scholarly journals Drivers and Risk Factors of Unplanned 30-Day Readmission Following Spinal Cord Stimulator Implantation

2017 ◽  
Vol 21 (1) ◽  
pp. 87-92 ◽  
Author(s):  
Aladine A. Elsamadicy ◽  
Amanda Sergesketter ◽  
Xinru Ren ◽  
Syed Mohammed Qasim Hussaini ◽  
Avra Laarakker ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spinal Cord ◽  
Spinal Cord Stimulator

Risk Factors and Survival Analysis of Spinal Cord Stimulator Explantation

2020 ◽  
Author(s):  
Mark C. Dougherty ◽  
Royce W. Woodroffe ◽  
Saul Wilson ◽  
George T. Gillies ◽  
Matthew A. Howard ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spinal Cord ◽  
Survival Analysis ◽  
Spinal Cord Stimulator

Spinal Cord Stimulator Implant Infection Rates and Risk Factors: A Multicenter Retrospective Study

2017 ◽  
Vol 20 (6) ◽  
pp. 558-562 ◽  
Author(s):  
Bryan C. Hoelzer ◽  
Mark A. Bendel ◽  
Timothy R. Deer ◽  
Jason S. Eldrige ◽  
David R. Walega ◽  
...  
Keyword(s):  
Risk Factors ◽  
Spinal Cord ◽  
Retrospective Study ◽  
Spinal Cord Stimulator ◽  
Infection Rates ◽  
Implant Infection

scholarly journals Development of Predictive Informatics Tool Using Electronic Health Records to Inform Personalized Evidence-Based Pressure Injury Management for Veterans with Spinal Cord Injury

2021 ◽  
Vol 186 (Supplement_1) ◽  
pp. 651-658
Author(s):  
Kath M Bogie ◽  
Steven K Roggenkamp ◽  
Ningzhou Zeng ◽  
Jacinta M Seton ◽  
Katelyn R Schwartz ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Care ◽  
Spinal Cord ◽  
Spinal Cord Injury ◽  
User Interface ◽  
Veterans Health Administration ◽  
Study Cohort ◽  
Veterans Health ◽  
Health Administration ◽  
Cord Injury

ABSTRACT Background Pressure injuries (PrI) are serious complications for many with spinal cord injury (SCI), significantly burdening health care systems, in particular the Veterans Health Administration. Clinical practice guidelines (CPG) provide recommendations. However, many risk factors span multiple domains. Effective prioritization of CPG recommendations has been identified as a need. Bioinformatics facilitates clinical decision support for complex challenges. The Veteran’s Administration Informatics and Computing Infrastructure provides access to electronic health record (EHR) data for all Veterans Health Administration health care encounters. The overall study objective was to expand our prototype structural model of environmental, social, and clinical factors and develop the foundation for resource which will provide weighted systemic insight into PrI risk in veterans with SCI. Methods The SCI PrI Resource (SCI-PIR) includes three integrated modules: (1) the SCIPUDSphere multidomain database of veterans’ EHR data extracted from October 2010 to September 2015 for ICD-9-CM coding consistency together with tissue health profiles, (2) the Spinal Cord Injury Pressure Ulcer and Deep Tissue Injury Ontology (SCIPUDO) developed from the cohort’s free text clinical note (Text Integration Utility) notes, and (3) the clinical user interface for direct SCI-PIR query. Results The SCI-PIR contains relevant EHR data for a study cohort of 36,626 veterans with SCI, representing 10% to 14% of the U.S. population with SCI. Extracted datasets include SCI diagnostics, demographics, comorbidities, rurality, medications, and laboratory tests. Many terminology variations for non-coded input data were found. SCIPUDO facilitates robust information extraction from over six million Text Integration Utility notes annually for the study cohort. Visual widgets in the clinical user interface can be directly populated with SCIPUDO terms, allowing patient-specific query construction. Conclusion The SCI-PIR contains valuable clinical data based on CPG-identified risk factors, providing a basis for personalized PrI risk management following SCI. Understanding the relative impact of risk factors supports PrI management for veterans with SCI. Personalized interactive programs can enhance best practices by decreasing both initial PrI formation and readmission rates due to PrI recurrence for veterans with SCI.

scholarly journals The neurological level of spinal cord injury and cardiovascular risk factors: a systematic review and meta-analysis

Spinal Cord ◽  
2021 ◽  
Author(s):  
Peter Francis Raguindin ◽  
Gion Fränkl ◽  
Oche Adam Itodo ◽  
Alessandro Bertolo ◽  
Ramona Maria Zeh ◽  
...  
Keyword(s):  
Risk Factors ◽  
Systematic Review ◽  
Blood Pressure ◽  
Spinal Cord ◽  
Cardiovascular Risk ◽  
Meta Analysis ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Low Density ◽  
Cord Injury

Abstract Study design Systematic review and meta-analysis. Objective To determine the difference in cardiovascular risk factors (blood pressure, lipid profile, and markers of glucose metabolism and inflammation) according to the neurological level of spinal cord injury (SCI). Methods We searched 5 electronic databases from inception until July 4, 2020. Data were extracted by two independent reviewers using a pre-defined data collection form. The pooled effect estimate was computed using random-effects models, and heterogeneity was calculated using I2 statistic and chi-squared test (CRD42020166162). Results We screened 4863 abstracts, of which 47 studies with 3878 participants (3280 males, 526 females, 72 sex unknown) were included in the meta-analysis. Compared to paraplegia, individuals with tetraplegia had lower systolic and diastolic blood pressure (unadjusted weighted mean difference, −14.5 mmHg, 95% CI −19.2, −9.9; −7.0 mmHg 95% CI −9.2, −4.8, respectively), lower triglycerides (−10.9 mg/dL, 95% CI −19.7, −2.1), total cholesterol (−9.9 mg/dL, 95% CI −14.5, −5.4), high-density lipoprotein (−1.7 mg/dL, 95% CI −3.3, −0.2) and low-density lipoprotein (−5.8 mg/dL, 95% CI −9.0, −2.5). Comparing individuals with high- vs. low-thoracic SCI, persons with higher injury had lower systolic and diastolic blood pressure (−10.3 mmHg, 95% CI −13.4, −7.1; −5.3 mmHg 95% CI −7.5, −3.2, respectively), while no differences were found for low-density lipoprotein, serum glucose, insulin, and inflammation markers. High heterogeneity was partially explained by age, prevalent cardiovascular diseases and medication use, body mass index, sample size, and quality of studies. Conclusion In SCI individuals, the level of injury may be an additional non-modifiable cardiovascular risk factor. Future well-designed longitudinal studies with sufficient follow-up and providing sex-stratified analyses should confirm our findings and explore the role of SCI level in cardiovascular health and overall prognosis and survival.

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