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250.5: Early Predictors of Enteral Autonomy in Pediatric Intestinal Failure:Development of a Disease Severity Score

2019· article· en· W2969940375 on OpenAlexaff
Christina Belza, Kevin T. Fitzgerald, Nicole de Silva, Yaron Avitzur, Paul W. Wales

Bibliographic record

VenueTransplantation · 2019
Typearticle
Languageen
FieldNursing
TopicClinical Nutrition and Gastroenterology
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineEnteral administrationParenteral nutritionInternal medicineShort bowel syndromeGastroenterologyProportional hazards modelRetrospective cohort studyUnivariate analysisSepsisMultivariate analysis

Abstract

fetched live from OpenAlex

Introduction: Patients with short bowel syndrome (SBS) are dependent on parenteral nutrition (PN) while their bowel attempts to compensate for loss of function. Our objective was to create a SBS disease severity score that would predict the probability of achieving enteral autonomy (EA) using clinical variables available in the early postoperative period. Methods: A retrospective cohort study of SBS children managed by our Intestinal Rehabilitation Program (IRP) was completed. Data abstracted included demographic, anatomic and outcome variables including serum conjugated bilirubin, proportion of enteral nutrition (EN) and episodes of sepsis specifically at 6 months post gut loss. A univariate analysis and Cox proportional hazards (CPH) model was performed. A score predicting EA was created based on weighting of Cox model coefficients. For all analyses, an alpha-value of <0.05 was considered significant. Results: 139 patients were analyzed (61% males). Ninety-five (68%) achieved EA. Those who achieved EA had a longer residual small bowel (75% vs 24%; p<0.0001) and colon (100% vs 75%; p<0.0001) and were less likely to have the ileocecal valve removed (26% vs 57%; p=0.0005). At 6 months, children who achieved EA had higher enteral tolerance (100% vs 30%; p<0.0001), a lower conjugated bilirubin (0 vs 71.5umol/L; p<0.0001) and less septic episodes (1.0 vs 2.0; p=0.0112). Cox proportional hazards modeling found >50% residual small bowel (HR 2.68 [95%CI 1.60–4.49], p<0.001), ICV intact (HR 0.61 [95%CI 0.37–1.02], p<0.06) and >50% enteral tolerance at 6 months (HR 5.70 [95% CI 2.77–11.74] p<0.001) were positively associated with EA. Conjugated bilirubin >34umol/L at 6 months was negatively associated with EA (HR 0.42 [95%CI 0.27–0.66], p<0.001). A severity score was created by weighting CPH parameter estimates [small bowel length >50%, ICV intact, CB<34umol/L and EN>50% for a maximum score of 8. Disease severity strata were developed (severe [0–2; 25.7% EA], moderate [3–5; 52.9% EA] and mild [6–8; 97.1% EA]. Disease severity strata were developed (severe [0–2; 9/35 (25.7%) EA], moderate [3–5; 18/34 (52.9%) EA and mild [6–8; 68/70 (97.1%) EA]. Conclusion: We propose a paediatric intestinal failure disease severity score that predicts probability of EA, stratified into mild, moderate and severe. The score allows prognostication of individual patients, and could assist research by adjusting outcome reporting or stratifying recruitment.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.254
Teacher spread0.241 · 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 designSimulation or modeling
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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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