17 research outputs found

    Spatiotemporal Pattern of Neuroinflammation After Impact-Acceleration Closed Head Injury in the Rat

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    Inflammatory processes have been implicated in the pathogenesis of traumatic brain damage. We analyzed the spatiotemporal expression pattern of the proinflammatory key molecules: interleukin-1β, interleukin-6, tumor necrosis factor-α, and inducible nitric oxide synthase in a rat closed head injury (CHI) paradigm. 51 rats were used for RT-PCR analysis after CHI, and 18 for immunocytochemistry. We found an early upregulation of IL-1β, IL-6, and TNF-α mRNA between 1 h and 7 h after injury; the expression of iNOS mRNA only revealed a significant increase at 4 h. After 24 h, the expression decreased towards baseline levels, and remained low until 7 d after injury. Immunocytochemically, IL-1β induction was localized to ramified microglia in areas surrounding the primary impact place as well as deeper brain structures. Our study shows rapid induction of inflammatory gene expression that exceeds by far the primary impact site and might therefore contribute to tissue damage at remote sites

    Clinical course and prognostic models for the conservative management of cervical radiculopathy: a prospective cohort study

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    Purpose: To describe the clinical course and develop prognostic models for poor recovery in patients with cervical radiculopathy who are managed conservatively. Methods: Sixty-one consecutive adults with cervical radiculopathy who were referred for conservative management were included in a prospective cohort study, with 6- and 12-month follow-up assessments. Exclusion criteria were the presence of known serious pathology or spinal surgery in the past. Outcome measures were perceived recovery, neck pain intensity and disability level. Multiple imputation analyses were performed for missing values. Prognostic models were developed using multivariable logistic regression analyses, with bootstrapping techniques for internal validation. Results: About 55% of participants reported to be recovered at 6 and 12 months. All multivariable models contained 2 baseline predictors. Longer symptoms duration increased the risk of poor perceived recovery, whereas the presence of paresthesia decreased this risk. A higher neck pain intensity and a longer duration of symptoms increased the risk of poor relief of neck pain. A higher disability score increased the risk of poor relief of disability, and larger active range of rotation toward the affected side decreased this risk. Following bootstrapping, the explained variance of t

    Baseline Patient Characteristics Commonly Captured Before Surgery Do Not Accurately Predict Long-Term Outcomes of Lumbar Microdiscectomy Followed by Physiotherapy

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    Study Design.Prospective cohort study.Objective.To develop and internally validate prognostic models based on commonly collected preoperative data for good and poor outcomes of lumbar microdiscectomy followed by physiotherapy.Summary of Background Data.Lumbar microdiscectomy followed by physiotherapy is a common intervention for lumbar radiculopathy. Postoperatively, a considerable percentage of people continues to experience pain and disability. Prognostic models for recovery are scarce.Methods.We included 298 patients with lumbar radiculopathy who underwent microdiscectomy followed by physiotherapy. Primary outcomes were recovery and secondary outcomes were pain and disability at 12 months follow-up. Potential prognostic factors were selected from sociodemographic and biomedical data commonly captured preoperatively. The association between baseline characteristics and outcomes was evaluated using multivariable logistic regression analyses.Results.At 12 months follow-up, 75.8% of the participants met the criterion for recovery. Variables in the model for good recovery included: younger age, leg pain greater than back pain, high level of disability, and a disc herniation at another level than L3-L4. The model for poor recovery included: lower educational level, prior back surgery, and disc herniation at L3-L4. Following internal validation, the explained variance (Nagelkerke R 2) and area under the curve for both models were poor (≤0.02 and ≤0.60, respectively). The discriminative ability of the models for disability and pain were also poor.Conclusion.The outcome of microdiscectomy followed by postoperative physiotherapy cannot be predicted accurately by commonly captured preoperative sociodemographic and biomedical factors. The potential value of other biomedical, personal, and external factors should be further investigated.Level of Evidence: 3

    Variability in recovery following microdiscectomy and postoperative physiotherapy for lumbar radiculopathy: A latent class trajectory analysis

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    Objectives: The clinical course of lumbar radiculopathy following microdiscectomy and post-operative physiotherapy varies substantially. No prior studies assessed this variability by deriving outcome trajectories. The primary aims of this study were to evaluate the variability in long-term recovery after lumbar microdiscectomy followed by post-operative physiotherapy and to identify outcome trajectories. The secondary aim was to assess whether demographic, clinical characteristics and patient-reported outcome measures routinely collected at baseline could predict poor outcome trajectories. Methods: We conducted a prospective cohort study with a 24-month follow-up. We included 479 patients with clinical signs and symptoms of lumbar radiculopathy confirmed by Magnetic Resonance Imaging findings, who underwent microdiscectomy and post-operative physiotherapy. Outcomes were leg pain and back pain measured with Visual Analogue Scales, and disability measured with the Roland-Morris Disability Questionnaire. Descriptive statistics were performed to present the average and the individual clinical course. A latent class trajectory analysis was conducted to identify leg pain, back pain, and disability outcome trajectories. The best number of clusters was determined using the Bayesian Information Criterion, Akaike's information criteria, entropy, and overall interpretability. Prediction models for poor outcome trajectories were assessed using multivariable logistic regression analyses. Results: Several outcome trajectories were identified. Most patients were assigned to the ‘large improvement’ trajectory (leg pain: 79.3%; back pain: 70.2%; disability: 59.5% of patients). Smaller proportions of patients were assigned to the ‘moderate improvement’ trajectory (leg pain: 7.9%; back pain: 10.6%; disability: 20.7% of patients), the ‘minimal improvement’ trajectory (leg pain: 4.9%, back pain: 6.7%, disability: 16.3% of patients) and the ‘relapse’ trajectory (leg pain: 7.9%; back pain: 12.5%; disability: 3.5%). Approximately one-third of patients (32.6%) belonged to one or more than one poor outcome trajectory. Patients with previous treatment (prior back surgery, injection therapy, and medication use) and those who had higher baseline pain and disability scores were more likely to belong to the poor outcome trajectories in comparison to the large improvement trajectories in back pain, leg pain and disability, and the moderate improvement trajectory in disability. The explained variance (Nagelkerke R2) of the prediction models ranged from 0.06 to 0.13 and the discriminative ability (Area Under the Curve) from 0.66 to 0.73. Conclusion: The clinical course of lumbar radiculopathy varied following microdiscectomy and post-operative physiotherapy, and several outcome trajectories could be identified. Although most patients were allocated to favorable trajectories, one in three patients was assigned to one or more poor outcome trajectories following microdiscectomy and post-operative physiotherapy for lumbar radiculopathy. Routinely gathered data were unable to predict the poor outcome trajectories accurately. Prior to surgery, clinicians should discuss the high variability and the distinctive subgroups that are present in the clinical course with their patients
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