Reporting Surgical Site Infections (SSIs) Using Different Surveillance Systems— Complexity of Infection Matters
Bibliographic record
Abstract
Background: In Alberta, Canada, surgical site infections (SSIs) following total hip (THR) and knee replacements (TKR) are reported using 2 data sources: infection prevention and control (IPC), which surveys all THR and TKR using NHSN definitions and the Canadian International Classification of Disease, Tenth Revision (ICD-10-CA) codes, and the National Surgical Quality Improvement Program (NSQIP), which uses a systematic sampling process that involves an 8-day cycle schedule, modified NHSN definitions and current procedural terminology (CPT) codes. We compared the similarities and discrepancies in THR/TKR SSI reporting. Methods: A retrospective multisite cohort study of IPC and NSQIP THR/TKR SSI data at 4 hospitals was performed. SSI data were collected between September 1, 2015, and March 31, 2018. Demographic information and complex and total SSIs reported by IPC and NSQIP were compared for both THR and TKR surgeries. To determine whether both data sources reported similar trends over time, total SSIs by quarter were compared. Univariate analyses using a t test for age and the χ 2 test for gender for complex SSIs and total SSIs was performed. The Pearson correlation and the Shapiro-Wilk test were used to assess the THR and TKR trends between the 2 data sources. A P value of <.05 was considered significant. Results: Following the removal of duplicates and missing data, 7,549 IPC and 2,037 NSQIP patients, respectively, were compared. Age, gender, and other demographic parameters were not significantly different. Total THR and TKR SSIs per 100 procedures using NSQIP data were significantly higher than the same rates using IPC data: THR, 2.25 versus 0.92 ( P < .05) and TKR, 3.43 versus 1.26 ( P < .05). Both IPC and NSQIP data indicated increasing total THR SSI rates over time, but with different magnitudes (r = 0.658). For total TKR SSI, the IPC rate decreased, whereas the NSQIP rate increased over the same period (r = 0.374). When superficial SSIs were excluded, the rates reported between IPC and NSQIP data by hospital and by procedure type were more comparable, with trends toward higher rates reported by NSQIP for THR than for TKR: THR, 1.19 versus 0.68 ( P = 0.15) and TKR, 0.92 versus 0.80 ( P = .68). Conclusions: Different approaches used to monitor SSIs following surgeries may lead to different results and trend patterns. NSQIP reports total SSI rates that are significantly higher than the IPC Alberta orthopedic population predominantly as a result of increased identification of superficial SSIs. Because the diagnosis of superficial SSIs may be less reliable, SSI reporting should focus on complex infections. Funding: None Disclosures: None
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".