Landscape of the Lumbar Cartilaginous End Plate Microbiota and Metabolites in Patients with Modic Changes.

BACKGROUND: Modic changes (MCs), vertebral end plate and bone marrow damage observed by magnetic resonance imaging, are an independent risk factor for low back pain. The compositions of and interaction between microbiota and metabolites in the lumbar cartilaginous end plates (LCEPs) of patients with MCs have not been identified. METHODS: Patients with lumbar disc degeneration who were undergoing lumbar spinal fusion surgery were recruited between April 2020 and April 2021. LCEPs were collected for 16S rRNA sequencing and liquid chromatography-mass spectrometry (LC/MS)-based targeted metabolomic profiling. Of the 54 patients recruited, 24 had no MCs and 30 had changes classified as Modic type 2 or 3. The primary goal was to identify specific genera of microbiota associated with MCs, and secondary goals included investigating differences in metabolites between patients with and without MCs and exploring the correlation between these metabolites and microorganisms. RESULTS: Investigation of the microbiota community structure revealed that both alpha diversity and beta diversity were significantly different between patients with and without MCs, and the abundances of 26 genera were significantly different between these 2 groups. Metabolomic analysis revealed that 26 metabolites were significantly different between the 2 groups. The unsaturated fatty acid pathway was found to be the main pathway related to MCs. Multiomic correlation analysis suggested that Caulobacteraceae (unclassified) and Mycobacterium, Clostridium, Blautia, and Bifidobacterium at the genus level were linked to dysregulation of fatty acid metabolism, contributing to the pathogenesis of MCs. CONCLUSIONS: Our study represents a foundational effort to examine the landscape of the microbiota and metabolites in patients with MCs, informing future studies on the pathogenesis of and targeted therapy for MCs. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Modic changes in patients with lumbar disc herniation followed more than 1 year after lumbar discectomy: a systematic review and meta-analysis.

Background: Modic changes (MCs) are identified as an independent risk factor for low back pain. Different subtypes of MCs vary in their impact on postoperative pain relief. However, consensus on the transformation of postoperative MC fractions in patients with distinct MC subtypes is lacking. Methods: This comprehensive systematic review and meta-analysis searched English-language articles in PubMed, Cochrane Library, Web of Science, and Embase databases until January 2024. Studies included focused on patients transitioning between various microcrack subtypes post-discectomy. The primary outcome measure was the transformation between different postoperative microcrack fractions. Results: Eight studies with 689 participants were analyzed. Overall, there is moderate to high-quality evidence indicating differences in the incidence of MC conversion across MC subtypes. The overall incidence of MC conversion was 27.7%, with rates of 37.0%, 20.5%, and 19.1% for MC0, MC1, and MC2 subtypes, respectively. Thus, postoperative MC type transformation, particularly from preoperative MC0 to MC1 (17.7%) or MC2 (13.1%), was more common, with MC1 transformation being predominant. Patients with preoperative comorbid MC1 types (19.0%) exhibited more postoperative transitions than those with MC2 types (12.4%). Conclusion: This study underscores the significance of analyzing post-discectomy MCs in patients with lumbar disc herniation, revealing a higher incidence of MCs post-lumbar discectomy, particularly from preoperative absence of MC to MC1 or MC2. Preoperative MC0 types were more likely to undergo postoperative MC transformation than combined MC1 or MC2 types. These findings are crucial for enhancing surgical outcomes and postoperative care.

Development and validation of a radiomics-based model for predicting osteoporosis in patients with lumbar compression fractures.

BACKGROUND: Osteoporosis, a metabolic bone disorder, markedly elevates fracture risks, with vertebral compression fractures being predominant. Antiosteoporotic treatments for patients with osteoporotic vertebral compression fractures (OVCF) lessen both the occurrence of subsequent fractures and associated pain. Thus, diagnosing osteoporosis in OVCF patients is vital. PURPOSE: The aim of this study was to develop a predictive radiographic model using T1 sequence MRI images to accurately determine whether patients with lumbar spine compression fractures also have osteoporosis. STUDY DESIGN: Retrospective cohort study. PATIENT SAMPLE: Patients over 45 years of age diagnosed with a fresh lumbar compression fracture. OUTCOME MEASURES: Diagnostic accuracy of the model (area under the ROC curve). METHODS: The study retrospectively collected clinical and imaging data (MRI and DEXA) from hospitalized lumbar compression fracture patients (L1-L4) aged 45 years or older between January 2021 and June 2023. Using the pyradiomics package in Python, features from the lumbar compression fracture vertebral region of interest (ROI) were extracted. Downscaling of the extracted features was performed using the Mann-Whitney U test and the least absolute shrinkage selection operator (LASSO) algorithm. Subsequently, six machine learning models (Naive Bayes, Support Vector Machine [SVM], Decision Tree, Random Forest, Extreme Gradient Boosting [XGBoost], and Light Gradient Boosting Machine [LightGBM]) were employed to train and validate these features in predicting osteoporosis comorbidity in OVCF patients. RESULTS: A total of 128 participants, 79 in the osteoporotic group and 49 in the nonosteoporotic group, met the study's inclusion and exclusion criteria. From the T1 sequence MRI images, 1906 imaging features were extracted in both groups. Utilizing the Mann-Whitney U test, 365 radiologic features were selected out of the initial 1,906. Ultimately, the lasso algorithm identified 14 significant radiological features. These features, incorporated into six conventional machine learning algorithms, demonstrated successful prediction of osteoporosis in the validation set. The NaiveBayes model yielded an area under the receiver operating characteristic curve (AUC) of 0.84, sensitivity of 0.87, specificity of 0.70, and accuracy of 0.81. CONCLUSIONS: A NaiveBayes machine learning algorithm can predict osteoporosis in OVCF patients using t1-sequence MRI images of lumbar compression fractures. This approach aims to obviate the necessity for further osteoporosis assessments, diminish patient exposure to radiation, and bolster the clinical care of patients with OVCF.

Efficacy and safety of ketamine as an adjuvant to regional anesthesia: A systematic review and meta-analysis of randomized controlled trials.

STUDY OBJECTIVE: To identify whether adding ketamine to the local anesthetics (LA) in the regional anesthesia could prolong the duration of analgesia. DESIGN: A Systematic review and meta-analysis of randomized controlled trials. SETTING: The major dates were obtained in the operating room and the postoperative recovery ward. PATIENTS: A total of 1011 patients at ASA physical status I and II were included in the analysis. Procedure performed including cesarean section, orthopedic, radical mastectomy, urological or lower abdominal surgery and intracavitary brachytherapy implants insertion. INTERVENTIONS: After an extensive search of the electronic database, patients received regional anesthesia combined or not combined general anesthesia and with or without adding ketamine to LA were included in the analysis. The regional anesthesia includes spinal anesthesia, brachial plexus block, pectoral nerve block, transversus abdominis plane block and femoral and sciatic nerve block. MEASUREMENT: The primary outcome was the duration of analgesia. Secondary outcomes were the duration and onset time of motor and sensory block as well as the ketamine-related adverse effect. Data are expressed in mean differences in continuous data and odds ratios (OR) for dichotomous data with 95% confidence intervals. The risk of bias of the included studies was evaluated using the revised Cochrane risk of bias tool for randomized trials. The quality of evidence for each outcome was rated according to the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) Working Group system. MAIN RESULT: Twenty randomized controlled trials were included in the analysis. When ketamine was used as an adjuvant to LA, the duration of analgesia could be prolonged(172.21 min, 95% CI, 118.20 to 226.22; P<0.00001, I2 = 98%), especially in the peripheral nerve block(366.96 min, 95% CI, 154.19 to 579.74; P = 0.0007, I2 = 98%). Secondary outcomes showed ketamine could prolong the duration of sensory block(29.12 min, 95% CI, 10.22 to 48.01; P = 0.003, I2 = 96%) but no effect on the motor block(6.94 min, 95% CI,-2.65 to 16.53;P = 0.16, I2 = 84%), the onset time of motor and sensory block (motor onset time, -1.17 min, 95% CI, -2.67 to 0.34; P = 0.13, I2 = 100%; sensory onset time, -0.33 min, 95% CI,-0.87 to 0.20; P = 0.23, I2 = 96%) as well as the ketamine-related adverse effect(OR, 1.97, 95% CI,0.93 to 4.17;P = 0.08, I2 = 57%). CONCLUSION: This study indicates that ketamine could be an ideal adjuvant to local anesthetics regardless of the types of anesthesia. Overall, the quality of the evidence is low.

Is discectomy effective for treating low back pain in patients with lumbar disc herniation and Modic changes? A systematic review and meta-analysis of cohort studies.

BACKGROUND CONTEXT: Previous low-quality evidence has suggested preoperative Modic changes (MC) showed a trend toward less improvement in low back pain in patients with lumbar disc herniation (LDH) undergoing discectomy. However, a recent meta-analysis concluded that the presence of preoperative MC did not significantly impact clinical outcomes following lumbar discectomy. PURPOSE: To compare low back pain and functional outcomes of patients after discectomy for LDH with preoperative MC. STUDY DESIGN: Systematic review and meta-analysis of cohort studies. METHODS: This comprehensive systematic review and meta-analysis used English-language articles identified through searches using Pubmed, Web of Science, Embase, and Cochrane library until August 2022. The included studies identified publications that concentrated on the patients suffering from LDH with different preoperative MCs treated by discectomy. The Visual Analogue Scale (VAS) and the Oswestry Disability Index (ODI) were the two main metrics to evaluate outcomes. RESULTS: A series of 2,299 LDH patients with a definitive type of MC were included in four retrospective and five prospective studies. Overall, there is moderate to high quality evidence suggesting no significant difference between normal and MC groups for pain outcomes as well as normal and Modic type 2 groups in terms of pain or functional outcomes at one or two-year follow up. There are less functional outcomes in LDH patients with preoperative MC compared with no MC at 2-year follow up and showed no significant difference at 1-year follow-up. However, above all results may due to heterogeneity. Subgroup analysis revealed that only Modic type 1 showed statistically lower functional scores (mean difference in ODI scores range from 0 to 100) compared with Modic type 2 or compared with no MC at 2-year follow-up and showed no significant difference at 1-year follow-up (MC1 vs. MC0, p=.24, MD= -2.70; 95% CI, -7.15 to 1.76 for 1-year;p<.00001, MD= -7.92; 95% CI, -11.19 to -4.66 for 2 years. MC1 vs. MC2, p=.58, MD= -1.29; 95% CI, -5.83 to 3.25 for 1-year;p<.0001, MD= -6.77; 95% CI, -9.94 to -3.61 for 2 years). CONCLUSIONS: These data suggest LDH patients with or without preoperative MCs show a similar improvement of low back pain at 1 and 2-year follow-up and functional scores after discectomy at one-year follow-up. LDH patients with preoperative Modic type 1 are associated with worse functional status after discectomy at 2-year follow-up. However, high-quality randomized controlled trials and prospective cohort studies which focus on analyzing the risk and confounding factors are lacking.