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- Understanding risk factors of post-stroke mortalityPublication . Castro, David; Antonio, Nuno; Marreiros, Ana; Nzwalo, HipólitoStroke is one of the leading causes of death worldwide. Understanding the risk factors for poststroke mortality is crucial for improving patient outcomes. This study analyzes and predicts poststroke mortality using the modified Rankin Scale (mRS), a functional neurological evaluation scale. Several Machine Learning models were developed and assessed using a dataset of 332 stroke patients from Hospital de Faro, Portugal, from 2016 to 2018. The Random Forest model outperformed others, achieving an accuracy of 98.5% and a recall of 91.3. Twenty-four risk factors were identified, with stroke severity as the most critical. These findings provide healthcare professionals with valuable tools for early identification and intervention for high-risk stroke patients, enabling informed decision-making and customized treatment plans. This research advances healthcare predictive analytics, offering a precise mortality prediction model and a comprehensive analysis of risk factors, potentially improving clinical outcomes and reducing mortality rates. Future applications could extend to patient monitoring and management across various medical conditions.
- Portuguese recommendations on transthyretin amyloid cardiomyopathy: a step toward disease awareness, prompt referral and early diagnosis and treatmentPublication . Marques, Nuno; Azevedo, OlgaTransthyretin amyloidosis (ATTR) is caused by the extracellular deposition of amyloid fibrils of wild-type (ATTRwt) or variant (ATTRv) transthyretin (TTR). While ATTRwt amyloidosis is essentially a cardiac disease, ATTRv amyloidosis may present with different phenotypes, ranging from predominantly cardiac to predominantly neurologic, or even mixed phenotypes, depending on the TTR gene variant.1---3 Transthyretin amyloid cardiomyopathy (ATTR-CM) is a progressive cardiomyopathy that causes heart failure, dysrhythmias and conduction block, which eventually lead to death.1 Median survival following diagnosis in untreated patients with ATTR-CM is 3.6---4.8 years in the wild-type form, 2.6 years in ATTR-CM due to the Val142Ile variant and 5.8 years in ATTR-CM caused by other TTR variants.4,5 To improve the prognosis of ATTR-CM, it is important to implement strategic measures that (i) increase awareness of ATTR amyloidosis, (ii) ensure early referral of cases with suspicion of ATTR-CM, (iii) promote early screening, diagnosis and treatment of ATTR-CM, and (iv) assure appropriate symptomatic management of the disease. However, some questions remain concerning who should be screened for ATTR-CM, and international recommendations differ regarding the red flags that should prompt screening for ATTR-CM.6
- Portuguese recommendations for the management of transthyretin amyloid cardiomyopathy (Part 1 of 2): screening, diagnosis and treatment. Developed by the task force on the management of transthyretin amyloid cardiomyopathy of the working group on myocardial and pericardial diseases of the portuguese society of cardiologyPublication . Marques, Nuno; Rosa, Sílvia Aguiar; Cordeiro, Filipa; Fernandes, Raquel Menezes; Ferreira, Catarina; Bento, Dina; Brito, Dulce; Cardim, Nuno; Lopes, Luís; Azevedo, OlgaThe Portuguese recommendations for the management of transthyretin amyloid cardiomyopathy (ATTR-CM) evaluate and summarize the available evidence and provide evidence-based recommendations on the best management of patients with ATTR-CM. These recommendations represent the official position of the Working Group on Myocardial and Pericardial Diseases (WGMPD) of the Portuguese Society of Cardiology. The Portuguese WGMPD selected the members of this Task Force as expert professionals involved in the care of patients with this disease. The Task Force performed a critical evaluation of the available evidence on the diagnostic procedures and therapeutic options for ATTR-CM, including an assessment of risk-benefit ratios. The strength of every recommendation and its level of evidence were weighed and scored according to predefined scales, usually those used by the European Society of Cardiology (ESC) in their guidelines, as outlined below in Tables 1 and 2. This Task Force followed voting procedures, and all approved recommendations were subject to a vote and achieved at least 75% agreement among voting members. The experts of the writing panels provided declaration of interest forms for all relationships that might be perceived as actual or potential sources of conflicts of interest. These recommendations were developed without any financial support or involvement of the healthcare industry. The Portuguese WGMPD supervised and coordinated the preparation of these recommendations and was responsible for the approval process. After appropriate revisions, the recommendations were signed off by all the experts involved in the Task Force. The WGMPD submitted the final document for publication in the official journal of the Portuguese Society of Cardiology, Revista Portuguesa de Cardiologia (Portuguese Journal of Cardiology). The recommendations were developed after careful consideration of the scientific knowledge and evidence available at the time of writing. Tables of recommendations are provided in this document along with the corresponding class of recommendation and level of evidence for each statement. Specific areas on which there are uncertainties concerning the existing evidence for the recommendation were also identified. The Task Force members carried out systematic reviews of the literature on these topics, which will be provided in separate publications. These recommendations do not override the individual responsibility of health professionals to make appropriate and accurate decisions in consideration of each individual patient’s health condition.
- High vs low protein intake in chronic critical illness: a systematic review and meta-analysisPublication . Castro, Sílvia; Tome, Ana Maria; Granja, C.; Macedo, A.; Binnie, AlexandraBackground & aims: Patients with persistent organ dysfunction after the first week of intensive care unit (ICU) admission are considered to have chronic critical illness (CCI). Acquired muscle weakness is a common feature of CCI that is accompanied by loss of muscle mass and electromyographic features of myopathy. Optimizing protein intake may help prevent acquired muscle weakness and/or promote muscle recovery, however, the optimal level of protein intake in CCI is uncertain and there is a lack of consensus in published nutritional guidelines. This systematic review focuses on the impact of high versus low protein intake as part of a nutritional strategy for patients with CCI. Methods: The terms “protein intake” and “critically ill” were systematically searched in PUBMED, CENTRAL (Cochrane Central Register of Controlled Trials), and WEB OF SCIENCE on 06/01/2023. We included studies that (1) enrolled critically ill adults (aged 18 years or over) who were in the ICU for more than 7 days and that compared (2) protein intake above and below 1.3 gr/kg administered by any route (enteral and/or parenteral), (3) had an intervention period that occurred primarily after the first 7 days of critical illness and (4) reported clinical outcomes including length of ICU and hospital stay, duration of invasive mechanical ventilation (IMV), mortality, ICU acquired infections, muscle mass and physical function. Studies pertaining to elective surgery, those with intervention periods shorter than 7 days or occurring primarily within the first 7 days of critical illness, those measuring only laboratory parameters as outcomes, and safety and feasibility studies were excluded. Results: Four studies were included (N ¼ 1730) in the meta-analysis and systematic review. Higher (>1.3 g/kg/d) versus lower protein intake was associated with a decrease in early mortality (defined as ICU or 28-day mortality) hazard ratio (HR) 0.42 (95 % confidence interval (CI): 0.26e0.70, P < 0.001), but had no impact on late mortality (defined as the latest mortality timepoint in each study): HR 0.93 (95 % CI 0.76e1.15, P ¼ 0.51). There was no significant difference between intervention and control groups with respect to duration of IMV, duration of ICU or hospital stay, muscle mass, or the incidence of ICUacquired infections. One study reported improvements in physical function at 3 and 6 months in the intervention group. Conclusion: After the first week of critical illness, increasing protein intake to >1.3 g/kg/d may improve early mortality but not late mortality or other clinical outcomes. The small number of relevant studies and the heterogeneity of outcomes assessed, weaken these conclusions. Further studies are warranted to discern whether higher protein intake is beneficial in chronic critical illness. PROSPERO registration number: CRD42023403554; PROSPERO registration name: “The effect of higher than 1,3 g/kg of protein versus lower intake in chronic critically ill patients”
- Detection of a pulmonary mass using lung ultrasound in pre-hospital carePublication . Miravent, Sérgio; Figueiredo, Teresa; Costa Vicente, Bianca IsabelAlthough lung ultrasound (LUS) has limitations in detecting pulmonary masses, especially small or deep-seated lesions that may be obscured by rib shadows or lung air content, screening ultrasound can still be a valuable tool for identifying these abnormalities in pre-hospital settings. It is especially helpful in situations where advanced tests like detailed blood analyses, biopsies, and the gold standard of computed tomography (CT) scans are not available. This portable, quick, and noninvasive technology can play a key role in detecting serious conditions and ensuring patients are referred to specialized care without unnecessary delays.
- Predictive factors driving positive awake test in carotid endarterectomy using machine learningPublication . Pereira-Macedo, Juliana; Duarte-Gamas, Luís; Pereira Pias, Ana Daniela; Myrcha, Piotr; Andrade, José P.; António, Nuno; Marreiros, Ana; Rocha-Neves, JoãoBackground: Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered risk calculator in predicting intraoperative neurologic deficits (INDs). Methods: Data was collected from carotid interventions performed between January 2012 and January 2023 under regional anesthesia. Patients with IND were selected along with consecutive controls without IND in a case-control study design. A predictive model for IND was developed using machine learning, specifically Extreme Gradient Boosting (XGBoost) model, and its performance was assessed and compared to an existing predictive model. Shapley Additive exPlanations (SHAP) analysis was employed for the model interpretation. Results: Among 216 patients, 108 experienced IND during CEA. The AI-based predictive model achieved a robust area under the curve of 0.82, with an accuracy of 0.75, precision of 0.88, sensitivity of 0.59, and F1Score of 0.71. High body mass index (BMI) increased contralateral carotid stenosis, and a history of limb paresis or plegia were significant IND risk factors. Elevated preoperative platelet and hemoglobin levels were associated with reduced IND risk. Conclusions: This AI model provides precise IND prediction in CEA, enabling tailored interventions for high-risk patients and ultimately improving surgical outcomes. BMI, contralateral stenosis, and selected blood parameters emerged as pivotal predictors, bringing significant advancements to decision-making in CEA procedures. Further validation in larger cohorts is essential for broader clinical implementation.
- The burden of COVID-19 care in community and academic intensive care units in Ontario, Canada: a retrospective cohort studyPublication . Pestana, Daniel; Joshi, Divya; Duan, Erick; Fowler, Robert; Tsang, Jennifer; Binnie, AlexandraDuring the COVID-19 pandemic, neighbourhoods with high material deprivation and high proportions of racialized Canadians were disproportionately affected by COVID-19. Many of these neighbourhoods were served by community hospitals. We sought to compare the burden of COVID-19 care in community and academic intensive care units (ICUs) in Ontario, Canada. We included all adult patients admitted to Ontario ICUs with COVID-19 between 1 March 2020 and 31 July 2021 in a retrospective cohort study. We compared patient volumes, demographics, interventions, and outcomes between community hospital corporations (CHCs) and academic hospital corporations (AHCs). During the first three waves of the pandemic, 9,651 adult ICU admissions for COVID-19 were reported across 72 hospital corporations in Ontario: 6,902 (71.5%) in CHCs and 2,749 (28.5%) in AHCs. Days of ICU care per baseline ICU bed were highest in large CHCs ([ 10 baseline ICU beds) relative to AHCs and small CHCs (median [interquartile range], 73.7 [53.8–110.6] vs 42.2 [32.7–71.8] vs 21.4 [7.2–40.3]; Kruskal–Wallis test, P \ 0.001). Among direct ICU admissions, CHC patients had greater severity of illness whereas among transfer ICU admissions, AHC patients were more severely ill. In a multivariable logistic regression model, mortality was similar among patients with index admission to a CHC or AHC; however, patients with index admission to an AHC were more likely to receive extracorporeal membrane oxygenation (adjusted odds ratio, 6.16; 95% confidence interval, 4.72 to 8.11). During the pandemic, Ontario’s large CHCs provided significantly more days of ICU COVID-19 care per baseline ICU bed compared with AHCs and small CHCs. Equipping large CHCs to handle ICU surges during future emerging disease outbreaks should be a priority for pandemic preparedness.
- Enhancing osteoporosis risk prediction using machine learning: a holistic approach integrating biomarkers and clinical dataPublication . Pires de Carvalho, Filipe Ricardo; Gavaia, PauloOsteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annually. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, its limitations, including restricted availability and radiation exposure, highlight the need for alternative screening methods. We developed a machine learning model to predict OP risk using routinely collected clinical data, deliberately excluding DXA measurements to ensure broad accessibility. Using data from NHANES cycles 2007–2014, we analyzed 7924 participants aged 50 years and older, identifying 1636 OP cases (20.6 %) and 6288 normal cases (79.4 %) through comprehensive criteria incorporating both WHO densitometric standards (T-scores ≤ − 2.5) and anthropometric risk factors. We implemented a stacking ensemble model combining four specialized classifiers (Gradient Boosting, Random Forest, XGBoost, and LightGBM) with a logistic regression meta-classifier. The model achieved 93 % accuracy, an AUC of 0.94, and demonstrated robust performance through cross-validation (mean score: 0.929 ± 0.030). feature importance analysis revealed age (6.04 %), arm muscle circumference (5.61 %), and body weight (5.30 %) as the most influential predictors, followed by gender (3.28 %), BMI (2.71 %), and calcium intake (2.42 %). Additional significant predictors included folate (2.28 %), height (2.23 %), hand grip strength (2.21 %), and alkaline phosphatase (2.16 %). These biologically plausible relationships align with established clinical knowledge of OP risk factors. The model’s strong performance metrics and reliance on readily available clinical data suggest its potential as a practical screening tool, particularly in settings with limited DXA access. All code and implementation details are openly available on GitHub, facilitating integration into existing healthcare systems. This approach offers a promising pathway for enhancing early OP detection and risk assessment across diverse healthcare settings.
- Impact of bariatric and metabolic surgery on sarcopenia-related parameters according to the EWGSOP2 consensus criteria in persons living with obesityPublication . Cardoso, Paulo Alexandre e Castro; Santos, Tânia V.; Ramon-Krauel, Marta; Pais, Sandra; De Sousa-Coelho, Ana LuísaAlthough bariatric and metabolic surgery (BS) has proved effective in the treatment of obesity based on the reduction in fat mass and the remission of comorbidities, there is also loss of lean mass after BS which could compromise muscle functionality. According to the European Working Group on Sarcopenia in Older People (EWGSOP), sarcopenia is a disease associated with loss of muscle mass, strength, and function. Through a comprehensive review of the literature, we identified a range of studies focusing on evaluating sarcopenia-related parameters according to the EWGSOP2 consensus criteria, before and after BS. Although most studies reported reductions in skeletal muscle mass and absolute muscle strength after surgery, improvements in muscle functionality were generally achieved, independent of the type of BS.
- Unveiling inter- and intra-patient sequence variability with a multi-sample coronavirus target enrichment approachPublication . Lado, Sara; Thannesberger, Jakob; Spettel, Kathrin; Arapović, Jurica; Ferreira, Bibiana; Lavitrano, Marialuisa; Steininger, ChristophAmid the global challenges posed by the COVID-19 pandemic, unraveling the genomic intricacies of SARS-CoV-2 became crucial. This study explores viral evolution using an innovative high-throughput next-generation sequencing (NGS) approach. By taking advantage of nasal swab and mouthwash samples from patients who tested positive for COVID-19 across different geographical regions during sequential infection waves, our study applied a targeted enrichment protocol and pooling strategy to increase detection sensitivity. The approach was extremely efficient, yielding a large number of reads and mutations distributed across 10 distinct viral gene regions. Notably, the genes Envelope, Nucleocapsid, and Open Reading Frame 8 had the highest number of unique mutations per 1000 nucleotides, with both spike and Nucleocapsid genes showing evidence for positive selection. Focusing on the spike protein gene, crucial in virus replication and immunogenicity, our findings show a dynamic SARS-CoV-2 evolution, emphasizing the virus–host interplay. Moreover, the pooling strategy facilitated subtle sequence variability detection. Our findings painted a dynamic portrait of SARS-CoV-2 evolution, emphasizing the intricate interplay between the virus and its host populations and accentuating the importance of continuous genomic surveillance to understand viral dynamics. As SARS-CoV-2 continues to evolve, this approach proves to be a powerful, versatile, fast, and cost-efficient screening tool for unraveling emerging variants, fostering understanding of the virus’s genetic landscape.