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Record W2563959272 · doi:10.1111/anae.13780

Evaluation of the accuracy of common weight estimation formulae in a Zambian paediatric surgical population

2016· article· en· W2563959272 on OpenAlexaff
Lowri Bowen, M. Zyambo, David Snell, John Kinnear, M. Dylan Bould

Bibliographic record

VenueAnaesthesia · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
FundersEuropean Resuscitation CouncilWorld Health Organization
KeywordsMedicineWeight estimationMalnutritionPediatricsSevere Acute MalnutritionEstimationBody weightPopulationObesityStatisticsEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Limited resources and access to healthcare in sub-Saharan Africa are associated with high rates of malnourished children, although many countries globally are demonstrating increasing childhood obesity. This study evaluated how well current age- or height-based formulae estimate the weight of children undergoing surgery in Zambia. All children under 14 years of age presenting for elective surgery at the University Teaching Hospital, Lusaka, had both height and weight measured. Their actual weight was compared against estimated weight from various formulae. The Broselow tape outperformed all the age-based formulae, demonstrating the lowest median percentage error of -5.8%, with 46.0% of estimates falling within 10% of the actual measured weight (p < 0.001). Of the 1111 children who were eligible for World Health Organization growth standard appraisal, 88 (8%) met the weight criteria for severe acute malnutrition. Our results are consistent with other studies in finding that the Broselow tape is the best estimator of weight in a lower middle-income country, followed by the original Advanced Paediatric Life Support formula if the Broselow tape is unavailable.

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 score0.313
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.022
GPT teacher head0.302
Teacher spread0.279 · 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

Citations11
Published2016
Admission routes1
Has abstractyes

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