Compagnie Africaine des Peintures

<h3>Background and Importance</h3> Implantable medical devices (IMDs) play a central role in orthopaedic surgery, yet post-operative complications and device recalls highlight the critical need for robust traceability. International safety frameworks – including the EU Medical Device Regulation and FDA’s Unique Device Identification (UDI) initiative – emphasise the mandatory use of patient implant cards (PICs) to ensure device traceability and patient safety. Nevertheless, implementation remains inconsistent, with limited data on real-world adherence and distribution of PICs. <h3>Aim and Objectives</h3> This study aimed to evaluate the status of implant traceability and the distribution rate of patient implant cards in orthopaedic units, to identify gaps in workflow, professional training and supplier compliance, and to propose actionable recommendations for standardisation and digital integration of PIC processes. <h3>Material and Methods</h3> A cross-sectional observational audit was performed over a three-month period in 2024. Data were collected from 1 240 orthopaedic implant files, responses of 40 healthcare professionals, and information from 7 medical device suppliers. Structured questionnaires were used, and data were analysed using SPSS v26 with chi-square and ANOVA tests (significance p &lt; 0.05). Key variables included PIC availability, staff awareness of PIC obligations, supplier performance, and existence of digital traceability systems. <h3>Results</h3> The global availability rate of PICs was 29%. Among professionals, 53% were unaware of the regulatory requirement to provide PICs, while 47% acknowledged responsibility but reported absence of standard protocols. Supplier compliance differed significantly (p = 0.02), with larger suppliers more likely to provide complete PIC documentation. No unified digital traceability platform was in use; traceability was managed via paper logbooks, contributing to inconsistencies. <h3>Conclusion and Relevance</h3> Significant deficiencies in implant traceability pose risks to patient safety and regulatory compliance. The adoption of a standardised PIC model, integration of UDI data into electronic health records, and development of a digital e-PIC system can strengthen traceability, enhance postoperative surveillance, and align local practice with international standards. Ongoing professional training and supplier accountability are essential to sustain improvements. <h3>References and/or Acknowledgements</h3> 1. Vaillant T, <i>et al. Pharm Hosp Clin.</i> 2018;<b>53</b>(1):3–9. 2. Kozak K, et al. <i>JMIR Med Inform.</i> 2023;<b>11</b>:e41614. https://doi.org/10.2196/41614 <h3>Conflict of Interest</h3> No conflict of interest

Background/Objectives: Acute respiratory distress syndrome (ARDS) represents a critical complication in polytrauma patients, characterized by diffuse lung inflammation and bilateral pulmonary infiltrates with mortality rates reaching 45% in intensive care units (ICU). The heterogeneous nature of ARDS and complex clinical presentation in severely injured patients poses substantial diagnostic challenges, necessitating early prediction tools to guide timely interventions. Machine learning (ML) algorithms have emerged as promising approaches for clinical decision support, demonstrating superior performance compared to traditional scoring systems in capturing complex patterns within high-dimensional medical data. Based on the identified research gaps in early ARDS prediction for polytrauma populations, our study aimed to: (i) develop a balanced random forest (BRF) ML model for early ARDS prediction in critically ill polytrauma patients, (ii) identify the most predictive clinical features using ANOVA-based feature selection, and (iii) evaluate model performance using comprehensive metrics addressing class imbalance challenges. Methods: This retrospective cohort study analyzed 407 polytrauma patients admitted to the ICU of the Center of Traumatology and Major Burns of Ben Arous, Tunisia, between 2017 and 2021. We implemented a comprehensive ML pipeline that incorporates Tomek Links undersampling, ANOVA F-test feature selection for the top 10 predictive variables, and SMOTE oversampling with a conservative sampling rate of 0.3. The BRF classifier was trained with class weighting and evaluated using stratified 5-fold cross-validation. Performance metrics included AUROC, PR-AUC, sensitivity, specificity, F1-score, and Matthews correlation coefficient. Results: Among 407 patients, 43 developed ARDS according to the Berlin definition, representing a 10.57% incidence. The BRF model demonstrated exceptional predictive performance with an AUROC of 0.98, a sensitivity of 0.91, a specificity of 0.80, an F1-score of 0.84, and an MCC of 0.70. Precision-recall AUC reached 0.86, demonstrating robust performance despite class imbalance. During stratified cross-validation, AUROC values ranged from 0.93 to 0.99 across folds, indicating consistent model stability. The top 10 selected features included procalcitonin, PaO2 at ICU admission, 24-h pH, massive transfusion, total fluid resuscitation, presence of pneumothorax, alveolar hemorrhage, pulmonary contusion, hemothorax, and flail chest injury. Conclusions: Our BRF model provides a robust, clinically applicable tool for early prediction of ARDS in polytrauma patients using readily available clinical parameters. The comprehensive two-step resampling approach, combined with ANOVA-based feature selection, successfully addressed class imbalance while maintaining high predictive accuracy. These findings support integrating ML approaches into critical care decision-making to improve patient outcomes and resource allocation. External validation in diverse populations remains essential for confirming generalizability and clinical implementation.

This study investigated the molecular and phenotypic characteristics of antimicrobial resistance in Escherichia coli isolates recovered from the ceca of healthy broilers in Tunisia. A total of 111 E. coli isolates were obtained from chicken samples collected at slaughterhouses and cultured on cefotaxime-supplemented MacConkey agar. All isolates exhibited a multidrug-resistant (MDR) phenotype, and 72.1% were confirmed as extended-spectrum β-lactamase (ESBL) producers. The most frequent β-lactamase gene was blaCTX-M-G1, followed by blaTEM and blaSHV. Carbapenem resistance genes (blaOXA-48 and blaIMP) were detected in 12.6% and 6.3% of isolates, respectively, while six isolates harbored the colistin resistance gene mcr-1. Among the tested virulence genes, fimH, traT, and iutA were the most prevalent, detected in over 70% of isolates. Class 1 integrons were present in 83% of isolates, and class 2 integrons in 39.6%, with gene cassettes encoding resistance to trimethoprim (dfrA) and streptomycin (aadA). These findings highlight the widespread presence of MDR and ESBL-producing E. coli strains with virulence traits and integrons in poultry, underscoring the risk of transmission to humans. This study provides essential data supporting the implementation of integrated surveillance strategies in line with the One Health approach.

Epidermoid cysts, originating from ectopic embryonic epithelial cells, are a common type of benign intracranial tumor. However, intraventricular epidermoid cysts are rare, with those occupying the lateral ventricles being exceptionally uncommon. This report details the case of a 59-year-old male presenting with recurrent headaches over an 8-month period, accompanied by behavioral changes, memory impairment, and seizures. Magnetic resonance imaging of the brain revealed a large intraventricular mass consistent with an epidermoid cyst. The patient underwent subtotal resection via a transfrontal transventricular approach, resulting in good postoperative recovery.

Postoperative fibrinogen deficiency after surgical removal of a brain tumor can cause potentially serious complications, such as intracranial hematoma, and worsen the patient's outcome. Our study aimed to determine the prevalence of hypofibrinogenemia after resection of intracranial tumor, to identify the risk factors for this abnormality, and to evaluate the prognosis of patients with this hemostasis disorder. We conducted a prospective, descriptive study including 120 patients who presented for brain tumor resection without preoperative fibrinogen deficiency and had given their consent to participate in the study. We determined the fibrinogen level the day before the procedure, at 1 h and 24 h postoperatively. We determined the prevalence of postoperative fibrinogen deficiency. Postoperative complications, neurological status of the patient, and mortality at 3 months were subsequently recorded. Forty-eight patients presented postoperative fibrinogen deficiency with a high prevalence of 40%. Our study identified three predictive independent risk factors of fibrinogen deficiency after surgical resection of brain tumor: histological type of meningioma (P = 0.015), prolonged duration of surgery (more than 195 min) (P = 0.045), and use of surgicel as a hemostatic product intraoperatively (P = 0.009). Postoperative hematoma and sensory-motor deficit were significantly associated with postoperative fibrinogen deficiency (P < 0.001). Patients with postoperative hypofibrinogenemia had worse Glasgow Outcome Scale-Extended at discharge and after 3 months. On the other hand, fibrinogen deficiency after surgical removal of the intracranial tumor was not significantly associated with increased postoperative mortality. We found a high prevalence of hypofibrinogenemia after brain tumor resection (40%). This anomaly increases the risk of intracranial hematoma. It, therefore, deserves the attention of the practitioner to correct it rapidly and avoid its potentially serious complications.

La pandémie du COVID-19 a provoqué une crise sanitaire imprévue. Les patients atteints de covid-19 séjournant dans un centre de confinement sont exposés à une détresse psychologique majeure et ont besoin de soins appropriés. Dans notre étude, nous nous sommes intéressés aux patients COVID-19, séjournant dans un centre de confinement tunisien pour évaluer les répercussions psychologiques d’être infectés par COVID-19 et d’être placé en quarantaine.Les données recueillies portaient sur les caractéristiques sociodémographiques et cliniques des patients. La détresse psychologique a été évaluée par l’échelle de dépression, d'anxiété et de stress (DASS-21) de 21 items) dans la version arabe. Les variables qualitatives ont été décrites à l'aide de fréquences et les variables quantitatives ont été décrites à l'aide de moyennes et d’écarts-types (DS).Une comparaison des variables sociodémographiques entre les patients atteints de COVID-19 a été réalisée au moyen d'un test T et ANOVA.Des analyses de régression linéaire multivariée ont été utilisées pour identifier les variables associées indépendamment au score DASS-21.Un total de 148 patients a été recrutés. L’âge moyen était de 41,39 ans et le rapport de masculinité était de 1,17. La durée du séjour dans le centre de confinement était de 35,86 jours avec des extrêmes allant de 7 à 86 jours.79,7 % des participants étaient asymptomatiques tandis que 20,3 % d'entre eux étaient symptomatiques. Selon les scores DASS-21, 74,3 % des participants n’étaient pas déprimés et 64,9 % d'entre eux n’étaient pas anxieux. De plus, les types légers à modérés de dépression, d'anxiété et de stress étaient plus fréquents que les types graves et extrêmement graves. Plusieurs facteurs étaient significativement associés à la détresse psychologique comme l'erreur de jugement de la santé physique et mentale et la peur d’être contagieux. Le sexe féminin et la durée du séjour dans le centre de confinement étaient significativement associés à l'anxiété et à la dépression. L’âge de plus de 41 ans, les maladies physiques et les symptômes de la COVID-19 étaient significativement associés à la gravité de la détresse psychologique.La pandémie de COVID-19 a créé une crise mondiale imprévisible qui est loin d’être une simple crise sanitaire avec des répercussions sur toutes les dimensions de la vie. Elle a eu des répercussions négatives sur l’économie, l'environnement, les interactions sociales, la vie culturelle, notre santé physique et notre santé mentale. Ainsi, des interventions multidisciplinaires après la période d'infection sont fortement recommandées.

The grading of glial tumors is based on morphological and sometimes on molecular features. Many markers have been assessed in order to grade the glial tumours without a real consensus. Some authors reported that SRSF1, a spiling factor, presents an expression correlated to the tumours grades. In this study, we aimed to assess the utility of the SRSF1 into the grading of gliomas based on its immunohistochemical expression. The authors conducted a meta-analysis under the PRISMA guidelines during a 10-year-period (2013-2023). The Meta-Disc software 5.4 (free version) was used. Q test and I2 statistics were carried out to explore the heterogeneity among studies. Meta-regression was performed in case of significant heterogeneity. Publication bias was assessed using the funnel plot test and the Egger's test (free version JASP). According to the inclusion criteria, 4 studies from 193 articles were included. The pooled SEN, SPE and DOR accounted respectively for 0.592, 0.565 and 1.852. The AUC was estimated to 0.558 suggesting a bad diagnostic accuracy. The heterogeneity in the pooled SEN and SPE was statistically significant. The meta-regression analysis focusing on the technique used, the clones, the dilution, the interpretation technique revealed no covariate factors (P>0.05). Even if this meta-analysis highlighted the absence of a real diagnostic utility of the SRSF1 in grading the glial tumours, the heterogeneity revealed reinforces the need for more prospective studies performed according to the quality assessment criteria.