•Risk factors for inpatient VTE are different from those diagnosed post-discharge.•Patients with EBL> 500cc, corpectomies, osteotomies and foraminotomies have higher rates of post-discharge ...VTE.•Spinal fractures is a risk factor for inpatient VTE.
retrospective chart review.
We aimed to determine the perioperative risk factors that lead to inpatient or post-discharge venous thromboembolism (VTE) events after spinal surgery.
While many studies relate the risk factors in a post-surgical setting to the incidence of VTE, this study aims to separate these VTE into inpatient and post-discharge categories to examine timing and risk factors.
We analyzed 6869 patients from 2009 to 2015 using Current Procedural Technology codes from a single tertiary academic institution. Patients were stratified based on occurrence and setting of VTE then controlled for perioperative characteristics with exclusion criteria being patients undergoing minor spine surgeries or secondary procedures.
In 170 VTE events, these factors were associated with increased risk for: Inpatient DVT only: IVC filter (OR 6.380 3.414−11.924), longer length of hospital stay (OR 1.083 1.047−1.120), a prior history of DVT (OR 3.640 1.931−6.856). Post-discharge DVT only: history of PE (OR 45.142 6.785−300.351), having a corpectomy (OR 26.670 3.477−204.548), and having an osteotomy (OR 18.877 1.129−315.534). Inpatient PE only: surgery >4 h (OR 30.820, p < 0.001), fracture (OR 6.913, p = 0.004), IVC filter (OR 3.135, p = 0.029). Post-discharge PE only: corpectomy (OR 541.271, p = 0.009), foraminotomy (OR 40.137, p = 0.013), EBL > 500cc (OR 2467.798, p = 0.002). Time to onset of VTE events was significantly longer for patients undergoing osteotomy (7.43 days) than for patients with fracture (4.28 days), which is consistent with our findings that fracture was an independent predictor of inpatient VTE, and osteotomy was an independent predictor of post-discharge VTE (p = 0.018).
Time-to-VTE varies between types of surgeries. Some risk factors are independently associated with VTE at all times during the 30-day postoperative period, while other factors are only associated with either inpatient or post-discharge VTE. Those patients with high-risk features for post-discharge VTE merit increased study for thromboprophylaxis management.
•Postoperative surgical site infection after posterior spinal fusion was examined.•Machine learning and artificial intelligence were used to create a model.•The model had high predictive ...value.•Factors protective against infection were identified.•Machine learning and artificial intelligence should be employed in clinical decision making.
Machine Learning and Artificial Intelligence (AI) are rapidly growing in capability and increasingly applied to model outcomes and complications within medicine. In spinal surgery, post-operative surgical site infections (SSIs) are a rare, yet morbid complication. This paper applied AI to predict SSIs after posterior spinal fusions.
4046 posterior spinal fusions were identified at a single academic center. A Deep Neural Network DNN classification model was trained using 35 unique input variables The model was trained and tested using cross-validation, in which the data were randomly partitioned into training n = 3034 and testing n = 1012 datasets. Stepwise multivariate regression was further used to identify actual model weights based on predictions from our trained model.
The overall rate of infection was 1.5 %. The mean area under the curve (AUC), representing the accuracy of the model, across all 300 iterations was 0.775 (95 % CI 0.767,0.782) with a median AUC of 0.787. The positive predictive value (PPV), representing how well the model predicted SSI when a patient had SSI, over all predictions was 92.56 % with a negative predictive value (NPV), representing how well the model predicted absence of SSI when a patient did not have SSI, of 98.45 %. In analyzing relative model weights, the five highest weighted variables were Congestive Heart Failure, Chronic Pulmonary Failure, Hemiplegia/Paraplegia, Multilevel Fusion and Cerebrovascular Disease respectively. Notable factors that were protective against infection were ICU Admission, Increasing Charlson Comorbidity Score, Race (White), and being male. Minimally invasive surgery (MIS) was also determined to be mildly protective.
Machine learning and artificial intelligence are relevant and impressive tools that should be employed in the clinical decision making for patients. The variables with the largest model weights were primarily comorbidity related with the exception of multilevel fusion. Further study is needed, however, in order to draw any definitive conclusions.
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Background: Tumor Necrosis Factor Alpha (TNF-a) inhibitors suppress the immune system in patients with systemic inflammatory conditions. Long term data assessing future cancer ...risk for these patients is not known. We assessed long term risk of malignancy in patients with Rheumatoid Arthritis RA, Inflammatory Bowel Disease IBD, Psoriasis PS, and Ankylosing Spondylitis AS, who were or were not exposed to a TNF-a inhibitor. Methods: This was a retrospective, cohort study conducted using electronic medical record data for patients with complete demographic and treatment data at Northwestern Medicine from years 1998 to 2020 (RA: n = 10763; IBD: n = 12106; PS: n = 1920; AS: n = 5103). Inverse Probability of Treatment Weighting (IPTW) was used to balance the distributions of age, race, gender, smoking status, and follow-up time across exposure groups within each inflammatory condition type. Relative risk (RR) of malignancy based on TNF-a exposure was assessed using logistic regression. Results: 2583 (24.0%) of RA, 2185 (18.0%) of IBD, 1811 (94.3%) of PS, 572 (11.2%) of AS patients had TNF-a exposure. Median follow-up for patients was 43 months. The RR for any cancer was higher for patients exposed to a TNF-a agent with rheumatoid arthritis (RR 1.121 (95% CI 1.02-1.23, p = 0.015) and psoriasis (RR 1.763 (95% CI 1.32-2.37, p < 0.001). The relative risk of any cancer was lower in patients exposed to a TNF-a agent with IBD (RR 0.858 (95% CI 0.78-0.94, p = 0.001). No significant difference in relative risk associated with TNF-a exposure was detected with ankylosing spondylitis (RR 0.929 (95% CI 0.8-1.08, p = 0.344). Conclusions: Patients with RA or PS and TNF-a exposure had higher RR of overall malignancy. Patients with IBD and TNF-a exposure had lower risk of overall malignancy. TNF-a immunosuppression may alter cancer risk differently based on the disease states for which it is being used. This information is critical when counseling patients on long term risk and screening strategies when considering TNF-a inhibition.
Clinical trials require significant resources, but benefits are only realized after trial completion and dissemination of results. We comprehensively assessed early discontinuation, registry results ...reporting, and publication by trial sponsor and subspecialty in urology trials.
We assessed trial registrations from 2007 to 2019 on ClinicalTrials.gov and publication data from PubMed®/MEDLINE®. Associations between sponsor or subspecialty with early discontinuation were assessed using Cox proportional hazards and results reporting or publication with logistic regression at 3 years after completion.
Of 8,636 trials 3,541 (41.0%) were completed and 999 (11.6%) were discontinued. Of completed trials 26.9% reported results and 21.6% were published. Sponsors included academic institutions (53.1%), industry (37.1%) and the U.S. government (9.8%). Academic-sponsored (adjusted HR 0.81, 95% CI 0.69-0.96, p=0.012) and government-sponsored trials (adjusted HR 0.62, 95% CI 0.49-0.78, p <0.001) were less likely than industry to discontinue early. Government-sponsored trials were more likely to report (adjusted OR 1.72, 95% CI 1.17-2.54, p=0.006) and publish (adjusted OR 1.89, 95% CI 1.23-2.89, p=0.004). Academic-sponsored trials were less likely to report (adjusted OR 0.65, CI:0.48-0.88, p=0.006) but more likely to publish (adjusted OR 1.72, 95% CI 1.25-2.37, p <0.001). These outcomes were similar across subspecialties. However, endourology was more likely to discontinue early (adjusted HR 2.00, 95% CI 1.53-2.95, p <0.001), general urology was more likely to report results (adjusted OR 1.54, 95% CI 1.13-2.11, p=0.006) and andrology was less likely to publish (adjusted OR 0.53, 95% CI 0.35-0.81, p=0.003).
Sponsor type is significantly associated with trial completion and dissemination. Government-sponsored trials had the best performance, while industry and academic-sponsored trials lagged in completion and results reporting, respectively. Subspecialty played a lesser role. Lack of dissemination remains a problem for urology trials.
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