The still under-investigated role of cognitive deficits in PML diagnosis

Background: Despite cognitive deficits frequently represent the first clinical manifestations of Progressive Multifocal Leukoencephalopathy (PML) in Natalizumab-treated MS patients, the importance of cognitive deficits in PML diagnosis is still under-investigated. The aim of the current study is to investigate the cognitive deficits at PML diagnosis in a group of Italian patients with PML. Methods: Thirty-four PML patients were included in the study. The demographic and clinical data, the lesion load and localization, and the longitudinal clinical course was compared between patients with (n = 13) and without (n = 15) cognitive deficit upon PML suspicion (the remaining six patients were asymptomatic). Clinical presentation of cognitive symptoms was described in detail. Result: After symptoms detection, the time to diagnosis resulted to be shorter for patients presenting with cognitive than for patients with non cognitive onset (p = 0.03). Within patients with cognitive onset, six patients were presenting with language and/or reading difficulties (46.15%); five patients with memory difficulties (38.4%); three patients with apraxia (23.1%); two patients with disorientation (15.3%); two patients with neglect (15.3%); one patients with object agnosia (7.7%), one patient with perseveration (7.7%) and one patient with dementia (7.7%). Frontal lesions were less frequent (p = 0.03), whereas temporal lesions were slightly more frequent (p = 0.06) in patients with cognitive deficits. The longitudinal PML course seemed to be more severe in cognitive than in non cognitive patients (F = 2.73, p = 0.03), but differences disappeared (F = 1.24, p = 0.29) when balancing for the incidence of immune reconstitution syndrome and for other treatments for PML (steroids, plasma exchange (PLEX) and other therapies (Mefloquine, Mirtazapine, Maraviroc). Conclusion: Cognitive deficits at PML onset manifest with symptoms which are absolutely rare in MS. Their appearance in MS patients should strongly suggest PML. Clinicians should be sensitive to the importance of formal neuropsychological evaluation, with particular focus on executive function, which are not easily detected without a formal assessment

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

: The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS® v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 ± 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 ± 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 ± 4.9 and 7.8 ± 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 ± 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity > 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI

Outcomes from elective colorectal cancer surgery during the SARS-CoV-2 pandemic

This study aimed to describe the change in surgical practice and the impact of SARS-CoV-2 on mortality after surgical resection of colorectal cancer during the initial phases of the SARS-CoV-2 pandemic

Trace elements in scalp hair samples from patients with relapsing-remitting multiple sclerosis.

BACKGROUND:Epidemiological studies have suggested a possible role of trace elements (TE) in the etiology of several neurological diseases including Multiple Sclerosis (MS). Hair analysis provides an easy tool to quantify TE in human subjects, including patients with neurodegenerative diseases. OBJECTIVE:To compare TE levels in scalp hair from patients with MS and healthy controls from the same geographic area (Sicily). METHODS:ICP-MS was used to determine the concentrations of 21 elements (Ag, Al, As, Ba, Cd, Co, Cr, Cu, Fe, Li, Mn, Mo, Ni, Pb, Rb, Sb, Se, Sr, U, V and Zn) in scalp hair of 48 patients with relapsing-remitting Multiple Sclerosis compared with 51 healthy controls. RESULTS:MS patients showed a significantly lower hair concentration of aluminum and rubidium (median values: Al = 3.76 μg/g vs. 4.49 μg/g and Rb = 0.007 μg/g vs. 0.01 μg/g;) and higher hair concentration of U (median values U: 0.014 μg/g vs. 0.007 μg/g) compared to healthy controls. The percentages of MS patients showing hair elemental concentrations greater than the 95th percentile of controls were 20% for Ni, 19% for Ba and U, and 15% for Ag, Mo and Se. Conversely, the percentages of MS patients showing hair elemental concentrations lower than the 5th percentile of healthy controls were 27% for Al, 25% for Rb, 22% for Ag, 19% for Fe, and 16% for Pb. No significant association was found between levels of each TE and age, disease duration or Expanded Disability Status Scale (EDSS) score. After stratification by gender, healthy subjects did not show any significant difference in trace element levels, while MS patients showed significant differences (p<0.01) for the concentrations of Ag, Cr, Fe, Ni and Sr. No significant differences were also found, at p<0.01, in relation to the use of cigarettes, consume of water, vegetables and place of living. CONCLUSION:The different distributions of TE in hair of MS patients compared to controls provides an additional indirect evidence of metabolic imbalance of chemical elements in the pathogenesis of this disease. The increase in U and decrease in Al and Rb levels in MS compared to controls require further assessments as well as the observed different distributions of other elements

Subcutaneous Uptake on [18F]Florbetaben PET/CT: a Case Report of Possible Amyloid-Beta Immune-Reactivity After COVID-19 Vaccination

Introduction: Large-scale worldwide COVID-19 vaccination programs are being rapidly deployed, and high-risk patients with comorbidity are now receiving the first doses of the vaccine. Physicians should be, therefore, aware of new pitfalls associated with the current pandemic vaccination program, also in the case of [18F]Florbetaben PET/CT.Case PresentationWe described the first image of [18F]Florbetaben PET/CT in the evaluation of a 70-year-old male with suspicious Alzheimer disease and unclear history of heart disease. We detailed the diagnostic imaging PET/CT workup with different findings. Conclusion: In this case, [18F]Florbetaben PET/CT can demonstrate potential beta-amyloid immune-reactivity and deposition associated with the current COVID-19 pandemic vaccination programs. Keywords: Alzheimer; Amyloid; COVID-19; Florbetaben; PET/CT; Vaccination

Basic statistical parameters of trace element contents in scalp hair from Multiple Sclerosis patients (MS) and healthy controls (HC).

<p>Concentration data expressed as μg g^-1 (dry weight basis). Notes: MS: Multiple Sclerosis patients and HC: healthy controls.SD—standard deviation, Q₅, Q₂₅, Q₇₅ and Q₉₅ indicate the 5^th, 25^th, 75^th and 95^th percentiles, respectively. CV indicates the coefficient of variation, calculated as: CV(%) = 100 × SD/mean.</p><p>Basic statistical parameters of trace element contents in scalp hair from Multiple Sclerosis patients (MS) and healthy controls (HC).</p

Results of Mann-Whitney test for differences between MS patients, HC controls and confounding variables.

<p>Results of Mann-Whitney test for differences between MS patients, HC controls and confounding variables.</p