Risk Factors for Infection After Spinal Surgery
Bibliographic record
Abstract
STUDY DESIGN: A retrospective case control analysis of 48 cases of postoperative infection following spinal procedures. OBJECTIVES: Spinal procedures that became infected after surgery were analyzed to identify the significance of preoperative and intraoperative risk factors. Characterization of the nature and timing of the infections was also performed. SUMMARY OF BACKGROUND DATA: The rate of postoperative infection following spinal surgery varies widely depending on the nature of the procedure and the patient's diagnosis. Preoperative comorbidities and risk factors also influence the likelihood of infection. METHODS: A review of 1629 procedures performed on 1095 patients revealed that a postoperative infection developed in 48 patients (4.4%). Data regarding preoperative and intraoperative risk factors were gathered from patient charts for these and a randomly selected control group of 95 uninfected patients. For analysis, these patient groups were further divided into adult and pediatric subgroups, with an age cutoff of 18 years. Preoperative risk factors reviewed included smoking, diabetes, previous surgery, previous infection, steroid use, body mass index, and alcohol abuse. Intraoperative factors reviewed included staging of procedures, estimated blood loss, operating time, and use of allograft or instrumentation. RESULTS: The majority of infections occurred during the early postoperative period (less than 3 months). Age >60 years, smoking, diabetes, previous surgical infection, increased body mass index, and alcohol abuse were statistically significant preoperative risk factors. The most likely procedure to be complicated by an infection was a combined anterior/posterior spinal fusion performed in a staged manner under separate anesthesia. Infections were primarily monomicrobial, although 5 patients had more than 4 organisms identified. The most common organism cultured from the wounds was Staphylococcus aureus. All patients were treated with surgical irrigation and débridement, and appropriate antibiotics to treat the cultured organism. CONCLUSIONS: Aggressive treatment of patients undergoing complex or prolonged spinal procedures is essential to prevent and treat infections. Understanding a patient's preoperative risk factors may help the physician to optimize a patient's preoperative condition. Additionally, awareness of critical intraoperative parameters will help to optimize surgical treatment. It may be appropriate to increase the duration of prophylactic antibiotics or implement other measures to decrease the incidence of infection for high risk patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".