Large Sample Research Articles

Is England’s Office for Students likely to falsely identify courses as below threshold on the B3 progression metric?

ABSTRACT Rising inflation and slow growth globally have led to governments focussing on value for money, and in the sphere of higher education policy that is often translated into graduate outcomes. In England, the Office for Students (OfS) has created the progression metric which for full-time, first degree and UK domiciled students requires courses to have 60% of graduates with positive outcomes 15 months after graduation. This paper utilises simulations to evaluate the likelihood that the OfS’s approach will fail to identify courses below the threshold (false positives) and incorrectly identify courses at or above the threshold (false negatives). The simulation adapts the levels of positive outcomes within the population (20-90%), sample size (40–1000), percentage sampled (30-90%) and crucially confidence intervals applied (90%, 95% and 99%) to identify courses below threshold. The three main findings are: the choice of 90% CI minimises the likelihood of false positives compared to 95% or 99% CIs; second, larger samples are essential to reduce likelihood of false positives; and third, preferring the 95% confidence interval instead of 99% for taking regulatory action will result in more courses incorrectly identified as below threshold. Governments that choose a statistical approach to regulate educational standards, like the application of confidence intervals to identify provision below quality standards, should utilise simulations to check the likelihood of false positives and false negatives since failure to do so could lead to both: (a) courses below standard not being identified and (b) regulatory action taken incorrectly against provision at or above standards.

Effectiveness of Participatory Training for Prevention of Slips, Trips, and Falls: A Cluster Randomized Controlled Trial of Corn Farmers in Thailand.

This study evaluated the effectiveness of a participatory training program for mitigating the risk of slips, trips, and falls (STFs) in agriculture. We conducted a cluster randomized controlled trial of corn farmers over six months in Thailand. The participatory training intervention comprised lectures, group discussions, and presentation sessions centered around a specifically developed action checklist for occupational fall prevention. Sixty-two individuals were included in the intervention group, with 169 included in the control group. The results revealed a reduction in the incidence of STFs in the intervention group from 42% to 23%; however, this difference was not statistically significant. The study highlights the potential of participatory training for enhancing occupational safety for farmers. However, the absence of statistical significance necessitates cautious interpretation of the results. Future research should examine larger sample sizes, involve employers in the training process, and implement repetitive training interventions.

Modulatory effect of the fruit rind extract of Garcinia indica Choisy against gamma radiation induced damage in human peripheral blood lymphocytes: a preliminary study

Purpose Nowadays people are exposed to radiation due to various reasons, including natural, diagnostic, occupational or accidental exposure. High level of exposure to ionizing radiation can be fatal to human body. Synthetic drugs used to prevent radiation-induced damage are toxic in nature. Recently, Herbal drugs are being screened as an alternative due to their mechanism of action. Garcinia indica (G. indica) is one of the traditional medicinal plant which contains phytochemicals having several medicinal properties. Materials and methods In this study, G. indica extract was observed for its modulatory effect against 3 Gray (Gy) gamma radiation-induced damages in human peripheral blood lymphocytes. Various concentrations of G. indica extract ranging from 1 to 25 µg/mL was added to the blood post irradiation at 0 hr. Chromosomal aberration (CA) and Cytochalasin B blocked Micronuclei Cytome (CBMN) Assay were performed as per standard procedure. Results Radiomodulatory effect of Garcinia indica fruit rind extract (GIFRE) on CA and MN formation was observed in this study. Treatment of GIFRE did not affect the mitotic index. Positive inhibition percentages for dicentrics, total chromosomal aberrations and micronuclei were observed except for one instance. Conclusion Owing to the various properties of Garcinia extracts, it makes it a potential candidate to be tested for its radiomodulatory effect. Based on the results observed in this preliminary study, it could act as a radiomodulatory agent. Radiomodulatory effect of GIFRE could possibly serve it as a potential herbal medicinal alternative to current drugs. However, results of this study need to be validated on larger sample size.

Using the children’s accelerated trauma technique with adults with intellectual disabilities

Purpose This paper aims to explore using the children’s accelerated trauma technique (CATT) in an adult intellectual disability population, with the aim of reducing symptoms of post-traumatic stress disorder (PTSD). Design/methodology/approach A service evaluation was completed to investigate differences between pre- and post-CATT trauma scores. Findings Scores on a measure of PTSD decreased significantly following CATT. Practical implications The findings support continued use of CATT in adults with intellectual disabilities, and they highlight the need to evaluate effectiveness in a larger sample. Originality/value This paper evaluates the novel application of a trauma treatment – developed for use with children – in an adult intellectual disability population and adds to the existing evidence base.

Downregulated expression of exosomal long non-coding RNA UCA1 in plasma of patients with non-small cell lung cance

Long non-coding RNAs (lncRNAs), mainly found in the nucleus of cells, are involved in different gene expression and regulation processes. Growing evidence has shown that abnormalities in the expression levels of lncRNAs play an important role in tumour metastasis, invasion, and proliferation, especially in non-small cell lung cancer (NSCLC). LncRNAs were also found to be upregulated or downregulated in exosomes secreted by cancer cells, thus they have the potential to be used as a non-invasive cancer biomarker. In this study, the expression of exosomal lncRNA UCA1 was determined on 29 plasma samples of patients with NSCLC and 29 controls who did not have NSCLC or related lung diseases by quantitative PCR using SYBR Green. Then, statistical analyses were used to evaluate the association between the expression of lncRNA UCA1 and some pathological features of NSCLC. The results showed that lncRNA UCA1 was downregulated in the exosomes of NSCLC patients compared with the control group (p=0.050), especially in the early stage (stage I + II). However, there was no association between the expression of lncRNA UCA1 and some pathological features of NSCLC, such as age, sex, smoking, alcohol consumption, tumour size, disease stage, lymph nodes, or tumour metastasis. This study provided the initial data on the expression of exosomal lncRNA UCA1 in the plasma of Vietnamese patients with NSCLC and further studies on the larger samples are needed to be continued.

Prognosis Prediction in Head and Neck Squamous Cell Carcinoma by Radiomics and Clinical Information

(1) Background: head and neck squamous cell carcinoma (HNSCC) is a common cancer whose prognosis is affected by its heterogeneous nature. We aim to predict 5-year overall survival in HNSCC radiotherapy (RT) patients by integrating radiomic and clinical information in machine-learning models; (2) Methods: HNSCC radiotherapy planning computed tomography (CT) images with RT structures were obtained from The Cancer Imaging Archive. Radiomic features and clinical data were independently analyzed by five machine-learning algorithms. The results were enhanced through a voted ensembled approach. Subsequently, a probability-weighted enhanced model (PWEM) was generated by incorporating both models; (3) Results: a total of 299 cases were included in the analysis. By receiver operating characteristic (ROC) curve analysis, PWEM achieved an area under the curve (AUC) of 0.86, which outperformed both radiomic and clinical factor models. Mean decrease accuracy, mean decrease Gini, and a chi-square test identified T stage, age, and disease site as the most important clinical factors in prognosis prediction; (4) Conclusions: our radiomic–clinical combined model revealed superior performance when compared to radiomic and clinical factor models alone. Further prospective research with a larger sample size is warranted to implement the model for clinical use.

The efficacy of transcranial random noise stimulation in treating tinnitus: a systematic review.

This review aims to examine the effects of transcranial random noise stimulation (tRNS) on tinnitus and to determine the optimal treatment parameters, if possible. A comprehensive search, including MEDLINE, PubMed, EMBASE, CINAHL, SCOPUS, and PEDro, was conducted to determine experiments studying the effects of tRNS on tinnitus from inception to March 1, 2024. The Physiotherapy Evidence Database (PEDro) scale was used to evaluate the quality of the included studies. Seven studies met the eligibility criteria. A total of 616 patients with non-pulsatile tinnitus (mean age 50.93 years; 66% males) were included in this review. The included studies ranged from 3 to 8 out of 10 (median = 7) on the PEDro scale. The results showed that tRNS is an effective intervention in reducing tinnitus symptoms. The evidence for the effects of tRNS on people with chronic non-pulsatile tinnitus is promising. Administering tRNS with an intensity of 1-2mA, high-frequency (101-650Hz), using a 35cm² electrode size over the auditory cortex and DLPFC, for 20min with eight sessions may demonstrate the desired tRNS effects. The tRNS stimulation should be contralateral for unilateral tinnitus and bilaterally for bilateral tinnitus. Combining tRNS with other concurrent interventions may show superior effects in reducing tinnitus compared to tRNS alone. Further high-quality studies with larger sample sizes are strongly needed.

Assessing disparities through missing race and ethnicity data: results from a juvenile arthritis registry.

Ensuring high-quality race and ethnicity data within the electronic health record (EHR) and across linked systems, such as patient registries, is necessary to achieving the goal of inclusion of racial and ethnic minorities in scientific research and detecting disparities associated with race and ethnicity. The project goal was to improve race and ethnicity data completion within the Pediatric Rheumatology Care Outcomes Improvement Network and assess impact of improved data completion on conclusions drawn from the registry. This is a mixed-methods quality improvement study that consisted of five parts, as follows: (1) Identifying baseline missing race and ethnicity data, (2) Surveying current collection and entry, (3) Completing data through audit and feedback cycles, (4) Assessing the impact on outcome measures, and (5) Conducting participant interviews and thematic analysis. Across six participating centers, 29% of the patients were missing data on race and 31% were missing data on ethnicity. Of patients missing data, most patients were missing both race and ethnicity. Rates of missingness varied by data entry method (electronic vs. manual). Recovered data had a higher percentage of patients with Other race or Hispanic/Latino ethnicity compared with patients with non-missing race and ethnicity data at baseline. Black patients had a significantly higher odds ratio of having a clinical juvenile arthritis disease activity score (cJADAS10) of ≥5 at first follow-up compared with White patients. There was no significant change in odds ratio of cJADAS10 ≥5 for race and ethnicity after data completion. Patients missing race and ethnicity were more likely to be missing cJADAS values, which may affect the ability to detect changes in odds ratio of cJADAS ≥5 after completion. About one-third of the patients in a pediatric rheumatology registry were missing race and ethnicity data. After three audit and feedback cycles, centers decreased missing data by 94%, primarily via data recovery from the EHR. In this sample, completion of missing data did not change the findings related to differential outcomes by race. Recovered data were not uniformly distributed compared with those with non-missing race and ethnicity data at baseline, suggesting that differences in outcomes after completing race and ethnicity data may be seen with larger sample sizes.

Comparative efficacy and safety of traditional Chinese medicine injections in patients with transient ischemic attack: A systematic review and network meta-analysis.

Traditional Chinese medicine (TCM) injections are extensively utilized for the treatment of transient ischemic attack (TIA). However, it remains unclear which specific TCM injection exhibits superior efficacy. In this study, we conducted a network meta-analysis to compare the clinical efficacy and safety of various TCM injections in the treatment of TIA, with the aim of identifying the optimal treatment regimen. We searched seven databases to collect information on nine TCM injections for the treatment of transient randomized controlled trials (RCTs) for the treatment of transient ischemic attacks were collected from the establishment to August 2023. The methodological quality and risk of bias were assessed using the RoB 2.0 evaluation tool, and reticulated Meta-analysis was performed using R software and Stata software. We ultimately included 58 RCTs involving 5502 patients and comprising 9 TCM injections. In terms of improving the total effective rate, Shuxuetong injection (P-score = 0.69) was the most effective. In addition, Shuxuetong injection was most effective in lowering total cholesterol (P-score = 1.00) and triglyceride (P-score = 1.00) levels. Notably, Shuxuetong injection remained the most prominent in reducing fibrinogen (P-score = 0.91). However, among other blood hemorheology indicators, Dengzhanhuasu injection was the best regimen in reducing plasma viscosity (P-score = 1.00), whole blood viscosity (high shear rate) (P-score = 0.87), and whole blood viscosity (low shear rate) (P-score = 0.90). It was found that Yinxingyetiquwu injection (P-score = 0.72) was the most effective in reducing the incidence of cerebral infarction. In terms of safety, 22 studies reported adverse effects and descriptive analyses showed that the number of adverse effects of combination therapy was comparable to that of conventional therapy and that the safety profile was good. TCM injections in combination with CT may be a safe and effective intervention for patients with TIA, of which Shuxuetong injection, Dengzhanhuasu injection, and Yinxingyetiquwu injection may be more noteworthy. The quality of the literature included in the study was low, so further validation is needed with larger sample sizes, higher quality, and more rigorously designed RCTs. [PROSPERO], identifier [CRD42023443652].

Acute kidney injury with intravenous colistin sulfate compared with polymyxin B in critically ill patients: A real-world, retrospective cohort study.

Polymyxins have re-emerged as a last-resort therapeutic option for infections caused by carbapenem-resistant gram-negative bacteria. Nephrotoxicity induced by polymyxins is a significant limitation of its use in the clinic. Polymyxin B and colistin sulfate are two widely used active formulations of polymyxins. However, there is a lack of studies conducting a comparative assessment of nephrotoxicity between the two formulations. This study aimed to compare the nephrotoxicity of polymyxin B and colistin sulfate in critically ill patients. We conducted a retrospective cohort study among critically ill patients who received intravenous polymyxin B or colistin sulfate for over 48 h from January 2017 to January 2024. The primary outcome was the incidence of acute kidney injury (AKI) associated with polymyxins, and the secondary outcome was 30-day all-cause mortality. Additionally, the risk factors of polymyxins-induced AKI and 30-day all-cause mortality were identified by Cox proportional hazard regression analysis. A total of 473 patients were included in this study. The overall incidence of AKI was significantly higher in patients who received polymyxin B compared to those who received colistin sulfate in the unmatched cohort (20.8% vs. 9.0%, p = 0.002) and in the propensity score matching cohort (21.1% vs. 7.0%, p = 0.004), respectively. However, there was no significant difference in 30-day all-cause mortality between the two groups. Polymyxin type, septic shock, and concomitant use of vasopressors were identified as independent risk factors for polymyxin-induced AKI. The prevalence of AKI was higher among patients who received polymyxin B compared to those treated with colistin sulfate. However, there was no significant difference in 30-day all-cause mortality between the two groups. Further prospective, multicenter studies with larger sample sizes are needed to validate these findings.

Causes of death in individuals with lifetime major depression: a comprehensive machine learning analysis from a community-based autopsy center

BackgroundDepression can be associated with increased mortality and morbidity, but no studies have investigated the specific causes of death based on autopsy reports. Autopsy studies can yield valuable and detailed information on pathological ailments or underreported conditions. This study aimed to compare autopsy-confirmed causes of death (CoD) between individuals diagnosed with major depressive disorder (MDD) and matched controls. We also analyzed subgroups within our MDD sample, including late-life depression and recurrent depression. We further investigated whether machine learning (ML) algorithms could distinguish MDD and each subgroup from controls based on their CoD.MethodsWe conducted a comprehensive analysis of CoD in individuals who died from nontraumatic causes. The diagnosis of lifetime MDD was ascertained based on the DSM-5 criteria using information from a structured interview with a knowledgeable informant. Eleven established ML algorithms were used to differentiate MDD individuals from controls by simultaneously analyzing different disease category groups to account for multiple tests. The McNemar test was further used to compare paired nominal data.ResultsThe initial dataset included records of 1,102 individuals, among whom 232 (21.1%) had a lifetime diagnosis of MDD. Each MDD individual was strictly paired with a control non-psychiatric counterpart. In the MDD group, the most common CoD were circulatory (67.2%), respiratory (13.4%), digestive (6.0%), and cancer (5.6%). Despite employing a range of ML models, we could not find distinctive CoD patterns that could reliably distinguish individuals with MDD from individuals in the control group (average accuracy: 50.6%; accuracy range: 39-59%). These findings were consistent even when considering factors within the MDD group, such as late-life or recurrent MDD. When comparing groups with paired nominal tests, no differences were found for circulatory (p=0.450), respiratory (p=0.790), digestive (p=1.000), or cancer (p=0.855) CoD.ConclusionsOur analysis revealed that autopsy-confirmed CoD exhibited remarkable similarity between individuals with depression and their matched controls, underscoring the existing heterogeneity in the literature. Future research should prioritize more severe manifestations of depression and larger sample sizes, particularly in the context of CoD related to cancer.

Feasibility of virtual reality and machine learning to assess personality traits in an organizational environment.

Personality plays a crucial role in shaping an individual's interactions with the world. The Big Five personality traits are widely used frameworks that help describe people's psychological behaviours. These traits predict how individuals behave within an organizational setting. In this article, we introduce a virtual reality (VR) strategy for relatively scoring an individual's personality to evaluate the feasibility of predicting personality traits from implicit measures captured from users interacting in VR simulations of different organizational situations. Specifically, eye-tracking and decision-making patterns were used to classify individuals according to their level in each of the Big Five dimensions using statistical machine learning (ML) methods. The virtual environment was designed using an evidence-centered design approach. The dimensions were assessed using NEO-FFI inventory. A random forest ML model provided 83% accuracy in predicting agreeableness. A k-nearest neighbour ML model provided 75%, 75%, and 77% accuracy in predicting openness, neuroticism, and conscientiousness, respectively. A support vector machine model provided 85% accuracy for predicting extraversion. These analyses indicated that the dimensions could be differentiated by eye-gaze patterns and behaviours during immersive VR. Eye-tracking measures contributed more significantly to this differentiation than the behavioural metrics. Currently, we have obtained promising results with our group of participants, but to ensure the robustness and generalizability of our findings, it is imperative to replicate the study with a considerably larger sample. This study demonstrates the potential of VR and ML to recognize personality traits.

Using natural language processing to facilitate the harmonisation of mental health questionnaires: a validation study using real-world data

BackgroundPooling data from different sources will advance mental health research by providing larger sample sizes and allowing cross-study comparisons; however, the heterogeneity in how variables are measured across studies poses a challenge to this process.MethodsThis study explored the potential of using natural language processing (NLP) to harmonise different mental health questionnaires by matching individual questions based on their semantic content. Using the Sentence-BERT model, we calculated the semantic similarity (cosine index) between 741 pairs of questions from five questionnaires. Drawing on data from a representative UK sample of adults (N = 2,058), we calculated a Spearman rank correlation for each of the same pairs of items, and then estimated the correlation between the cosine values and Spearman coefficients. We also used network analysis to explore the model’s ability to uncover structures within the data and metadata.ResultsWe found a moderate overall correlation (r = .48, p < .001) between the two indices. In a holdout sample, the cosine scores predicted the real-world correlations with a small degree of error (MAE = 0.05, MedAE = 0.04, RMSE = 0.064) suggesting the utility of NLP in identifying similar items for cross-study data pooling. Our NLP model could detect more complex patterns in our data, however it required manual rules to decide which edges to include in the network.ConclusionsThis research shows that it is possible to quantify the semantic similarity between pairs of questionnaire items from their meta-data, and these similarity indices correlate with how participants would answer the same two items. This highlights the potential of NLP to facilitate cross-study data pooling in mental health research. Nevertheless, researchers are cautioned to verify the psychometric equivalence of matched items.

Microbiota composition effect on immunotherapy outcomes in colorectal cancer patients: A systematic review.

Immune checkpoint inhibitors (ICIs) have emerged as an effective treatment for colorectal cancer (CRC). Studies indicate that the composition of gut microbiota could potentially serve as a biomarker for predicting the clinical effectiveness of immune checkpoint inhibitors. Following PRISMA guidelines, the review was conducted after registering the protocol with PROSPERO. A comprehensive literature search was carried out across five databases: PubMed, Scopus, Web of Science, Embase, and Cochrane Library. Assessment tools from the National Institutes of Health (NIH) were used to gauge the quality of the studies. A total of 5,132 papers were identified, and three studies and one conference abstract published between 2017-2022 met the inclusion criteria and were summarized in a descriptive synthesis table. These four studies were in accord with the following findings, four main phyla, Firmicutes, Bacteroidata, Actinobacteria, and Verrucomicrobiota were associated with CRC patients' clinical response toward ICIs treatment. Ruminococcaceae was predominantly related to CRC patients responding to therapy, while the Micrococcaceae family was more common among the non-responders. Bacterial taxa such as Faecalibacterium and Prevotellaceae were associated with better responses to ICIs and could be predictive biomarkers. The signature of fecal microbiota with Akkermansia muciniphila and Eubacterium rectale enrichment, and Rothia mucilaginosa depletion could independently predict better response to ICIs in patients with CRC. The findings have brought attention to the notable differences in terms of richness and composition of microbiota between patients who responded positively to the treatment and those who did not. Bacterial species and families, such as Faecalibacterium, Bifidobacterium, Lachnospiraceae, Akkermansia sp., Ruminococcaceae, and Prevotellaceae, have consistently surfaced as potential indicators of immunotherapeutic responses. Furthermore, this review also emphasizes the need for additional comprehensive, multi-center studies with larger sample sizes to validate reported microbiota and expand our understanding of the role of gut microbiota in CRC ICIs therapy. PROSPERO ID: CRD42021277691.

Machine learning for automating subjective clinical assessment of gait impairment in people with acquired brain injury – a comparison of an image extraction and classification system to expert scoring

BackgroundWalking impairment is a common disability post acquired brain injury (ABI), with visually evident arm movement abnormality identified as negatively impacting a multitude of psychological factors. The International Classification of Functioning, Disability and Health (ICF) qualifiers scale has been used to subjectively assess arm movement abnormality, showing strong intra-rater and test-retest reliability, however, only moderate inter-rater reliability. This impacts clinical utility, limiting its use as a measurement tool. To both automate the analysis and overcome these errors, the primary aim of this study was to evaluate the ability of a novel two-level machine learning model to assess arm movement abnormality during walking in people with ABI.MethodsFrontal plane gait videos were used to train four networks with 50%, 75%, 90%, and 100% of participants (ABI: n = 42, healthy controls: n = 34) to automatically identify anatomical landmarks using DeepLabCut™ and calculate two-dimensional kinematic joint angles. Assessment scores from three experienced neurorehabilitation clinicians were used with these joint angles to train random forest networks with nested cross-validation to predict assessor scores for all videos. Agreement between unseen participant (i.e. test group participants that were not used to train the model) predictions and each individual assessor’s scores were compared using quadratic weighted kappa. One sample t-tests (to determine over/underprediction against clinician ratings) and one-way ANOVA (to determine differences between networks) were applied to the four networks.ResultsThe machine learning predictions have similar agreement to experienced human assessors, with no statistically significant (p < 0.05) difference for any match contingency. There was no statistically significant difference between the predictions from the four networks (F = 0.119; p = 0.949). The four networks did however under-predict scores with small effect sizes (p range = 0.007 to 0.040; Cohen’s d range = 0.156 to 0.217).ConclusionsThis study demonstrated that machine learning can perform similarly to experienced clinicians when subjectively assessing arm movement abnormality in people with ABI. The relatively small sample size may have resulted in under-prediction of some scores, albeit with small effect sizes. Studies with larger sample sizes that objectively and automatically assess dynamic movement in both local and telerehabilitation assessments, for example using smartphones and edge-based machine learning, to reduce measurement error and healthcare access inequality are needed.

A comparative study on effects of defect closure versus non-closure in laparoscopic totally extraperitoneal repair of direct inguinal hernia

Introduction: Total extraperitoneal (TEP) and transabdominal preperitoneal (TAPP) repair are the principal techniques in laparoscopic hernia repair. Seroma formation and pain are frequent complications of moderate-large size laparoscopic direct inguinal hernia mesh repair. This study was conducted to evaluate the feasibility of defect closure in moderate-large direct inguinal hernias and its effect on various outcomes. Method: This is a prospective cohort study from September 2020 to August 2021, where a total of 88 patients with uncomplicated direct inguinal hernia (M3 or more) were enrolled in the study and divided into two equal groups of TEP defect closure and non-closure, and various outcome measures were noted. Results: The majority of patients were male (94.31%), with a mean age range of 18–85 years, and had right-sided inguinal hernia (46.5%). Seroma formation at 10th POD in the defect closure and non closure were 24% and 33% (p-value: 0.225), which reduced to 11% and 18%, respectively, at 1 month (p-value: 1.000). All seromas resolved within 6 months. Pain in VAS at 10th POD in the defect closure and non-closure were 1.55±0.571 and 1.38±0.527, respectively (p-value: 0.121), which gradually decreased to 1.20±0.524 and 1.16±0.420 at a 6-month interval (p-value: 0.689). The mean operative time in the bilateral and unilateral defect closure groups was 72.3±4.1 and 56.5±4.3 min. respectively, whereas that in the bilateral and unilateral defect non-closure groups was 62.3±3.7 and 45.7±3.6 min. respectively. Conclusion: The defect closure was found to have higher pain and less seroma formation at various intervals of time following TEP for moderate-large direct inguinal hernia. Although these findings were statistically insignificant, they may be clinically significant, and further studies with a larger sample size are suggested.

Prevalence of metabolic syndrome and its association with CT-based central adiposity measures: a cross-sectional study at a tertiary care hospital in Pakistan

ObjectivesTo assess the prevalence of metabolic syndrome (MS) and association of central obesity measures such as body mass index (BMI), visceral fat adiposity (VFA) and superficial fat adiposity (SFA) with...

Major stoma complications in pediatric patients in a tertiary hospital in a low-middle-income country: a retrospective cohort study.

Intestinal stomas are one of the most common parts of pediatric surgical care,and complications arising from it have significant impact on overall patient outcomes. However, data on major complications in low-middle-income countries remain limited. This pilot retrospective cohort study aimed to investigate the prevalence, types, and management of major stoma complications in pediatric patients at a tertiary government hospital in the Philippines. Medical records of pediatric patients with major stoma complications classified as Clavien-Dindo III-V from June 2018 to June 2023 were reviewed. Patient-related factors (age, sex, diagnosis) and surgery-related factors (stoma type and location, surgeon expertise) were analyzed. Descriptive statistics characterized demographic profiles, while Chi-square and t tests analyzed categorical and continuous variables, respectively. Multivariable logistic regression evaluated independent associations with major stoma complications. Out of 1041 pediatric patients with stomas, 102 cases had major complications, representing a prevalence rate of 9.8%. Mortality directly attributed to stoma complications accounted for 1.3% of the total cases, or 14 deaths in 5years. Neonates comprised a significant portion, primarily diagnosed with congenital conditions like anorectal malformation and Hirschsprung's disease. Ileostomies exhibited a higher incidence of major complications compared to other stoma types. Stomal prolapse and adhesive bowel obstruction are the most common reported stoma complications requiring surgical intervention while stoma revision is the most frequent corrective procedure. The median time from stoma creation to presentation of major complication was 14months, with nearly half of the complications occurring within the first year. Only the presence of ileostomy had significant association with the development of major complications among the risk factors analyzed. This study provides useful insights into stoma complications in pediatric patients in a low-middle income country. Despite the lack of significant associations between the patient-related and surgeon-related factors, and major stoma complications, further investigation into other contributing factors is warranted. Improvements in data collection methods and prospective studies with larger sample sizes are recommended to enhance understanding and optimize care of major stoma complications. Addressing the challenges identified in this study could lead to a comprehensive and tailored approach to pediatric stoma care and their complications.

Comparative evaluation of cognitive behavioural therapy versus standard treatment in temporomandibular disorders: Asystematic review.

Temporomandibular disorders (TMDs) are musculoskeletal and neuromuscular conditions affecting the temporomandibular joint and associated structures. Cognitive-behavioural therapy (CBT) has emerged as a potential intervention for TMDs, but its comparative effectiveness against standard treatments remains unclear. This systematic review aimed to evaluate and compare the efficacy of CBT versus standard treatment interventions in managing TMDs. A comprehensive search was conducted across multiple databases using MeSH keywords and Boolean operators. Inclusion criteria encompassed clinical trials comparing CBT/CBT in combination with standard treatment interventions or a control group in individuals with TMDs. The primary outcome measured was pain. Secondary outcomes such as disability, depression and jaw function were also looked into. Two reviewers independently assessed for the eligibility of the articles and conducted data extraction. Quality assessments were performed using RoB 2.0 for randomised clinical trials. The initial search identified 623 articles, of which a total of eight clinical studies met the inclusion criteria and were included in the systematic review. Seven out of eight studies demonstrated improvements in outcomes related to TMD. Pain was significantly decreased in studies that showed a positive outcome. Jaw function, quality of life and psychological well-being were superior among individuals receiving CBT alone or in combination with conventional modalities, as well as hypnotic therapy coupled with CBT-based interventions. The quality of studies assessed showed all articles to be of good quality as per RoB-2 evaluation. This systematic review highlights the potential benefits of CBT in managing TMDs, suggesting its effectiveness in improving pain outcomes and enhancing overall well-being. The findings indicate that CBT may be a valuable adjunct or alternative to standard treatment interventions for individuals with TMDs. However, further research with larger sample sizes and standardised outcome measures is warranted to establish definitive conclusions regarding the comparative efficacy of CBT versus standard treatments in TMD management.

Analysis of the TP53 exon 4 gene polymorphism in patients with oral squamous cell carcinoma

Squamous cell carcinoma (SCC) of the oral cavity is the most frequent epithelial neoplasm among head and neck cancers, with multifactorial etiology. Risk factors include smoking, alcohol consumption, and genetic predisposition. The p53 gene, known as the guardian of the genome, has a polymorphism at codon 72 of exon 4, resulting in the arginine/proline genotype. This case-control study included 280 healthy individuals and eight patients with oral SCC treated at a reference hospital in Brasília. Using PCR-RFLP, we investigated the association between the p53 Arg72Pro polymorphism (rs1042522) and oral SCC. A statistically significant predominance of the Arg/Arg genotype was observed in the case group (p=0.004). The results suggest that the Arg/Arg genotype may be associated with an increased risk of developing oral SCC. It is concluded that, although promising, studies with larger samples are needed to validate this polymorphism as a predictive marker.