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.

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.

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.

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.

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.

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.

Chloride Applied via Fertilizer Affects Plant Nutrition and Coffee Quality.

The present study had the objective to evaluate the effect of blends of KCl and K2SO4 fertilizers and their influence on the yield and the nutritional state of coffee plants, as well as on the chemical composition and quality of the coffee beverage. The experimental design was in randomized blocks with four repetitions and six treatments (T1: 100% KCl; T2: 75% KCl + 25% K2SO4; T3: 50% KCl + 50% K2SO4; T4: 25% KCl + 75% K2SO4; T5: 100% K2SO4; and a control, without application of K). The following analyses were performed: K and Cl content in the leaves and the soil, stocks of Cl in soil, yield, removal of K and Cl with the beans, cup quality of the beverage, polyphenol oxidase activity (PPO), electric conductivity (EC), potassium leaching (KL), the content of phenolic compounds, the content of total sugars (TS), and total titratable acidity (TTA). The stocks of Cl in the soil decreased as the proportion of KCl in the fertilizer was reduced. The fertilization with KCl reduces the cup quality and the activity of the polyphenol oxidase, probably due to the ion Cl. The increase in the application of Cl directly relates to the increase in potassium leaching, electric conductivity, and titratable acidity. Indirectly, these variables indicate damages to the cells by the use of Cl in the fertilizer. The activity of the polyphenol oxidase enzyme and the cup quality indicate that the ion Cl- reduces the quality of the coffee beverage. K content in the leaves was not influenced by the application of blends of K fertilizer while Cl content increased linearly with KCl applied. The application of KCl and K2SO4 blends influenced coffee yield and the optimum proportion was 25% of KCl and 75% of K2SO4. The highest score in the cup quality test was observed with 100% K2SO4.

Measuring adherence to inhaled control medication in patients with asthma: Comparison among an asthma app, patient self-report and physician assessment.

BACKGROUND: Previous studies have demonstrated the feasibility of using an asthma app to support medication management and adherence but failed to compare with other measures currently used in clinical practice. However, in a clinical setting, any additional adherence measurement must be evaluated in the context of both the patient and physician perspectives so that it can also help improve the process of shared decision making. Thus, we aimed to compare different measures of adherence to asthma control inhalers in clinical practice, namely through an app, patient self-report and physician assessment. METHODS: This study is a secondary analysis of three prospective multicentre observational studies with patients (≥13 years old) with persistent asthma recruited from 61 primary and secondary care centres in Portugal. Patients were invited to use the InspirerMundi app and register their inhaled medication. Adherence was measured by the app as the number of doses taken divided by the number of doses scheduled each day and two time points were considered for analysis: 1-week and 1-month. At baseline, patients and physicians independently assessed adherence to asthma control inhalers during the previous week using a Visual Analogue Scale (VAS 0-100). RESULTS: A total of 193 patients (72% female; median [P25-P75] age 28 [19-41] years old) were included in the analysis. Adherence measured by the app was lower (1 week: 31 [0-71]%; 1 month: 18 [0-48]%) than patient self-report (80 [60-95]) and physician assessment (82 [51-94]) (p < 0.001). A negligible non-significant correlation was found between the app and subjective measurements (ρ 0.118-0.156, p > 0.05). There was a moderate correlation between patient self-report and physician assessment (ρ = 0.596, p < 0.001). CONCLUSIONS: Adherence measured by the app was lower than that reported by the patient or the physician. This was expected as objective measurements are commonly lower than subjective evaluations, which tend to overestimate adherence. Nevertheless, the low adherence measured by the app may also be influenced by the use of the app itself and this needs to be considered in future studies.

Assessment of the Health Status of Women in Prison: A Comparison between Drug Users versus Non-users.

This study aims to analyze the history of substances use, clinical diagnoses, contacts with healthcare, and health complaints. Also, it aims to compare the health status of substance users versus non-users. Health records of 93 detained women from a prison in northern Portugal, with a mean age of 38.02 years old, were reviewed and coded using both International Classification of Primary Care-2 and International Classification of Diseases-10th. Data revealed high percentages of detainees with a history of substance use and pre-existing clinical diagnosis. During the first month of imprisonment, on average, participants had complained to a health professional 14.63 times. Substance users were younger and presented more mental health problems and health complaints. Health policies and professional practices in prison must include immediate assessment of a woman's health concerns and foster the development of efficient protocols to address those problems, especially substance use disorder treatment.

Clinical profiles and factors associated with treatment initiation in survivors of sex trafficking: A comparison with survivors of domestic violence and sexual assault.

OBJECTIVE: Little is known about formal help-seeking for mental health issues in survivors of human sex trafficking (ST) and if their experiences are different from those initiating treatment for sexual assault (SA) or domestic violence (DV). This study sought to characterize the clinical and trauma profiles of treatment-seeking survivors of ST as compared with DV and SA and the predictors of mental health treatment initiation in these three groups. METHOD: The research was based on a secondary data analysis of data gathered from 1,264 treatment-seeking adults from a community mental health treatment facility in the United States. RESULTS: Compared with DV and SA survivors, ST survivors were significantly younger, female, Black, single, unemployed, completed less than high school, and were from the United States. Despite the presence of clinical symptoms among all three groups, findings suggest significant differences in clinical and trauma profiles, with ST survivors reporting lower levels of mental health symptomology compared to DV and SA survivors. Older age (OR = 1.03, 95% CI [1.01, 1.05]), female sex (OR = 3.03, 95% CI [1.89, 4.88]), employment (OR = 0.40, 95% CI [0.24, 0.66]), and better social relationships (OR = 1.09, 95% CI [1.01, 1.16]) were significantly associated with treatment initiation. CONCLUSIONS: This research highlights some important predictors of formal help-seeking, including perceived social relationships. Assessing for support systems in these three groups of survivors of interpersonal violence early when engaging survivors is recommended. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Addressing the psychological trauma in human trafficking victims: A brief review.

OBJECTIVE: This systematic review of the literature aims to systematize the current knowledge on psychological treatments implemented with trafficked children and adults, specifically exploring their effect on the mental health recovery of victims. Integrating this information is an important step to informing practice, as well as examining gaps in the literature and enlightening future research. METHOD: A systematic search was conducted of five electronic databases for journal articles published until October 2019. This study followed the protocol based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (Moher et al., 2009) recommendations. RESULTS: The search yielded six articles for inclusion in the review. Evidence for the efficacy of interventions to increase the mental health recovery of victims is inconclusive as most studies presented a range of methodology limitations, which in turn are related to difficulties with causal inferences and low external validity. CONCLUSION: There is a need for further research in this area to increase informed practices and interventions with human trafficking victims. Implications for practice and research are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Predicting obstructive coronary artery disease in heart failure with reduced ejection fraction: A practical clinical score.

INTRODUCTION AND OBJECTIVES: Obstructive coronary artery disease (CAD) remains the most common etiology of heart failure with reduced ejection fraction (HFrEF). However, there is controversy whether invasive coronary angiography (ICA) should be used initially to exclude CAD in patients presenting with new-onset HFrEF of unknown etiology. Our study aimed to develop a clinical score to quantify the risk of obstructive CAD in these patients. METHODS: We performed a cross-sectional observational study of 452 consecutive patients presenting with new-onset HFrEF of unknown etiology undergoing elective ICA in one academic center, between January 2005 and December 2019. Independent predictors for obstructive CAD were identified. A risk score was developed using multivariate logistic regression of designated variables. The accuracy and discriminative power of the predictive model were assessed. RESULTS: A total of 109 patients (24.1%) presented obstructive CAD. Six independent predictors were identified and included in the score: male gender (2 points), diabetes (1 point), dyslipidemia (1 point), smoking (1 point), peripheral arterial disease (1 point), and regional wall motion abnormalities (3 points). Patients with a score ≤3 had less than 15% predicted probability of obstructive CAD. Our score showed good discriminative power (C-statistic 0.872; 95% CI 0.834-0.909: p<0.001) and calibration (p=0.333 from the goodness-of-fit test). CONCLUSIONS: A simple clinical score showed the ability to predict the risk of obstructive CAD in patients presenting with new-onset HFrEF of unknown etiology and may guide the clinician in selecting the most appropriate diagnostic modality for the assessment of obstructive CAD.