Objective: In 2020, Mekhail et al published a formula that predicted the likelihood of a successful outcome for those who undergo spinal cord stimulation (SCS) for long-term pain management, based on retrospectively collected clinical and demographic data from one major medical center. The aim of this study is to validate such a predictive formula, prospectively, in a cohort of patients from multiple medical practices that are more representative of real-life clinical practice.
Materials And Methods: For the study, 939 patients who underwent successful SCS or targeted drug delivery (TDD) trials at multiple independent medical centers in the USA were enrolled into the Medtronic product surveillance registry data base before they underwent SCS or TDD device implantation, from 2018 to 2020. The registry data were collected prospectively but not specifically for this study. The data examined included demographic information, pain diagnosis, pain scores (visual analog scale [VAS]), Oswestry Disability Index scores, and quality-of-life scores at baseline and six months after implant. Because our goal is to validate the previously published predictive formula, in addition to the outcomes data previously mentioned, we collected the variables necessary for such a task: sex, age, depression, the presence of neuropathic pain, spine-related pain diagnosis, and persistent spinal pain syndrome "post laminectomy syndrome." Spine-related pain diagnosis included subjects with chronic spine pain who never had back surgery and whose pain was not radicular nor neuropathic.
Results: Of 619 patients with SCS, 138 (22%) achieved ≥ 50% reductions of the baseline VAS at six months. The logistic model predicts SCS success with an area under the receiver operating characteristic curve (AUC) of 80% in the current validation data set. Of 320 patients with TDD, 147 (46%) achieved ≥ 50% reduction of the baseline VAS at six months. The logistic model predicts TDD success with an AUC of 78% in the current validation data set.
Conclusion: The study provides real life validation of the previously published predictive formula(4).
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http://dx.doi.org/10.1016/j.neurom.2023.02.083 | DOI Listing |
Eur J Haematol
January 2025
Faculty of Medicine, Tel Aviv University, Tel Aviv-Yafo, Israel.
Background: Bone marrow examination (BME) is the gold standard of diagnosing myelodysplastic syndromes (MDS).
Problems: it is invasive, painful, causing possible bleeding, inaccurate (aspirate hemodilution), and subjective (inter-observer interpretation discordance). We developed non-invasive diagnostic tools: A logistic regression formula [LeukRes 2018], then a web algorithm using 10 variables (age, gender, Hb, MCV, WBC, ANC, monocytes, PLT, glucose, creatinine) to diagnose/exclude MDS [BldAdv 2021].
BMC Nephrol
January 2025
Nutrition Research Center, Department of Clinical Nutrition, School of Nutrition and Food Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
Background: The prevalence of chronic kidney disease (CKD) is estimated to be about 13.4% worldwide. Studies have shown that CKD accounts for up to 2% of the health cost burden.
View Article and Find Full Text PDFBMC Genomics
January 2025
Department of Food, Bioprocessing, & Nutrition Sciences, North Carolina State University, Raleigh, NC, USA.
Background: The advent of next generation sequencing technologies has enabled a surge in the number of whole genome sequences in public databases, and our understanding of the composition and evolution of bacterial genomes. Besides model organisms and pathogens, some attention has been dedicated to industrial bacteria, notably members of the Lactobacillaceae family that are commonly studied and formulated as probiotic bacteria. Of particular interest is Lactobacillus acidophilus NCFM, an extensively studied strain that has been widely commercialized for decades and is being used for the delivery of vaccines and therapeutics.
View Article and Find Full Text PDFSci Rep
January 2025
Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal do Paraná (UTFPR), Curitiba, 80230-901, Brazil.
Modeling the Digital Twin (DT) is an important resource for accurately representing the physical entity, enabling it to deliver functional services, meet application requirements, and address the disturbances between the physical and digital realms. This article introduces the Log Mean Kinematics Difference Synchronization (SyncLMKD) to measure the kinematic variations distributed among Digital Twin elements to ensure symmetric values relative to a reference. The proposed method employs abductive reasoning and draws inspiration from the Log Mean Temperature Difference (LMTD).
View Article and Find Full Text PDFJ Forensic Odontostomatol
December 2024
Department of Medicine and Health Science "Vincenzo Tiberio", University of Molise, AgeEstimation Project, Campobasso, Italy.
Forensic age estimation is performed by assessing pulp chamber constrictions due to physiological age-related changes in dental radiographs; however, the estimated ages occasionally deviate from the actual ages. In particular, long-term steroid users tend to demonstrate pulp chamber constrictions in all teeth. Because this is uncommon among younger age groups, caution should be exercised when evaluating pulp chamber constriction.
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