299. Paediatric Collaborative Network on Infections in Canada (PICNIC) Study of the Current Landscape of Gram Negative Bacteremias
Bibliographic record
Abstract
Abstract Background Antimicrobial resistance is a public health threat, invasive infection from multi-drug resistant gram-negative (MDRGN) pathogens is associated with significant morbidity and mortality. The incidence of MDRGN bacteremia in Canada is rising, and pediatric data is limited. Methods This retrospective chart review of paediatric patients with gram negative bacteremia in a multicenter PICNIC database (n=7 centers) from 2013 to 2017. MDRGN was defined as enterobacteriaceae that were resistant to third generation cephalosporins (including ESBL, CPE). Ethics approval was obtained at all sites, and data was entered into a secure REDCAP database, descriptive statistics are described herein. Results Of the 676 bacteremia patients in the database, 214 (31.7%) were gram negative pathogens. E. coli was the most frequent pathogen (59.8%, of which 22 of 128 were MDR), followed by Klebsiella (31.8%, of which 9 of 68 were MDR). Of the 31 MDRGNs, 19 were ESBL, 1 was a CPE, and 11 were nonspecific mechanisms of resistance. There were no multidrug resistant Pseudomonas, Stenotrophomonas, or Acinetobacter. The majority of patient were less than 3 months of age (59.3%) and were male (58.8%). The majority had an underlying comorbid condition; hematoncologic diagnosis accounting for 14.5%. Length of stay varied from 1 to 742 days (mean 72, standard deviation 88). 11% required admission to ICU, 10% required removal of a intravascular catheter, 7% required a change in ventilation status, 2% requiring procedural source control, and there was an 8% mortality rate. Treatment duration greater than 14 days occurred in 123 patients (61% of patients). Conclusion This preliminary analysis of a multicenter review of pediatric gram negative bacteremias demonstrates a higher risk in neonates with comorbid conditions. A surprisingly prolonged treatment duration of greater than 14 days occurred in the majority of patients. Further analysis to assess factors associated with prolonged treatment durations, MDR infection, and complications is required. Gram negative bacteremia remains a significant cause of morbidity and mortality in pediatric patients. Disclosures All Authors: No reported disclosures
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".