This study aimed to analyze the determinants of neonatal mortality over the last decade (2013-2023), identifying key factors that have influenced neonatal outcomes both before and during the COVID-19 pandemic. Utilizing a systematic literature review approach guided by the PRISMA method, this study evaluates 91 papers collected from indexed databases such as Scopus, PubMed, and Web of Science. The review encompasses studies conducted globally, offering insights into the evolution of neonatal mortality research and the impact of the COVID-19 crisis on neonatal health. The analysis revealed a complex array of risk determinants, categorized into socioeconomic factors, clinical factors, and healthcare access and quality. Notable factors include rural versus urban healthcare disparities, prenatal and postnatal care quality, and the influence of healthcare infrastructure on neonatal outcomes. This study highlights the shifting focus of neonatal mortality research in response to global health challenges, including the pandemic. The findings underscore the need for multidisciplinary approaches to address neonatal mortality, emphasizing the importance of enhancing healthcare systems, improving maternal education, and ensuring equitable access to quality care. Future research should explore the long-term effects of the COVID-19 pandemic on neonatal health and investigate the efficacy of interventions in diverse healthcare settings.

Dental implant fractures pose a significant challenge to long-term treatment success. This systematic review aims to comprehensively examine the clinical factors influencing dental implant fractures (IFs). Furthermore, strategies to choose the right type of implant and prevent this complication are addressed. A systematic search was conducted across PubMed, Scopus, and Web of Science databases. Eligible studies included retrospective case-control, prospective cohort studies, and clinical trials. The initial search yielded 361 articles, of which 312 were excluded being these reviews, case reports, irrelevant, or written in languages other than English. This left 49 articles, with only 6 meeting the eligibility criteria for an in-depth review. These studies, all retrospective case-control, examine implant characteristics, patient demographics, surgical and prosthetic variables, biomechanical and functional factors, clinical and procedural variables, complications and maintenance issues. The risk of bias was assessed as low using the ROBINS-I tool. Key findings suggest a correlation between implant diameter and structural resistance, with wider implants demonstrating reduced fracture risk. Additionally, posterior regions, especially molars and premolars, exhibit higher susceptibility to IFs due to increased masticatory forces. Implant design and material may considerably influence fracture risk, with conical implants and screw-retained prostheses showing higher vulnerability. Biomechanical overload, particularly in patients with bruxism, emerges as a primary contributing factor to IFs. Prosthesis type significantly influences fracture incidence, with cantilever prostheses posing a higher risk due to increased stress. Peri-implant bone loss is strongly associated with IFs, emphasizing the need for meticulous preoperative assessments and individualized management strategies. Future research should prioritize larger and heterogeneous populations with long-term follow-up and standardized methodologies to enhance the generalizability and comparability of findings. Randomized controlled trials and biomechanical studies under controlled conditions are also essential to elucidate the complex interactions contributing to IFs and developing effective prevention strategies. Additionally, integrating patient-reported outcomes may offer a comprehensive understanding of the impact of IFs on quality of life.

UNASSIGNED: Breast cancer is the leading cause of cancer-related fatalities among women worldwide. Conventional screening and risk prediction models primarily rely on demographic and patient clinical history to devise policies and estimate likelihood. However, recent advancements in artificial intelligence (AI) techniques, particularly deep learning (DL), have shown promise in the development of personalized risk models. These models leverage individual patient information obtained from medical imaging and associated reports. In this systematic review, we thoroughly investigated the existing literature on the application of DL to digital mammography, radiomics, genomics, and clinical information for breast cancer risk assessment. We critically analyzed these studies and discussed their findings, highlighting the promising prospects of DL techniques for breast cancer risk prediction. Additionally, we explored ongoing research initiatives and potential future applications of AI-driven approaches to further improve breast cancer risk prediction, thereby facilitating more effective screening and personalized risk management strategies.
UNASSIGNED: This study presents a comprehensive overview of imaging and non-imaging features used in breast cancer risk prediction using traditional and AI models. The features reviewed in this study included imaging, radiomics, genomics, and clinical features. Furthermore, this survey systematically presented DL methods developed for breast cancer risk prediction, aiming to be useful for both beginners and advanced-level researchers.
UNASSIGNED: A total of 600 articles were identified, 20 of which met the set criteria and were selected. Parallel benchmarking of DL models, along with natural language processing (NLP) applied to imaging and non-imaging features, could allow clinicians and researchers to gain greater awareness as they consider the clinical deployment or development of new models. This review provides a comprehensive guide for understanding the current status of breast cancer risk assessment using AI.
UNASSIGNED: This study offers investigators a different perspective on the use of AI for breast cancer risk prediction, incorporating numerous imaging and non-imaging features.

The objective of this article is to identify the factors that influence the choice of contraceptive methods in the postpartum period.
We conducted a qualitative systematic review including articles published between 2000 and 2021 on postpartum contraception and its related influential factors. Relying on Preferred Reporting Items for Systematic Reviews and Meta-Analyses and synthesis without meta-analysis checklists, the search strategy relied on a combination of 2 lists of keywords applied to 9 databases. A bias assessment was carried out with the help of the Cochrane\'s randomized controlled trial tool, the checklist from Downs and Black, and Consolidated criteria for reporting qualitative research (CoreQ). A thematic analysis was performed to identify categories of influential factors.
A total of 34 studies met our inclusion criteria and enabled us to isolate 4 categories of factors: (1) demographic and economic factors (geographic and ethnic origin, age, living environment, education/wealth), (2) clinical elements (parity, evolution of pregnancy, childbirth and afterwards, contraception used previously and its mechanism, pregnancy planning), (3) health care delivery (pregnancy monitoring, sessions about contraception, health care system, place of delivery), and (4) sociocultural factors (knowledge and beliefs about contraception, religion, the influence of family and society). The decision process related to postpartum contraception is influenced by a combination of socioenvironmental factors and clinical elements.
The main influential factors (parity, level of education, knowledge and beliefs about contraception, and influence of family) need to be addressed by clinicians during consultations. Further multivariate research should provide quantitative data on this topic.

Bipolar disorder (BD) is a multifactorial chronic psychiatric disease highly defined by genetic, clinical, environmental and social risk factors. The present systematic review and meta-analysis aimed to examine the relationship between inflammatory and neurotrophic factors and clinical, social and environmental factors involved in the development and the characterization of BD. Web of Science, PubMed, PsycINFO, Scopus and Science Direct were searched by two independent reviewers. The systematic review was registered in PROSPERO (CRD42020180626). A total of 51 studies with 4547 patients with a diagnosis of BD were selected for systematic review. Among them, 18 articles were included for meta-analysis. The study found some evidence of associations between BDNF and/or inflammatory factors and different stressors and functional and cognitive impairment, but limitations prevented firm conclusions. The main finding of the meta-analysis was a negative correlation between circulating levels of BDNF and depression severity score (standardized mean difference = -0.22, Confidence Interval 95% = -0.38, -0.05, p = 0.01). Evidence indicates that BDNF has a role in the depressive component of BD. However, the poor consistency found for other inflammatory mediators clearly indicates that highly controlled studies are needed to identity precise biomarkers of this disorder.

The pulmonary route has long been used for drug administration for both local and systemic treatment. It possesses several advantages, which can be categorized into physiological, i.e., large surface area, thin epithelial membrane, highly vascularized, limited enzymatic activity, and patient convenience, i.e., non-invasive, self-administration over oral and systemic routes of drug administration. However, the formulation of dry powder for pulmonary delivery is often challenging due to restrictions on aerodynamic size and the lung\'s lower tolerance capacity in comparison with an oral route of drug administration. Various physicochemical properties of dry powder play a major role in the aerosolization, deposition, and clearance along the respiratory tract. To prepare suitable particles with optimal physicochemical properties for inhalation, various manufacturing methods have been established. The most frequently used industrial methods are milling and spray-drying, while several other alternative methods such as spray-freeze-drying, supercritical fluid, non-wetting templates, inkjet-printing, thin-film freezing, and hot-melt extrusion methods are also utilized. The aim of this review is to provide an overview of the respiratory tract structure, particle deposition patterns, and possible drug-clearance mechanisms from the lungs. This review also includes the physicochemical properties of dry powder, various techniques used for the preparation of dry powders, and factors affecting the clinical efficacy, as well as various challenges that need to be addressed in the future.

Numerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the covariates, performances and risk of bias of these algorithms.
We systematically searched MEDLINE up to 20 May 2020 and selected studies describing the development, external validation or clinical utility of a multivariable warfarin dosing algorithm. Two investigators conducted data extraction and quality assessment.
Of 10 035 screened records, 266 articles were included in the review, describing the development of 433 dosing algorithms, 481 external validations and 52 clinical utility assessments. Most developed algorithms were for dose initiation (86%), developed by multiple linear regression (65%) and mostly applicable to Asians (49%) or Whites (43%). The most common demographic/clinical/environmental covariates were age (included in 401 algorithms), concomitant medications (270 algorithms) and weight (229 algorithms) while CYP2C9 (329 algorithms), VKORC1 (319 algorithms) and CYP4F2 (92 algorithms) variants were the most common genetic covariates. Only 26% and 7% algorithms were externally validated and evaluated for clinical utility, respectively, with <2% of algorithm developments and external validations being rated as having a low risk of bias.
Most warfarin dosing algorithms have been developed in Asians and Whites and may not be applicable to under-served populations. Few algorithms have been externally validated, assessed for clinical utility, and/or have a low risk of bias which makes them unreliable for clinical use. Algorithm development and assessment should follow current methodological recommendations to improve reliability and applicability, and under-represented populations should be prioritized.

Background: Clinical and functional outcome improvement in psychotic disorders is a challenge for the investigators. Recent advances offered opportunities for ameliorating the course of the illness during its early stages and for identifying treatment-resistant patients. Patients who had not response to two different antipsychotics, administered at correct doses for a sufficient period, can be operationally considered treatment-resistant. Available evidence suggested that the response\'s trajectory to the antipsychotic treatment revealed that a small proportion of subjects are poor responders (8.2%), the majority of patients have a moderate response (76.4%), and only 15.4% can be considered rapid responders with the greatest magnitude of response. Patients with first episode of psychosis generally obtain a more favorable response profile. Nevertheless, in around 25% of these patients symptoms of psychosis persist with a worse long-term course of illness. Objectives: The aim of this review is to report current evidences on the main predictors of treatment non-response in patients at early stage of psychosis. Methods: We used a specific string that guaranteed a high sensitive search in pubmed. We included the following types of publications: randomized-controlled trials, observational studies, longitudinal studies, retrospective studies, case-control studies, open-label investigations, cohort studies, and reviews. Publications must concern predictors of treatment resistance in early psychosis. Results: Forty-seven records were included: 5 reviews, 3 meta-analyses, 22 longitudinal studies, 2 retrospective studies, 1 naturalistic study, 6 randomized controlled trials, 2 open-label studies, 2 case-control studies, 4 cohort studies, 2 retrospective studies. Several factors were identified as predictors of treatment resistance: lower premorbid functioning; lower level of education; negative symptoms from first psychotic episode; comorbid substance use; younger age at onset; lack of early response; non-adherence to treatment; and longer duration of untreated psychosis. The role of gender and marital status is still controversial. More evidences are needed about neurobiological, genetic, and neuroimaging factors. Conclusions: The identification of specific predictive factors of treatment resistance in patients with first episode of psychosis ameliorates the quality of clinical management of these patients in the critical early phase of schizophrenia.

OBJECTIVE: To systematically review the literature to determine what clinical factors influence patient outcomes after meniscal root repairs.
METHODS: A systematic review of multiple databases was performed. The inclusion criteria included English language, studies evaluating clinical and/or radiographic factors related to meniscal root repair outcomes, medial or lateral posterior root repairs, and human studies. The exclusion criteria included meniscectomy studies, meniscal body studies, technique descriptions, studies reporting only failure rate of meniscal repairs, multiligament repairs, abstracts, controlled laboratory studies, meta-analyses, and systematic reviews.
RESULTS: Five studies were included for final analysis including four case series and one retrospective cohort study. A total of 178 patients in the five studies underwent posterior meniscal root repair (179 knees total). The mean age was 51.4 years. The mean duration of follow-up was 34.5 months. The mean Moga quality rating for case series studies was 15 points (83.3%) and NOS score for the retrospective comparative study was 8. Body mass index (BMI) was not associated with outcomes in 3/3 studies assessing BMI. Increased age was associated with worse outcome in 1/5 studies and had no association in 4/5 studies. Knee varus >5° was associated with worse outcomes in 3/3 studies.
CONCLUSIONS: Risk factors for poor clinical outcomes after posterior meniscal root repair include pre-existing high-grade (Outerbridge grade ≥ 3) chondral lesions and severe varus knee alignment (>5°) for medial root repairs.
METHODS: IV, systematic review.

BACKGROUND: There is a modest but consistent association between violence and schizophrenia. The consequences of serious violence could be catastrophic for the victims, as well as the patients themselves and the community. Any knowledge that would help to prevent acts of serious violence would be of considerable value for the individual and the society.
OBJECTIVE: To identify external and clinical risk factors for serious violence in schizophrenia, in addition to considering the strength of the association between the factors assessed and severe violence.
METHODS: This was accomplished by a literature survey. One-hundred and two relevant papers were identified that were published during the past 20 years. Forty-four papers were assessed for eligibility. In all, 27 studies including clinical or cognitive variables were reviewed systematically. An effect size was reported where an odds ratio (OR) could be identified or calculated from available data. Five external factors and six clinical domains were evaluated.
RESULTS: Substance abuse is robustly linking schizophrenia and violence. Among the clinical factors, insight, impulsivity, psychopathy, motor speed and a global measure of cognition are the factors with the strongest empirical evidence for an association with severe violence.
CONCLUSIONS: This is the first systematic review of risk factors for severe violence in schizophrenia, in which a great number of clinical and external factors have been evaluated. Most of the clinical factors have been compared on effect size. The identified factors that represent an increased risk of violence in patients with schizophrenia should be included in risk assessments.