Long Term Trends in the Occurrence of Nosocomial Blood Stream Infection
Bibliographic record
Abstract
OBJECTIVE: To determine trends in the occurrence of nosocomial blood stream infection at the University of Alberta Hospital. METHODS: A prospective survey of nosocomial blood stream infection was conducted; cases from August 1986 to December 1996 were reviewed. Cases were detected by a review of positive blood cultures reported by the microbiology laboratory. Centers for Disease Control and Prevention definitions of nosocomial infection were used to categorize isolates as nosocomial, community acquired or contaminant. RESULTS: There were 2389 cases; primary bacteremia was the most common source (57%), followed by urinary tract, respiratory tract and surgical site sources (10% each). The nosocomial blood steam infection rate rose progressively from 6.0/1000 admissions and 4.59/10,000 patient days in 1986 to 11.2/1000 admissions and 14.31/10,000 days in 1996 (P<0.01); 48% of the total increase in rate occurred between 1995 and 1996. Significant increases occurred between 1986 and 1996 in primary infections (from 3.2 to 7.5/1000 admissions, P<0.01) and infections from all secondary sources (from 2.5 to 3.8/1000 admissions, P=0.01). Coagulase-negative staphylococci (27%), Staphylococcus aureus (19%) and enterococci (9%) were the most common microbial causes. Aerobic Gram-negative bacilli accounted for 28% and candida for 6%. Coagulase-negative staphylococci, enterococci and candida all became more prevalent as causes of infection over the study period. CONCLUSIONS: The nosocomial blood stream infection rate in the hospital has nearly doubled in the past 10 years, largely due to increased primary bacteremia.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".