.
Acute Achilles tendon ruptures (AATRs), an extremely prevalent injury amongst adults who remain active, have been treated with surgical intervention for decades. This choice was made due to several decades-old studies demonstrating reduced re-rupture rates as opposed to nonsurgical interventions utilizing casts; however, numerous surgeons and researchers acknowledged potential complications such as wound problems and nerve damage. Functional braces and early weight-bearing now challenge this 'surgical by default' model. An evidence-based, focused review of randomized clinical trials, conventional and network meta-analysis, and large cohorts was conducted for the comparison of operative and nonoperative treatment for AATRs or the evaluation of various rehabilitation approaches. Operative management provides a lower rate of re-rupture in comparison to traditional cast-based nonoperative treatment; however, operative management also results in increased wound complications and sural nerve injuries. Nonoperative management employing functional bracing and early weight-bearing provides re-rupture rates approaching those of operative management, and the long-term functional outcome data are generally comparable. Differences in structural changes continue to exist between the two management groups, with longer tendon length and atrophy of the soleus muscle seen after conservative treatment, although for the majority of patients, the resultant strength and endurance deficits will be minimal. Both treatment options may provide optimal results if implemented through structured rehabilitation pathways. Treatment should be individualized based on the patient's specific factors, injury characteristics, and available resources. The use of current comparative effectiveness research to assist in making decisions regarding treatment with the patient is recommended.
Introduction Sleep deprivation is an escalating public health concern among young adults, as it impairs cognitive function and increases the risk of cardiovascular disease (CVD). Existing studies have linked chronic sleep deficiencies to mental confusion, reduced cognitive performance, and early signs of cognitive decline. Research also indicates that inadequate sleep contributes to metabolic dysregulation and autonomic system instability, both of which elevate cardiovascular risk. However, the overall effects of sleep deprivation on cognitive function and cardiovascular markers in young adults require further exploration. This study aims to examine the relationship between sleep deprivation, brain fog, early cognitive decline, and cardiovascular risk factors in this population. Methods This cross-sectional study involved 300 participants aged 18-30 from Pakistan and various other countries. Participants were selected using non-probability purposive sampling. Data were collected using four validated instruments: the Pittsburgh Sleep Quality Index, the Cognitive Failures Questionnaire, the Mini-Mental State Examination, and the Perceived Stress Scale. Data analysis was conducted using IBM SPSS Statistics for Windows, Version 26.0 (Released 2019; IBM Corp., Armonk, NY, USA), applying chi-square tests, independent sample t-tests, ANOVA, Pearson correlation, and logistic regression to assess associations between sleep deprivation, cognitive performance, and cardiovascular outcomes. Results Participants with shorter sleep durations had significantly higher scores in cognitive failures (p < 0.01) and perceived stress (p < 0.01). Poor sleep quality was associated with reduced cognitive performance (r = -0.114, p < 0.05), and it also increased the likelihood of developing cardiovascular risk factors. Participants with a family history of CVD exhibited significantly higher cognitive failure scores (t = 5.540, p < 0.001). Furthermore, a decline in sleep quality was associated with increased cardiovascular risk (B = 0.035, p = 0.019), although sleep disorders were not significantly influenced by sleep quality deterioration (B = 0.012, p = 0.400). Employment status and smoking habits were also found to impact both sleep quality and cognitive function (p < 0.01). Conclusions This study highlights the adverse impact of insufficient sleep on cognitive function and cardiovascular health in young adults aged 18-30. Poor sleep quality is associated with increased cognitive errors, heightened stress levels, and a greater risk of cardiovascular issues. These findings emphasize the importance of targeted health interventions aimed at improving sleep hygiene and lifestyle behaviors to reduce the risk of early cognitive decline and cardiovascular conditions. Future research should employ longitudinal designs and objective sleep tracking to strengthen causal inferences.
Background: Arsenic (As) is a leading environmental toxicant contributing to the global burden of hypertension and cardiovascular disease. Multiple studies have reported greater burden of hypertension among people of African ancestry including in the Caribbean although the mechanisms remain largely unexplored. Hypothesis: We investigated the hypothesis that environmental factors, such as arsenic exposure, are associated with greater risk of hypertension&high blood pressures in 965 middle aged and older (age range 40-87) Afro-Caribbean men and women from the Tobago Health Study. Methods: Arsenic exposure was measured as the sum of inorganic and methylated As (ΣAs = inorganic As + dimethylarsinic acid + monomethylarsonic acid) in spot urine samples using Liquid Chromatography&Inductively Coupled Plasma Mass Spectrometry. We used multiple linear regression models to examine cross-sectional associations of urine ΣAs with systolic blood pressure, diastolic blood pressure, pulse pressure&mean arterial pressure. Logistic regression models were used to examine odds of hypertension (defined as systolic BP ≥140, diastolic BP ≥ 90, or use of antihypertensive medication). The models were adjusted for age, sex, waist circumference, urinary creatinine, physical activity, smoking&antihypertensive treatment. Additionally, we conducted sex-stratified analyses separately in men and women. We also compared these associations within ΣAs exposure quartiles. We tested for effect measure modification by sex and p-values for interaction were calculated with likelihood ratio test to determine how sex interacted with these associations. Results: Each standard deviation increase in ΣAs (16.9 ng/ml) was associated with 40% higher odds of hypertension in the total cohort (OR: 1.40, 95% CI: 1.11–1.81, p: 0.008) and 90% higher odds in women (OR: 1.90, 95% CI: 1.13–3.47, p: 0.027). People with the highest ΣAs exposure quartile had 1.9-fold (95% CI:1.16, 3.12, p: 0.011 in total cohort)&4.3-fold (95% CI: 1.96, 9.82, p: <0.001 in women) higher odds of hypertension compared to those with the lowest quartile. Evidence of effect modification by sex was observed, between ΣAs and mean arterial pressure (p-interaction =0.015) where men had higher mean arterial pressure. Conclusion: These findings suggest that exposure to inorganic arsenic is cross-sectionally associated to a sex specific pattern of greater burden of hypertension and high blood pressure among Afro-Caribbean adults in Tobago.
Orthopaedic fracture diagnosis and surgical planning are being revolutionised by artificial intelligence (AI) and machine learning (ML). These technologies enable the automated detection and classification of fractures and provide surgeons with AI-assisted pre-operative decision-making support at multiple body sites. The objective of this review is to synthesise current evidence (from 2016 to 2026) related to the application of AI/ML technologies in orthopaedic fracture diagnosis and surgical planning, to summarise the primary clinical findings from these studies, and to describe the challenges associated with translating these technological advancements into clinical practice. A MEDLINE/PubMed literature search was conducted utilising a combination of Medical Subject Headings (MeSH) terms for AI, deep learning, fracture detection, and orthopaedic surgical planning. A total of 24 peer-reviewed publications that met the inclusion criteria and were published between 2016 and 2026 were identified and then synthesised through a narrative approach. Convolutional neural network (CNN)-based and Vision Transformer (ViT)-based deep learning models demonstrated area under receiver operating curves (AUROC) values ranging from 0.85 to 0.98 for detecting fractures in the hips, femurs, spines, scaphoids, tibias, pelvises, and ribs on radiographs and computed tomography (CT). The AI-assisted pre-operative planning tools have also been validated for use with pelvic and proximal humeral fractures. Additionally, ML has predicted the outcomes of surgery with AUROC values ranging from 0.78 to 0.87. There are several key limitations to the adoption of these technologies in clinical practice, including the majority of studies having been designed as retrospective analyses, the relative lack of diversity within their datasets, and the evolution of regulatory frameworks governing the application of AI/ML in medical imaging. Overall, AI technology has been shown to be highly accurate in both diagnosing fractures and assisting surgeons with planning for orthopaedic surgery. Before widespread clinical use can begin, prospective multi-centre validation and regulatory clarity will need to be achieved.
Abstract Background Acromegaly often develops insidiously and may first be suspected only when a pituitary lesion is detected incidentally on neuroimaging. Clinical features can be subtle despite established biochemical disease, particularly in patients with common comorbidities such as type 2 diabetes and hypertension. This case describes the journey from an incidental pituitary macroadenoma to a confirmed diagnosis of acromegaly, highlighting the importance of systematic endocrine evaluation and multidisciplinary management. Case Report A middle-aged man with type 2 diabetes (on metformin) and recently diagnosed hypertension (on lisinopril) underwent CT head imaging, which incidentally revealed a pituitary lesion. Subsequent pituitary MRI confirmed a 15-17 mm macroadenoma with suprasellar extension but no optic chiasm compression. Over the preceding year he had developed increasing tiredness and intermittent light-headedness, and more recently a persistent central pressure-type headache. He denied visual disturbance but reported an increase in shoe size from 10.5 to 11.5 and a perception that his hands were enlarging. Examination showed mildly coarse facial features, a widened nasal bridge, subtle prognathism and broadened digits, without obvious frontal bossing or macroglossia. Initial pituitary profile demonstrated elevated age-adjusted insulin-like growth factor-1 (IGF-1 ≈90 nmol/L) with growth hormone (GH) around 2 µg/L, normal thyroid function, low-normal testosterone with low sex hormone-binding globulin, normal gonadotrophins, mildly raised prolactin and borderline-low morning cortisol. A subsequent short synacthen test confirmed an adequate adrenal reserve. Repeat IGF-1 remained elevated and an oral glucose tolerance test showed failure of GH suppression, with values persistently 1.9-2.3 µg/L and a nadir around 1.9 µg/L, confirming acromegaly. Formal visual field testing was normal, concordant with the absence of chiasmal compression on imaging. The case was discussed at the pituitary multidisciplinary team meeting, which recommended transsphenoidal surgery as first-line treatment. Conclusion This case illustrates how a pituitary incidentaloma can unveil clinically important acromegaly when subtle phenotypic changes and cardiometabolic comorbidities are actively sought. It emphasises the need for high clinical suspicion, structured biochemical assessment and early multidisciplinary input, even in the absence of visual field defects, to enable timely surgical management and reduce long-term complication risk.
