Perioperative Major Non-neurological Complications in 105 Patients Undergoing Posterior Vertebral Column Resection Procedures for Severe Rigid Deformities
Bibliographic record
Abstract
STUDY DESIGN: Retrospective study. OBJECTIVE: To analyze the perioperative major non-neurological complications (MNNCs) in posterior vertebral column resection (PVCR) procedures for severe rigid deformities and to identify the factors that may increase the risk. SUMMARY OF BACKGROUND DATA: Although surgeons constantly attempted to increase the corrective efficacy and neurological safety after PVCR, there are still significant risks of major and potentially life-threatening complications. METHODS: A total of 105 consecutive patients with severe rigid deformity who underwent 1-stage PVCR at a single center from 2004 to 2013 were reviewed. The demographic data, medical and surgical histories, perioperative and final follow-up radiographical measurements, and prevalence of perioperative MNNCs were reviewed. RESULTS: The mean age of patients at the time of surgery was 18.9 years (range: 10-45 yr). The major curve of scoliosis was 108.9 ± 25.5 preoperatively and 37.2 ± 16.8 at the final follow-up, and segmental kyphosis was from 89.8 ± 31.1 to 30.4 ± 15.3. There were 31 MNNCs in 24 patients: 16 respiratory complications in 13 patients, 9 cardiovascular adverse events in 7 cases, 1 malignant hyperthermia, and 1 optic deficit. There were 3 patients with wound infection, and 1 of them had to undergo partial removal of the implant for infection control. One patient with neurofibromatosis died 1 day after operation. Factors that showed no relationships with an increased prevalence of MNNCs were age, sex, presence of cardiac disease or neural axis malformation, and both sagittal and coronal correction rate. Patients with T6 and upper resected level, undergoing PVCR at the early period, showed a trend toward more MNNCs encountered. Moreover, nonidiopathic deformity, large scoliotic curve greater than 150°, percent predicated forced vital capacity and forced expiratory volume in 1 second (FEV1.0) less than 40%, and estimated blood loss volume more than 5000 mL were identified as risk factors associated with MNNCs. CONCLUSION: Patients who had undergone PVCR experienced expected higher rate of MNNCs, with an overall prevalence of 22.9%. When considering PVCR, it is important to recognize the significantly higher inherent risks and provide appropriate preoperative counseling on the risks and benefits of surgery. LEVEL OF EVIDENCE: 3.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".