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Record W2032376187 · doi:10.1186/1710-1492-8-s1-a7

Measured depth of subcutaneous tissue on posterolateral arm of aeroallergen immunotherapy patients

2012· article· en· W2032376187 on OpenAlexaffvenue
Laura Kim, Ryan Potts, Clark Eeuwes, Arunmozhi Dominic, Immaculate Nevis, Harold L Kim

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2012
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsWestern UniversityMcMaster UniversityUniversity of WaterlooMcGill University
Fundersnot available
KeywordsMedicineLogistic regressionInternal medicine

Abstract

fetched live from OpenAlex

Subcutaneous immunotherapy (SIT) injections for aeroallergens are often utilized in patients. SIT should be injected into the subcutaneous space in the mid-posterolateral upper arm. If the injections are given intramuscularly (IM), there may be an increased risk of anaphylaxis. In our allergy clinic, SIT is given with BD Safety Glide™ Allergy syringes with needle length 13 mm. There is a risk of the SIT being injected IM if patients have a skin to muscle depth (STMD) less than 13 mm. Charts were reviewed in an allergy clinic for patients on SIT where an ultrasound of the left posterolateral arm was done to measure STMD. Baseline characteristics of the two groups of patients with STMD greater than, and less than or equal to 13 mm were compared. The proportions of patients with STMD greater than 4mm, 6 mm, 8 mm, and 10 mm were calculated. Multivariable logistic regression was performed with age, sex, BMI and race. Ultrasounds had been completed on 186 patients on SIT. There were 149 (80%) with STMD less than 13mm. Baseline characteristics including age, sex and BMI differed among the two groups ( p < 0.05). Based on the logistic regression analysis, BMI was significantly associated with STMD. There were 168 (90%) patients with more than 4mm STMD. With standard allergy syringes, most patients on SIT are at risk of receiving the injections IM. A needle length of 4 mm would significantly decrease the risk of SIT being given IM.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.023
GPT teacher head0.301
Teacher spread0.278 · 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
Published2012
Admission routes2
Has abstractyes

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