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Record W3126759302 · doi:10.14740/ijcp419

Primary Care Referral Perspectives in Pediatric Failure to Thrive and Outcomes From a Diagnostic Clinic

2021· article· en· W3126759302 on OpenAlexvenueno aff
G. Lisius, Tony Tarchichi

Bibliographic record

VenueInternational Journal of Clinical Pediatrics · 2021
Typearticle
Languageen
FieldMedicine
TopicChild Nutrition and Feeding Issues
Canadian institutionsnot available
FundersUniversity of Pittsburgh
KeywordsMedicineReferralFailure to thrivePsychological interventionSnackingPsychosocialPrimary careMedical diagnosisEtiologyPediatricsGrowth chartIntensive care medicineFamily medicineNursingPsychiatryObesityInternal medicine

Abstract

fetched live from OpenAlex

Background: Decades of data demonstrate the overwhelming rates of failure to thrive (FTT) nutritional causes (80-90%) even in patients with complex medical conditions and diagnoses. Primary care providers (PCPs), the initial FTT evaluators, have been underrepresented in the FTT literature, despite their pivotal role in overseeing management. Our purpose was to assess PCPs ’ FTT referral strategies and their concerns for their FTT patients referred to an academic pediatrician diagnostic clinic. Methods: We surveyed PCPs who referred FTT patients to a diagnostic clinic (the Diagnostic Referral Group (DRG)) for their main concern prompting referral, and next management if consult was unavailable. Chart review determined the hospitalization rates of FTT patients, and DRG interventions. Results: Of the 81 PCP responses, 66.7% were most concerned with an uncertain underlying diagnosis, contrasting with the 20.6% of patients that DRG providers suspected to have an organic etiology. PCPs ’ next preferable management was subspecialist referral (58.0%) and hospitalization (22.2%). DRG providers most commonly recommended nutritional interventions such as increasing caloric density, decreased snacking and juice, and structured meals for 72.4% of patients. Conclusions: This study suggests that FTT due to nutritional causes continues to be a challenging diagnosis for PCPs. More investigation is needed to identify interventions to empower primary providers to diagnose nutritional causes, such as practical standardized assessments to evaluate the nutritional and psychosocial FTT contributors. Int J Clin Pediatr. 2021;10(1):1-5 doi: https://doi.org/10.14740/ijcp419

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)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.013
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 integrity0.0000.001
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 head0.066
GPT teacher head0.415
Teacher spread0.348 · 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.

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
Published2021
Admission routes1
Has abstractyes

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