STUDY DESIGN: Retrospective study.PURPOSE: This study aimed to investigate the association of surgical intervention with clinical and quality of life (QoL) outcomes in patients who underwent posterior spinal surgery for lumbar spinal stenosis (LSS) with spinal calcium pyrophosphate dihydrate deposition (SCPPD) versus that in those who underwent the surgery for LSS without SCPPD.OVERVIEW OF LITERATURE: Calcium pyrophosphate (CPP)-associated arthritis is one of the most common types of arthritis. The clinical outcomes are well studied in CPP-associated arthritis of the appendicular joints. However, few studies have investigated SCPPD.METHODS: A single-institution database was reviewed. LSS patients were categorized as those who did and did not have SCPPD, based on histologic identification. Clinical presentations and postoperative results were analyzed. Disability and QoL were assessed using the Oswestry Disability Index (ODI) and the 36-item Short-Form Health Survey.RESULTS: Thirty-four patients were enrolled, with 18 patients being allocated to the SCPPD group and 16 being allocated to the non- SCPPD group. Preoperative and postoperative pain scores were not significantly different between the groups (p=0.33 and p=0.48, respectively). The average preoperative ODI score in the SCPPD group was slightly higher than that in the non-SCPPD group (57 vs. 51, p=0.33); however, the postoperative ODI score was significantly lower (15 vs. 43, p=0.01). The postoperative physical function, vitality, and mental health of the SCPPD patients were also significantly improved (p=0.03, p=0.022, and p=0.022, respectively).CONCLUSIONS: Surgical intervention resulted in good clinical outcomes in SCPPD patients. As per our findings, total removal of CPPinvolved tissue is unnecessary. As such, surgery should be performed as indicated according to clinical presentation without considering the presence of CPPD.
Arthritis ; Calcium Pyrophosphate ; Calcium ; Chondrocalcinosis ; Disability Evaluation ; Health Surveys ; Humans ; Joints ; Lumbar Vertebrae ; Mental Health ; Pain, Postoperative ; Quality of Life ; Retrospective Studies ; Spinal Stenosis

STUDY DESIGN: Retrospective cohort study. PURPOSE: To evaluate surgical outcomes and complications of cervical spine fractures in ankylosing spondylitis (CAS) patients who were treated using either the posterior (P) or combined approach (C). OVERVIEW OF LITERATURE: Ankylosing spondylitis typically causes progressive spinal stiffness that makes patients susceptible to spinal fractures. CAS is a highly unstable condition. There is contradictory evidence regarding which treatment option, the posterior or the combined approach, yields superior clinical results. METHODS: A single institution database was reviewed for data in the period 1999 to 2015. All CAS patients who underwent posterior or combined instrumented fusion were enrolled. We analyzed demographic data, radiographic results, perioperative complications, and postoperative results. RESULTS: Thirty-three patients were enrolled (23 in the P group, 10 in the C group). All patients presented with neck pain after a fall. In the P group, mean operative time was 161.1 minutes (100–327 minutes), and mean estimated blood loss (EBL) was 306.4 mL (50–750 mL). In the C group, 90% of patients underwent a staged procedure, typically with posterior surgery first. Mean EBL was 124 mL (25–337 mL). For posterior surgery, mean EBL was 458.3 mL (400–550 mL). EBL of posterior surgery in the C group was higher but this difference was not significant (p=0.16). Postoperative complication rate was higher in the C group but this difference was not significant (50% vs. 17.4%, p=0.09). In the follow-up period, no late reoperations were performed. Patients who underwent C surgery had a higher rate of neurological improvement but this difference was not significant (p=0.57). CONCLUSIONS: Both P and C provided good clinical results. P surgery had lower EBL, lower postoperative complication rate, and shorter length of stay than C surgery; none of these differences were statistically significant.
Cervical Vertebrae ; Cohort Studies ; Female ; Follow-Up Studies ; Humans ; Length of Stay ; Neck Pain ; Operative Time ; Postoperative Complications ; Reoperation ; Retrospective Studies ; Spinal Fractures ; Spine ; Spondylitis, Ankylosing

Methods: A registry of patients who underwent surgery (instrumentation, decompression, or fusion) for spinal metastases between 2004 and 2018 was used. The outcome measure was survival at postoperative days 90, 180, and 365. Preoperative variables were used to develop machine-learning algorithms to predict survival chance in each period. The performance of the algorithms was measured using the area under the receiver operating characteristic curve (AUC). Results: A total of 389 patients were identified, with 90-, 180-, and 365-day mortality rates of 18%, 41%, and 45% postoperatively, respectively. The XGBoost algorithm showed the best performance for predicting 180-day and 365-day survival (AUCs of 0.744 and 0.693, respectively). The CatBoost algorithm demonstrated the best performance for predicting 90-day survival (AUC of 0.758). Serum albumin had the highest positive correlation with survival after surgery. Conclusions These machine-learning algorithms showed promising results in predicting survival in patients who underwent spinal palliative surgery for spinal metastasis, which may assist surgeons in choosing appropriate treatment and increasing awareness of mortality-related factors before surgery.

Methods: This retrospective study included patients who underwent spinal metastasis at a university-based medical center in Thailand between January 2009 and November 2021. Collected data included preoperative parameters and ambulatory status 90 and 180 days following surgery. Thirteen machine-learning algorithms, namely, artificial neural network, logistic regression, CatBoost classifier, linear discriminant analysis, extreme gradient boosting, extra trees classifier, random forest classifier, gradient boosting classifier, light gradient boosting machine, naïve Bayes, K-neighbor classifier, Ada boost classifier, and decision tree classifier were developed to predict ambulatory status 90 and 180 days following surgery. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and F1-score. Results: In total, 167 patients were enrolled. The number of patients classified as ambulatory 90 and 180 days following surgery was 140 (81.9%) and 137 (82.0%), respectively. The extreme gradient boosting algorithm was found to most accurately predict 180-day ambulatory outcome (AUC, 0.85; F1-score, 0.90), and the decision tree algorithm most accurately predicted 90-day ambulatory outcome (AUC, 0.94; F1-score, 0.88). Conclusions Machine-learning algorithms were effective in predicting ambulatory status following surgery for spinal metastasis. Based on our data, the extreme gradient boosting and decision tree best predicted postoperative ambulatory status 180 and 90 days after spinal metastasis surgery, respectively.