4205257037 · doi:10.1111/jocd.14758

Oral clonidine as a pre‐anesthetic medication in hair transplantation surgery—A pilot study

2022· article· en· W4205257037 on OpenAlexaff
Venkataram Mysore, Shivshankar Muniswamy, Namitha Chathra, Jayashree Venkataram

Bibliographic record

VenueJournal of Cosmetic Dermatology · 2022
Typearticle
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsSKiN Health
Fundersnot available
KeywordsClonidineMedicineAnesthesiaSedationAnalgesicSedativeAnestheticSurgeryTransplantation

Abstract

fetched live from OpenAlex

BACKGROUND: Hair transplantation (HT) is a safe and rewarding procedure for a patient as well as the surgeon. Clonidine may be a good adjuvant in HT because of its analgesic, anxiolytic, and sedative effects. OBJECTIVE: To study efficacy of Clonidine as a preoperative medication in HT. METHODS & MATERIALS: The study was a prospective trial of 46 consecutive patients who underwent HT between January and May 2017. Patients with normal vital parameters on arrival were given Tab clonidine (0.1 mg) 30 min before starting of the procedure [Clonidine group (n = 30)]; rest were included in the control group (n = 16). Vitals were monitored every 30 min during surgery until the end. Patients were assessed for pain, level of sedation during surgery and for postoperative analgesia. RESULT: All patients who received clonidine, except one, were comfortable and experienced no pain throughout the duration of surgery; nine went into deep sleep. Of the 16 patients in the control group, no patients reported deep sleep, 3 felt restless, and 4 had mild pain. There were no untoward effects in both groups. CONCLUSION: Our study suggests that clonidine is useful as a pre-anesthetic medication in HT. However, this is a pilot study and further larger studies are needed.

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)0.001
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 score0.339
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.295
Teacher spread0.271 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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