ABSTRACT
Lumbar disc bulging or herniation (LDBH) is one of the major causes of spinal stenosis and related nerve compression, and its severity is the major determinant for spine surgery. MRI of the spine is the most important diagnostic tool for evaluating the need for surgical intervention in patients with LDBH. However, MRI utilization is limited by its low accessibility. Spinal X-rays can rapidly provide information on the bony structure of the patient. Our study aimed to identify the factors associated with LDBH, including disc height, and establish a clinical diagnostic tool to support its diagnosis based on lumbar X-ray findings. In this study, a total of 458 patients were used for analysis and 13 clinical and imaging variables were collected. Five machine-learning (ML) methods, including LASSO regression, MARS, decision tree, random forest, and extreme gradient boosting, were applied and integrated to identify important variables for predicting LDBH from lumbar spine X-rays. The results showed L4-5 posterior disc height, age, and L1-2 anterior disc height to be the top predictors, and a decision tree algorithm was constructed to support clinical decision-making. Our study highlights the potential of ML-based decision tools for surgeons and emphasizes the importance of L1-2 disc height in relation to LDBH. Future research will expand on these findings to develop a more comprehensive decision-supporting model.
ABSTRACT
BACKGROUND: There is growing recognition of the role of platelets in inflammation and immune responses, and platelets have been associated with various cardiovascular diseases. It is also known that neonatal morbidities are related to overall platelet activity, and platelet parameters may have the potential to predict morbidities and mortality in preterm infants. This study aimed to assess the initial platelet parameters and the association with major morbidities and mortality in preterm neonates. METHODS: We retrospectively reviewed data from very preterm neonates with a gestational age (GA) <32 weeks who were admitted between June 2020 and May 2021 for platelet parameters (counts, mean platelet volume (MPV), platelet distribution width (PDW) and plateletcrit (platelet counts x MPV/10000(%)) at birth. Major morbidities included early- onset sepsis (EOS) ≤3 days after birth, severe intraventricular hemorrhage (IVH) grade ≥3, and early or overall mortality. RESULTS: A total of 197 very preterm neonates were studied. Their mean (±SD) GA was 28.0 ± 2.4 weeks, birth weight was 990 ± 293 g, platelet counts were 245 ± 81 x1000/µL, MPV was 10.0 ± 0.7 fl, PDW was 11.0 ± 1.6 fl, and plateletcrit was 0.24 ± 0.08%. MPV had a weak negative correlation with both GA (r = -0.234, p = 0.001) and BW (r = -0.343, p <0.001). A lower plateletcrit was associated with EOS (0.14 (0.04-0.22) % vs. 0.23 (0.19-0.30) %, p = 0.027), severe IVH ≤7 days after birth (0.18 (0.14-0.27) % vs. 0.23 (0.20-0.30) %, p = 0.022), and early and overall mortality (0.15 (0.20-0.30) % vs. 0.23 (0.20-0.30) %, p = 0.049; 0.20 ± 0.09 % vs. 0.25 ± 0.07 %, p = 0.008). CONCLUSION: A lower plateletcrit within 24 hours of birth was associated with EOS, severe IVH ≤7 days after birth, and first-week and overall mortality in very preterm neonates.
