Evaluation of Older Adults Hospitalized with a Diagnosis of Failure to Thrive
Bibliographic record
Abstract
BACKGROUND: older adults are sometimes hospitalized with the admission diagnosis of failure to thrive (FTT), often because they are not felt safe to be discharged back to their current living arrangement. It is unclear if this diagnosis indicates primarily a social admission or suggests an acute medical deterioration. The objective of this study was to explore the level of acuity and medical investigations commonly conducted among older hospitalized adults with a diagnosis of FTT. METHODS: We conducted a retrospective cohort study at three hospitals in Calgary, Alberta. Data were extracted from the electronic medical records of the 603 admissions of patients 65 years or older with a diagnosis of FTT between January 2010 and January 2011. Markers of medical acuity were evaluated. RESULTS: The vast majority of patients had short hospital stays. Specialist physicians were consulted for 323 cases (54%). Allied health-care professionals were consulted in 151 cases (25%). While in hospital, patients underwent extensive investigations, including CT scans, ultrasounds, and echo-cardiograms. Many patients received IV fluids (71%) and IV antibiotics (35%). CONCLUSIONS: The data suggest that acute illnesses, and not social factors, were the primary reason for admission among those given a diagnosis of FTT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".