Line Sepsis in Home Parenteral Nutrition Patients: Are There Socioeconomic Risk Factors? A Canadian Study
Bibliographic record
Abstract
BACKGROUND: Line sepsis complicates home parenteral nutrition (HPN). This study examined nonmedical risk factors that may contribute to line sepsis and compared 2 HPN programs with different administrative structures (Ontario and British Columbia [BC]) in terms of line sepsis and patient satisfaction. METHODS: A survey was developed to evaluate possible correlation between line sepsis and (1) patients' perceptions of HPN care, (2) family support, (3) community support, and (4) socioeconomic status. Data were analyzed by categorizing into high- and low-risk groups using a cutoff point. A second method analyzed the incidences of line sepsis as a continuous variable. RESULTS: Sixty-eight patients responded to the survey: 33 from Ontario (62%), 35 from BC (44%). Community agency, socioeconomic and educational status were not significant in determining line sepsis. Patients who had (1) medication or blood work done through the catheter, (2) a higher number of dependents, or (3) had a trained family member involved in HPN were in the high-risk category for line sepsis, in addition to patients who were part-time students or receiving social assistance. When comparing the provinces, there was no difference in line sepsis. However, significant differences between the provinces include (1) BC patients rate their level of care lower; (2) Ontario patients rely more on family members for HPN; and (3) Ontario patients have more community support. CONCLUSIONS: Line sepsis may be increased by some nonmedical risk factors. However, when comparing the 2 programs, rates of line sepsis were not influenced by different administrative structures.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".