Systematic review and meta-analysis of risk factor for postoperative delirium following spinal surgery
Bibliographic record
Abstract
BACKGROUND: Postoperative delirium is a common psychiatric disorder among patients who undergo spinal surgery. The purpose of current meta-analysis was to assess the potential risk factors related to delirium in spinal surgery. METHODS: We searched the following databases: PubMed, EMBASE, the Cochrane Library, and Web of Science, from inception to July 2020. Two reviewers independently assessed the quality of the included studies using the previously described Newcastle-Ottawa Scale (NOS). We included spinal surgery patients who suffered with delirium or not. Stata 12.0 was used for meta-analysis. RESULTS: Thirteen trial studies that met our inclusion criteria were incorporated into the meta-analysis. Postoperative delirium was associated with an increase of the duration of hospital stay (P = 0.044) and increased perioperative readmission rate (P = 0.013) and economic costs (P = 0.002). This meta-analysis demonstrates that there were twenty-two risk factors: general characteristic: old age, female patients, history of surgery, diabetes mellitus, hypertension; preoperative data: low hematocrit, low hemoglobin, low albumin, low sodium, depression; operative data: operating time, total blood loss; postoperative data: low sodium, low hemoglobin, low hematocrit, low albumin, fever, low potassium, blood sugar, and visual analog scale (VAS). CONCLUSIONS: Delirium not only prolongs the length of hospital stay, but also increases readmission rate and the economic costs. Several risk factors including old age, female patients, history of surgery, diabetes mellitus, low hematocrit, low hemoglobin, low albumin, low sodium, depression; operative data: operating time, total blood loss, low sodium, low hemoglobin, low hematocrit, low albumin, fever, low potassium, blood sugar, and VAS were significant predictors for postoperative delirium after spinal surgery.
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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 | 0.012 | 0.146 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.014 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".