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Background and Objectives: The increasing use of whole-body computed tomography (WBCT) examinations, also known as panCT, in emergency departments for trauma patients has raised concerns about potential overuse and the associated risk of unnecessary radiation exposure. The purpose of this study was to examine the utilization patterns and findings of panCT scans performed over one year at a major academic hospital. Materials and Methods: This retrospective cohort study included 531 stable trauma adult patients who underwent panCT scans in 2023. De-identified data for each patient, including the radiology report, age, gender, and total dose-length product (DLP) of the panCT scan, were retrieved and reviewed. Radiology reports were classified based on the findings as negative (no acute traumatic injuries) or positive, with positive reports further subclassified based on injury location. Injury severity scores (ISS) were also calculated based on the findings of the radiology reports. Statistical analysis was performed using the Python programming language to assess any association between the independent variables (age and gender) and the dependent variable (report findings: negative or positive). Results: About 57% (n = 303) of the panCT scans included in the analysis were negative. The chi-squared test and logistic regression revealed a significant association between age and report finding (negative or positive), while no association with gender was found. One-third of positive cases (n = 72) had injuries only in the head and neck (H&N) region, and another one-third (n = 72) had injuries only in chest-abdomen-pelvis (CAP) region. Most cases (n = 373; 70%) had an ISS between 1 and 8, which is a mild score. Conclusions: This study showed a high rate of negative panCT scans, suggesting potential overuse of panCT. The study results highlight the need for more selective CT imaging approaches in emergency settings. Following evidence-based guidelines and decision-support tools could promote appropriate utilization of panCT scans, reducing unnecessary radiation exposure while ensuring that high-risk patients in emergency setting receive appropriate imaging.

The efficiency of partial body weight-supported treadmill training (PBWSTT) for treating various conditions in children and adolescents with cerebral palsy (CP) in diverse contexts of rehabilitation, households, or schools is unknown. The major objective of this systematic review and meta-analysis was to analyze the effectiveness of PBWSTT on various outcomes in different contexts among children and adolescents with CP. We incorporated full-text, randomized controlled trial studies that specifically assessed the effects of PBWSTT walking, motor function, stride, balance, and endurance in children and adolescents aged 3 to 18 years with CP. The literature search was carried out using Google Scholar, PubMed, Web of Science, CINAHL Plus, Scopus, PEDro, and ResearchGate databases. The methodological quality was evaluated using a Cochrane risk of bias instrument. A meta-analysis of pooled data from 10 studies with 255 participants demonstrated that PBWSTT for 4–12 weeks in rehabilitation (mean difference [MD] = 1.94, 95% confidence interval [CI] = 1.40—2.48, p < 0.0001), at home or in a school context (MD = 13.5, 95% CI = 13.9—16.0, p < 0.0001), was significantly effective for treating various conditions in children and adolescents suffering with CP. The period of 4–12 weeks of PBWSTT in rehabilitation and at-home/school settings is effective on various outcomes in children or adolescents with CP.

Objective: To explore the impact of different lung cancer treatment modalities on survival time and mortality rates in older patients. Methods: The Surveillance Epidemiology and End Results (SEER) database was used to identify lung cancer patients aged ≥50 years old in the United States. Descriptive statistics and trend charts from 2000 to 2016 were generated. Regression analysis was performed among lung cancer patients to explore the association between survival time and treatment utilization (chemotherapy, radiation, and surgery). A regression model was also applied to explore the association between treatment modalities and odds of dying. Results: A total of 826,217 patients were diagnosed with lung cancer between 2000-2016. The number of lung cancer cases increased by 7%, and the average annual frequency was 48,529 cases per year. Survival, mortality, and treatment utilization varied over the years based on demographic, clinical characteristics, and social status. Five-year survival rate was less than 10% among the study population, and 84% of included lung cancer patients died. Chemotherapy was more commonly used (62%), followed by radiation (35%) and surgical interventions (22%). Chemotherapy and surgery showed a survival advantage. The odds of dying were two times higher among patients treated with surgery than those who were not (OR: 2.62, 95%Cl: 2.58- 2.67). Conclusion: This study highlighted the importance of considering treatment modalities and individual patient characteristics, which may impact survival times and mortality rates among older lung cancer patients.

Objectives: The present study is aimed at determining the effect of cigarette smoking (CS) on serum uric acid (UA) levels quantitatively before and after smoking cessation among people with MS (pwMS). Additionally, a possible correlation between UA levels and both disability progression and disease severity was also investigated. A retrospective cross-sectional study was conducted using the Nottingham University Hospitals MS Clinics database. It involves 127 people with definite MS recorded when reporting the latest smoking status and the clinical diagnosis. All necessary demographics and clinical characteristics were collected. We found that smoker pwMS had significantly lower serum UA levels than non-smoker pwMS (p-value = 0.0475), and this reduction was recovered after smoking cessation (p-value = 0.0216). However, the levels of disability or disease severity were not correlated with the levels of serum UA in current smoker pwMS, measured by the expanded disability status scale (EDSS; r = −0.24; p-value = 0.38), multiple sclerosis impact scale 29 (MSIS-29; r = 0.01; p-value = 0.97) and MS severity score (MSSS; r = −0.16; p-value = 0.58), respectively. Our result suggests that the reduction in UA levels is more likely a consequence of oxidative stress triggered by many risk factors, including CS, and could be considered a potential indicator of smoking cessation. In addition, the absence of a correlation between UA levels and disease severity and disability suggests that UA is not an optimal biomarker for disease severity and disability prediction among current smoker, ex-smoker or non-smoker pwMS.

To date, there are no definite imaging predictors for long-term disability in multiple sclerosis (MS). Magnetic resonance imaging (MRI) is the key prognostic tool for MS, primarily at the early stage of the disease. Recent findings showed that white matter lesion (WML) counts and volumes could predict long-term disability for MS. However, the prognostic value of MRI in the early stage of the disease and its link to long-term physical disability have not been assessed systematically and quantitatively. A meta-analysis was conducted using studies from four databases to assess whether MS lesion counts and volumes at baseline MRI scans could predict long-term disability, assessed by the expanded disability status scale (EDSS). Fifteen studies were eligible for the qualitative analysis and three studies for meta-analysis. T2 brain lesion counts and volumes after the disease onset were associated with disability progression after 10 years. Four or more lesions at baseline showed a highly significant association with EDSS 3 and EDSS 6, with a pooled OR of 4.10 and 4.3, respectively. The risk increased when more than 10 lesions were present. This review and meta-analysis confirmed that lesion counts and volumes could be associated with disability and might offer additional valid guidance in treatment decision making. Future work is essential to determine whether these prognostic markers have high predictive potential.

Multiple sclerosis (MS) is characterised by widespread damage of the central nervous system that includes alterations in normal-appearing white matter (NAWM) and demyelinating white matter (WM) lesions. Neurite orientation dispersion and density imaging (NODDI) has been proposed to provide a precise characterisation of WM microstructures. NODDI maps can be calculated for the Neurite Density Index (NDI) and Orientation Dispersion Index (ODI), which estimate orientation dispersion and neurite density. Although NODDI has not been widely applied in MS, this technique is promising in investigating the complexity of MS pathology, as it is more specific than diffusion tensor imaging (DTI) in capturing microstructural alterations. We conducted a meta-analysis of studies using NODDI metrics to assess brain microstructural changes and neuroaxonal pathology in WM lesions and NAWM in patients with MS. Three reviewers conducted a literature search of four electronic databases. We performed a random-effect meta-analysis and the extent of between-study heterogeneity was assessed with the I2 statistic. Funnel plots and Egger’s tests were used to assess publication bias. We identified seven studies analysing 374 participants (202 MS and 172 controls). The NDI in WM lesions and NAWM were significantly reduced compared to healthy WM and the standardised mean difference of each was −3.08 (95%CI −4.22 to (−1.95), p ≤ 0.00001, I2 = 88%) and −0.70 (95%CI −0.99 to (−0.40), p ≤ 0.00001, I2 = 35%), respectively. There was no statistically significant difference of the ODI in MS WM lesions and NAWM compared to healthy controls. This systematic review and meta-analysis confirmed that the NDI is significantly reduced in MS lesions and NAWM than in WM from healthy participants, corresponding to reduced intracellular signal fraction, which may reflect underlying damage or loss of neurites.

Type 1 and type 2 diabetes mellitus have an impact on the microstructural environment and cognitive functions of the brain due to its microvascular/macrovascular complications. Conventional Magnetic Resonance Imaging (MRI) techniques can allow detection of brain volume reduction in people with diabetes. However, conventional MRI is insufficiently sensitive to quantify microstructural changes. Diffusion Tensor Imaging (DTI) has been used as a sensitive MRI-based technique for quantifying and assessing brain microstructural abnormalities in patients with diabetes. This systematic review aims to summarise the original research literature using DTI to quantify microstructural alterations in diabetes and the relation of such changes to cognitive status and metabolic profile. A total of thirty-eight published studies that demonstrate the impact of diabetes mellitus on brain microstructure using DTI are included, and these demonstrate that both type 1 diabetes mellitus and type 2 diabetes mellitus may affect cognitive abilities due to the alterations in brain microstructures.