Extracellular vesicles: Methods for purification and characterization.

Extracellular vesicles (EVs) are membrane-bound particles released by cells that play a significant role in intercellular communication. They can be obtained from a variety of sources, including conditioned culture medium, blood and urine. In this chapter we detail the methods for EV isolation and characterization. Isolating and characterizing EVs is essential for understanding their functions in physiological and pathological processes. Advances in isolation and characterization techniques provide opportunities for deeper research into EV biology and its potential applications in diagnostics and therapeutics.

Extracellular vesicles.

Cells, pathogens, and other systems release extracellular vesicles (EVs). The particles promote intercellular communication and contain proteins, lipids, RNA and DNA. Initially considered to be cellular waste in the twentieth century, EVs were becoming recognized for their function in biological communication and control. EVs are divided into many subtypes: exosomes, microvesicles, and apoptotic bodies. Exosomes form in the late endosome/multivesicular body and are released when the compartments fuse with the plasma membrane. Microvesicles are generated by direct budding of the plasma membrane, whereas apoptotic bodies are formed after cellular apoptosis. The new guideline for EVs that describes alternate nomenclature for EVs. The particles modulate the immune response by affecting both innate and adaptive immunity, and their specific the structure allows them to be used as biomarkers to diagnose a variety of diseases. EVs have a wide range of applications, for example, delivery systems for medications and genetic therapies because of their ability to convey specific cellular material. In anti-tumor therapy, EVs deliver therapeutic chemicals to tumor cells. The EVs promote transplant compatibility and reduce organ rejection. Host-parasite interactions, therapeutic and diagnostic for cancer, cardiovascular disease, cardiac tissue regeneration, and the treatment of neurological diseases such as Alzheimer's and Parkinson's. The study of EVs keeps on expanding, revealing new functions and beneficial options. EVs have the potential to change drug delivery, diagnostics, and specific therapeutics, creating a new frontier in biomedical.

Understanding the Dynamics of Domestic Violence During the First Year of the Pandemic: An Integrative Review.

This integrative review aims to analyze and synthesize existing literature to inform our understanding of the multifaceted dimensions of domestic violence during the first year of the COVID-19 pandemic, using a holistic and ecological framework. Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) study design, searches were conducted on six databases, yielding a final sample of 58 articles. The study comprehensively overviews North America, South America, Asia, Europe, Africa, and worldwide research. The literature reveals an alarming increase in domestic violence victimization during the pandemic in most regions and studies, exacerbating pre-existing vulnerabilities. The increase in domestic violence during the pandemic is linked to ecological factors such as lower physical and mental health, rising substance use, and financial stress, which heightened individuals' vulnerability. Lockdowns exacerbated these issues by increasing confinement in homes, disrupting support services, and limiting victims' access to help. Barriers to help-seeking and amplified personal and professional stressors at the care level are identified. Advocacy for improved awareness, cooperation, and inclusive national and institutional policies emerges. This study underscores the urgency of empirical research to generate reliable data on the pandemic's impact on domestic violence. The findings of this study highlight the importance of understanding unique factors affecting specific groups, as well as informing prevention efforts and targeted interventions. Recognizing the mutual benefit of research-practice partnerships is crucial in addressing and preventing domestic violence. This research contributes to a deeper understanding of domestic violence during the pandemic's first year, guiding empirically informed interventions and policy changes.

Glucosylceramide synthase modulation ameliorates murine renal pathologies and promotes macrophage effector function in vitro.

While significant advances have been made in understanding renal pathophysiology, less is known about the role of glycosphingolipid (GSL) metabolism in driving organ dysfunction. Here, we used a small molecule inhibitor of glucosylceramide synthase to modulate GSL levels in three mouse models of distinct renal pathologies: Alport syndrome (Col4a3 KO), polycystic kidney disease (Nek8jck), and steroid-resistant nephrotic syndrome (Nphs2 cKO). At the tissue level, we identified a core immune-enriched transcriptional signature that was shared across models and enriched in human polycystic kidney disease. Single nuclei analysis identified robust transcriptional changes across multiple kidney cell types, including epithelial and immune lineages. To further explore the role of GSL modulation in macrophage biology, we performed in vitro studies with homeostatic and inflammatory bone marrow-derived macrophages. Cumulatively, this study provides a comprehensive overview of renal dysfunction and the effect of GSL modulation on kidney-derived cells in the setting of renal dysfunction.

HIV Diagnosis in the Context of Stable Relationships: A Qualitative Study With Women Living in Portugal.

ABSTRACT: The purpose of this phenomenological study is to explore the acceptance of HIV diagnosis of women in stable relationships. Based on eight semistructured interviews with cisgender Portuguese women, thematic analysis identified four interrelated themes that illustrated the emotional and psychosocial dynamics involved in this journey. Following an HIV diagnosis, participants grappled with complex emotions, societal perceptions, and the internalization of stigma. Marital relationships underwent profound changes, with trust breakdown and emotional distancing. Coping mechanisms ranged from seeking support to living in secrecy, which impacted psychological well-being. Acceptance of HIV diagnosis is influenced by self-stigmatization, societal perceptions of HIV, and gender dynamics. The findings contribute to the development of tailored interventions, emphasizing the interconnected nature of physical and psychological well-being in the diagnosis acceptance process.

Trauma-focused treatments for victims of interpersonal violence: A comparison of treatment interventions and outcomes.

Background: Interpersonal violence represents a critical public health issue globally, with profound psychological impacts on victims. Objective: The main objective of this study was to analyze the effectiveness of different trauma-focused therapies on mental health outcomes of victims of interpersonal violence, at a community mental health clinic. Methods: Employing a secondary data methodology, the research involves 601 participants who reported being victims of sexual assault (49.1%), domestic violence (44.3%) or sexual trafficking (6.7%). The average age of the participants was 35.54 years, with a majority being female (89.8%). Results: Initial assessments revealed distinct symptomatology among the groups; however, by the ninth therapy session, symptom severity converged across the board, surpassing threshold levels for clinical concern. No significant interaction was observed between the type of trauma-focused therapy and the specific trauma encountered, suggesting a beneficial effect of trauma-focused therapies investigated. This uniformity in therapeutic outcomes underscores the potential of trauma-focused therapies to foster psychological healing in victims of diverse forms of interpersonal violence. Conclusions: The findings advocate for the widespread adoption of trauma-focused therapeutic interventions in community settings, emphasizing their role in the recovery of victims, independent of the nature of the trauma or the specific trauma-focused therapeutic model employed.

Keratin 17 modulates the immune topography of pancreatic cancer.

BACKGROUND: The immune microenvironment impacts tumor growth, invasion, metastasis, and patient survival and may provide opportunities for therapeutic intervention in pancreatic ductal adenocarcinoma (PDAC). Although never studied as a potential modulator of the immune response in most cancers, Keratin 17 (K17), a biomarker of the most aggressive (basal) molecular subtype of PDAC, is intimately involved in the histogenesis of the immune response in psoriasis, basal cell carcinoma, and cervical squamous cell carcinoma. Thus, we hypothesized that K17 expression could also impact the immune cell response in PDAC, and that uncovering this relationship could provide insight to guide the development of immunotherapeutic opportunities to extend patient survival. METHODS: Multiplex immunohistochemistry (mIHC) and automated image analysis based on novel computational imaging technology were used to decipher the abundance and spatial distribution of T cells, macrophages, and tumor cells, relative to K17 expression in 235 PDACs. RESULTS: K17 expression had profound effects on the exclusion of intratumoral CD8+ T cells and was also associated with decreased numbers of peritumoral CD8+ T cells, CD16+ macrophages, and CD163+ macrophages (p < 0.0001). The differences in the intratumor and peritumoral CD8+ T cell abundance were not impacted by neoadjuvant therapy, tumor stage, grade, lymph node status, histologic subtype, nor KRAS, p53, SMAD4, or CDKN2A mutations. CONCLUSIONS: Thus, K17 expression correlates with major differences in the immune microenvironment that are independent of any tested clinicopathologic or tumor intrinsic variables, suggesting that targeting K17-mediated immune effects on the immune system could restore the innate immunologic response to PDAC and might provide novel opportunities to restore immunotherapeutic approaches for this most deadly form of cancer.

Modeling Lysosomal Storage Disorders in an Innovative Way: Establishment and Characterization of Stem Cell Lines from Human Exfoliated Deciduous Teeth of Mucopolysaccharidosis Type II Patients.

Among the many lysosomal storage disorders (LSDs) that would benefit from the establishment of novel cell models, either patient-derived or genetically engineered, is mucopolysaccharidosis type II (MPS II). Here, we present our results on the establishment and characterization of two MPS II patient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population has been isolated from LSD patient samples obtained from the dental pulp. Taking into account our results on the molecular and biochemical characterization of those cells and the fact that they exhibit visible and measurable disease phenotypes, we consider these cells may qualify as a valuable disease model, which may be useful for both pathophysiological assessments and in vitro screenings. Ultimately, we believe that patient-derived dental pulp stem cells (DPSCs), particularly those isolated from human exfoliated deciduous teeth (SHEDs), may represent a feasible alternative to induced pluripotent stem cells (iPSCs) in many labs with standard cell culture conditions and limited (human and economic) resources.

Keratin 17 modulates the immune topography of pancreatic cancer.

Background: The immune microenvironment impacts tumor growth, invasion, metastasis, and patient survival and may provide opportunities for therapeutic intervention in pancreatic ductal adenocarcinoma (PDAC). Although never studied as a potential modulator of the immune response in most cancers, Keratin 17 (K17), a biomarker of the most aggressive (basal) molecular subtype of PDAC, is intimately involved in the histogenesis of the immune response in psoriasis, basal cell carcinoma, and cervical squamous cell carcinoma. Thus, we hypothesized that K17 expression could also impact the immune cell response in PDAC, and that uncovering this relationship could provide insight to guide the development of immunotherapeutic opportunities to extend patient survival. Methods: Multiplex immunohistochemistry (mIHC) and automated image analysis based on novel computational imaging technology were used to decipher the abundance and spatial distribution of T cells, macrophages, and tumor cells, relative to K17 expression in 235 PDACs. Results: K17 expression had profound effects on the exclusion of intratumoral CD8 + T cells and was also associated with decreased numbers of peritumoral CD8 + T cells, CD16 + macrophages, and CD163 + macrophages (p < 0.0001). The differences in the intratumor and peritumoral CD8 + T cell abundance were not impacted by neoadjuvant therapy, tumor stage, grade, lymph node status, histologic subtype, nor KRAS, p53, SMAD4, or CDKN2A mutations. Conclusions: Thus, K17 expression correlates with major differences in the immune microenvironment that are independent of any tested clinicopathologic or tumor intrinsic variables, suggesting that targeting K17-mediated immune effects on the immune system could restore the innate immunologic response to PDAC and might provide novel opportunities to restore immunotherapeutic approaches for this most deadly form of cancer.

Image quality assessment of retinal fundus photographs for diabetic retinopathy in the machine learning era: a review.

This study aimed to evaluate the image quality assessment (IQA) and quality criteria employed in publicly available datasets for diabetic retinopathy (DR). A literature search strategy was used to identify relevant datasets, and 20 datasets were included in the analysis. Out of these, 12 datasets mentioned performing IQA, but only eight specified the quality criteria used. The reported quality criteria varied widely across datasets, and accessing the information was often challenging. The findings highlight the importance of IQA for AI model development while emphasizing the need for clear and accessible reporting of IQA information. The study suggests that automated quality assessments can be a valid alternative to manual labeling and emphasizes the importance of establishing quality standards based on population characteristics, clinical use, and research purposes. In conclusion, image quality assessment is important for AI model development; however, strict data quality standards must not limit data sharing. Given the importance of IQA for developing, validating, and implementing deep learning (DL) algorithms, it's recommended that this information be reported in a clear, specific, and accessible way whenever possible. Automated quality assessments are a valid alternative to the traditional manual labeling process, and quality standards should be determined according to population characteristics, clinical use, and research purpose.

Intimate Partner Homicide: Comparison Between Homicide and Homicide-Suicide in Portugal.

Intimate partner homicide (IPH) is a tragic event. Studies involving the comparison between IPH and intimate partner homicide-suicide (IPH-S) are scarce, with few studies in Portugal about this issue. The current study aims to compare IPH and IPH-S perpetrators, the victim-perpetrator relationships dynamics, and homicide circumstances. The data was collected through the analysis of 78 judicial processes of IPH that occurred in Portugal, between 2010 and 2015. Of the cases, 51 were IPH, 20 were IPH-S cases, and seven were attempted suicide cases, being perpetrated in 84.6% (n = 66) for male perpetrators. Suicide after intimate homicide were all committed by men. All judicial processes analyzed refer to heterosexual relationships. Bivariate and multivariate analyses were performed to compare the groups concerning perpetrator and victim sociodemographic characteristics, victim-perpetrator dyadic dynamics, and crime circumstances. The results show mostly common trends between the two groups with some differentiating factors when compared individually (e.g., perpetrator professional status, criminal records). Regression logistic analysis showed no differences between IPH and IPH-S.

Help Comes from Unexpected Places: How a Tiny Fairy and a Tropical Fish may help us Model Mucopolysaccharidoses.

INTRODUCTION: When it comes to disease modeling, countless models are available for Lysosomal Storage Diseases (LSD). Historically, two major approaches are well-established: in vitro assessments are performed in patient fibroblasts, while in vivo pre-clinical studies are performed in mouse models. Still, both platforms have a series of drawbacks. Thus, we implemented two alternative and innovative protocols to mimic a particular sub-group of LSDs, the Mucopolysaccharidoses both in vitro and in vivo. METHODS: The first one relies on a non-invasive approach using dental pulp stem cells from deciduous teeth (SHEDs). SHEDs are multipotent neuronal precursors that can easily be collected. The second uses a state-of-the-art gene editing technology (CRISPR/Cas9) to generate zebrafish disease models. RESULTS: Even though this is an ongoing project, we have already established and characterized two MPS II and one MPS VI SHED cell models. These cells self-maintain through several passages and can give rise to a variety of cells including neurons. Furthermore, all MPS-associated sub-cellular phenotypes we have assessed so far are easily observable in these cells. Regarding our zebrafish models, we have successfully knocked down both naglu and hgsnat and the first results we got from the behavioral analysis are promising ones, as we can observe altered activity and sleep patterns in the genetically modified fish. For this particular approach we chose MPS III forms as our target disorders, since their neurological features (hyperactivity, seizures and motor impairment) and lifespan decrease would be easily recognizable in zebrafish. CONCLUSION: Now that these methods are well-established in our lab, their potential is immense. On one hand, the newly developed models will be of ultimate value to understand the mechanisms underlying MPS sub-cellular pathology, which have to be further elucidated. On the other hand, they will constitute an optimal platform for drug testing in house. Also noteworthy, our models will be published as lab resources and made available for the whole LSD community.

Development of Engineered-U1 snRNA Therapies: Current Status.

Splicing of pre-mRNA is a crucial regulatory stage in the pathway of gene expression. The majority of human genes that encode proteins undergo alternative pre-mRNA splicing and mutations that affect splicing are more prevalent than previously thought. Targeting aberrant RNA(s) may thus provide an opportunity to correct faulty splicing and potentially treat numerous genetic disorders. To that purpose, the use of engineered U1 snRNA (either modified U1 snRNAs or exon-specific U1s-ExSpeU1s) has been applied as a potentially therapeutic strategy to correct splicing mutations, particularly those affecting the 5' splice-site (5'ss). Here we review and summarize a vast panoply of studies that used either modified U1 snRNAs or ExSpeU1s to mediate gene therapeutic correction of splicing defects underlying a considerable number of genetic diseases. We also focus on the pre-clinical validation of these therapeutic approaches both in vitro and in vivo, and summarize the main obstacles that need to be overcome to allow for their successful translation to clinic practice in the future.

Clinician-Driven AI: Code-Free Self-Training on Public Data for Diabetic Retinopathy Referral.

Importance: Democratizing artificial intelligence (AI) enables model development by clinicians with a lack of coding expertise, powerful computing resources, and large, well-labeled data sets. Objective: To determine whether resource-constrained clinicians can use self-training via automated machine learning (ML) and public data sets to design high-performing diabetic retinopathy classification models. Design, Setting, and Participants: This diagnostic quality improvement study was conducted from January 1, 2021, to December 31, 2021. A self-training method without coding was used on 2 public data sets with retinal images from patients in France (Messidor-2 [n = 1748]) and the UK and US (EyePACS [n = 58 689]) and externally validated on 1 data set with retinal images from patients of a private Egyptian medical retina clinic (Egypt [n = 210]). An AI model was trained to classify referable diabetic retinopathy as an exemplar use case. Messidor-2 images were assigned adjudicated labels available on Kaggle; 4 images were deemed ungradable and excluded, leaving 1744 images. A total of 300 images randomly selected from the EyePACS data set were independently relabeled by 3 blinded retina specialists using the International Classification of Diabetic Retinopathy protocol for diabetic retinopathy grade and diabetic macular edema presence; 19 images were deemed ungradable, leaving 281 images. Data analysis was performed from February 1 to February 28, 2021. Exposures: Using public data sets, a teacher model was trained with labeled images using supervised learning. Next, the resulting predictions, termed pseudolabels, were used on an unlabeled public data set. Finally, a student model was trained with the existing labeled images and the additional pseudolabeled images. Main Outcomes and Measures: The analyzed metrics for the models included the area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, and F1 score. The Fisher exact test was performed, and 2-tailed P values were calculated for failure case analysis. Results: For the internal validation data sets, AUROC values for performance ranged from 0.886 to 0.939 for the teacher model and from 0.916 to 0.951 for the student model. For external validation of automated ML model performance, AUROC values and accuracy were 0.964 and 93.3% for the teacher model, 0.950 and 96.7% for the student model, and 0.890 and 94.3% for the manually coded bespoke model, respectively. Conclusions and Relevance: These findings suggest that self-training using automated ML is an effective method to increase both model performance and generalizability while decreasing the need for costly expert labeling. This approach advances the democratization of AI by enabling clinicians without coding expertise or access to large, well-labeled private data sets to develop their own AI models.

Remarkable antibiofilm activity of ciprofloxacin, cefoxitin, and tobramycin, by themselves or in combination, against enteroaggregative Escherichia coli in vitro.

Enteroaggregative Escherichia coli (EAEC), a biofilm forming pathogen, causes acute and persistent diarrhea worldwide, requiring antimicrobial therapy in severe or persistent cases. To determine the susceptibility of EAEC biofilm to antimicrobials, as single-agent or combined therapy, biofilm formation was investigated using EAEC clinical strains via peg lid. Of the 78 initially analyzed strains, 35 could form biofilms, 15 (42.9%; 15/35) were resistant to at least 1 tested antimicrobial and 20 (57.1%) were susceptible to all of them in the planktonic form. The biofilms of these susceptible strains were challenged against chosen antimicrobials, and displayed resistance to tetracycline, trimethoprim-sulfamethoxazole, chloramphenicol, ampicillin, cefotaxime, ceftriaxone (85%-100%), tobramycin (25%), cefoxitin (20%), and ciprofloxacin (5%). Moreover, ciprofloxacin combined with ampicillin, and tobramycin eradicated the biofilm of 2 of the 4 tested strains. Ciprofloxacin, cefoxitin, and tobramycin maintained their activity well against EAEC biofilm, suggesting their possible effectiveness to treat diarrhea caused by biofilm-forming EAEC strains.

Neurological Disease Modeling Using Pluripotent and Multipotent Stem Cells: A Key Step towards Understanding and Treating Mucopolysaccharidoses.

Despite extensive research, the links between the accumulation of glycosaminoglycans (GAGs) and the clinical features seen in patients suffering from various forms of mucopolysaccharidoses (MPSs) have yet to be further elucidated. This is particularly true for the neuropathology of these disorders; the neurological symptoms are currently incurable, even in the cases where a disease-specific therapeutic approach does exist. One of the best ways to get insights on the molecular mechanisms driving that pathogenesis is the analysis of patient-derived cells. Yet, not every patient-derived cell recapitulates relevant disease features. For the neuronopathic forms of MPSs, for example, this is particularly evident because of the obvious inability to access live neurons. This scenario changed significantly with the advent of induced pluripotent stem cell (iPSC) technologies. From then on, a series of differentiation protocols to generate neurons from iPSC was developed and extensively used for disease modeling. Currently, human iPSC and iPSC-derived cell models have been generated for several MPSs and numerous lessons were learnt from their analysis. Here we review most of those studies, not only listing the currently available MPS iPSC lines and their derived models, but also summarizing how they were generated and the major information different groups have gathered from their analyses. Finally, and taking into account that iPSC generation is a laborious/expensive protocol that holds significant limitations, we also hypothesize on a tempting alternative to establish MPS patient-derived neuronal cells in a much more expedite way, by taking advantage of the existence of a population of multipotent stem cells in human dental pulp to establish mixed neuronal and glial cultures.

Predictive value of a positive stress single-photon emission computed tomography or stress cardiac magnetic resonance for ruling in obstructive coronary artery disease in a real-world setting.

INTRODUCTION AND OBJECTIVES: Randomized controlled trials comparing stress cardiac magnetic resonance (CMR) and single-photon emission computed tomography (SPECT) suggest similar diagnostic accuracy for detecting obstructive coronary artery disease (CAD). There are few data on whether this remains true in routine clinical practice. The aim of this study was to assess clinical and angiographic characteristics of patients undergoing invasive coronary angiography (ICA) after stress CMR or SPECT, and to compare their positive predictive value with published results from the CE-MARC trial. METHODS: In this retrospective tertiary-center analysis, we included 429 patients undergoing ICA after a positive stress CMR or positive SPECT performed within the previous 12 months. Obstructive CAD was defined as any coronary artery stenosis ≥50% in a vessel compatible with the ischemic territory on stress testing. RESULTS: Of the total 429 patients, 356 (83%) were referred after a positive SPECT, and 73 (17%) after a positive stress CMR. Patients did not differ according to age, cardiovascular risk factors, previous revascularization or left ventricular dysfunction, but patients with SPECT were more frequently male (p=0.046). The prevalence of obstructive CAD was similar in patients with positive SPECT vs. positive stress CMR (76.1% vs. 80.8%, respectively, p=0.385). The positive predictive values of both techniques were similar to those reported in the CE-MARC trial. CONCLUSION: In this tertiary center analysis, stress CMR and SPECT showed similar positive predictive values, comparable to those reported in the CE-MARC trial. This finding supports the emerging adoption of CMR in clinical practice for the diagnosis and management of CAD.

Implementation of Orthogeriatrics in Portugal.

INTRODUCTION: Orthogeriatrics is the subspecialty of geriatrics that is dedicated to the care of elderly patients with fragility fractures. The Orthogeriatrics Unit of the Vila Nova de Gaia Hospital Centre was the first unit created in Portugal in October 2015, in a co-management model. METHODS: Patients older than 65 years and with femur fractures were admitted to the unit after surgery. The department was run by internists with differentiation in geriatrics, and multidisciplinary support from orthopaedics, physiatrists, physiotherapists, nutritionists, and social workers, as well as rehabilitation nursing. A comprehensive multidisciplinary assessment was performed upon admission, including comprehensive geriatric assessment as well as postoperative monitoring of complications, investigation of fall mechanisms, functional rehabilitation, and outpatient orientation. Analysed variables included demographics, comorbidities, prior level of functionality, delay of orthopaedic surgery, complications, time of hospitalization, functional prognosis, and destination after discharge. Follow-up was maintained to assess short- and medium-term mortality. Kaplan-Meier curves and Cox regression were used for the statistical analysis of mortality. RESULTS: In four years of activity with 444 admissions, the typical patients were women (80.7%), with an average age of 84 years, coming from home (92%) after an accidental fall resulting in a proximal femur fracture. About half (54%) were previously autonomous, but with a high index of comorbidities (mean Charlson Index of 4.85), the most relevant of which were arterial hypertension (71%), malnutrition (46%), heart failure (35%), hyperlipidaemia (34%), osteoporosis (32%), and dementia (16%). During hospitalization, most patients had medical complications (86.3%), the most frequent ones being anaemia (45%), infections (35%), namely, urinary, respiratory, and surgical wound infections, acute heart failure (15%), and acute kidney injury (11%). Prevalent geriatric syndromes were also identified and corrected through protocols for delirium, urinary incontinence, pressure ulcers, and constipation. The mean length of stay was 12.49 days. At discharge, 75% presented a modified Rankin Scale score lower than 3 and 73% of patients were able to return home, with a low referral rate to long-term care facilities (5.9%). The in-hospital mortality rate was 2.65%. It was possible to maintain follow-up protocol after discharge in 343 patients, and the mortality at 12 months was 19.23% and at three years, it was 25.52%, with a risk of death almost doubled for patients discharged with a high degree of dependence (modified Rankin Scale score ≥ 3; OR: 2.19; p < 0.001). CONCLUSION: We demonstrated reduced in-hospital mortality despite an elderly, frail population, with multiple previous comorbidities and a high number of inpatient intercurrences evidencing the importance of a good in-hospital co-management between internal medicine and orthopaedics, demonstrating the benefit of orthogeriatric units in patients with fragility fractures of the femur.