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Purpose: Artifacts in magnetic resonance imaging (MRI) scans degrade image quality and thus negatively affect the outcome measures of clinical and research scanning. Considering the time-consuming and subjective nature of visual quality control (QC), multiple (semi-)automatic QC algorithms have been developed. This systematic review presents an overview of the available (semi-)automatic QC algorithms and software packages designed for raw, structural T1-weighted (T1w) MRI datasets. The objective of this review was to identify the differences among these algorithms in terms of their features of interest, performance, and benchmarks. Methods: We queried PubMed, EMBASE (Ovid), and Web of Science databases on the fifth of January 2023, and cross-checked reference lists of retrieved papers. Bias assessment was performed using PROBAST (Prediction model Risk Of Bias ASsessment Tool). Results: A total of 18 distinct algorithms were identified, demonstrating significant variations in methods, features, datasets, and benchmarks. The algorithms were categorized into rule-based, classical machine learning-based, and deep learning-based approaches. Numerous unique features were defined, which can be roughly divided into features capturing entropy, contrast, and normative measures. Conclusion: Due to dataset-specific optimization, it is challenging to draw broad conclusions about comparative performance. Additionally, large variations exist in the used datasets and benchmarks, further hindering direct algorithm comparison. The findings emphasize the need for standardization and comparative studies for advancing QC in MR imaging. Efforts should focus on identifying a dataset-independent measure as well as algorithm-independent methods for assessing the relative performance of different approaches. [ABSTRACT FROM AUTHOR]

Rectal atresia (RA) affects only 1 to 2% of all children with anorectal malformations. No consensus on optimal treatment strategy is yet achieved. Therefore, the aim of this systematic review is to summarize all surgical interventions for RA and outcomes described in the current literature. A literature search was conducted in PubMed, Embase, Web of Science, and Cochrane Library on January 24, 2022. All studies describing treatment for RA in children (< 18 years) were included. Operation technique and postoperative complications were listed. Only descriptive analysis was anticipated. Quality of the studies was assessed using Johanna Briggs Institute critical appraisal checklist for case reports and series. The search yielded 6,716 studies of which, after duplicate removal, 4,028 were excluded based on title and abstract screening. After full-text assessment, 22 of 90 studies were included, yielding 70 patients. Posterior sagittal anorectoplasty (PSARP) and pull-through were most performed (43/70 and 18/70 patients, respectively). Four patients experienced postoperative complications: anal stenosis (n = 1), anastomotic stenosis (n = 2), and death due to a pulmonary complication (n = 1). In the low-quality literature available, most patients with RA are treated with PSARP or pull-through technique. A low complication rate of both has been described but follow-up was often not mentioned. Larger well-designed studies should be performed to determine optimal treatment strategy for children with RA. This study reflects level of evidence V. [ABSTRACT FROM AUTHOR]

Background the efficacy and outcomes of geriatric rehabilitation (GR) have previously been investigated. However, a systematic synthesis of the aspects that are important to patients regarding the quality of GR does not exist. Objective the aim of this scoping review was to systematically synthesise the patients' perspective on the quality of GR. Methods we followed the Scoping Review framework and gathered literature including a qualitative study design from multiple databases. The inclusion criteria were: a qualitative study design; a geriatric population; that patients had participated in a geriatric rehabilitation programme and that geriatric rehabilitation was assessed by the patient. The results sections of the included studies were analysed using a thematic analysis approach. Results twenty articles were included in this review. The main themes identified were: (i) the need for information about the rehabilitation process, (ii) the need for telling one's story, (iii) the need for support (physical, psychological, social and how to cope with limitations), (iv) the need for shared decision-making and autonomy, (v) the need for a stimulating rehabilitation environment and (vi) the need for rehabilitation at home. Conclusion in this study, we identified the aspects that determine the quality of rehabilitation from the patient's perspective, which may lead to a more holistic perspective on the quality of GR. [ABSTRACT FROM AUTHOR]

Background: Machine learning (ML) has seen an increase in application, and is an important element of a digital evolution. The role of ML within upper gastrointestinal surgery for malignancies has not been evaluated properly in the literature. Therefore, this systematic review aims to provide a comprehensive overview of ML applications within upper gastrointestinal surgery for malignancies. Methods: A systematic search was performed in PubMed, EMBASE, Cochrane, and Web of Science. Studies were only included when they described machine learning in upper gastrointestinal surgery for malignancies. The Cochrane risk-of-bias tool was used to determine the methodological quality of studies. The accuracy and area under the curve were evaluated, representing the predictive performances of ML models. Results: From a total of 1821 articles, 27 studies met the inclusion criteria. Most studies received a moderate risk-of-bias score. The majority of these studies focused on neural networks (n = 9), multiple machine learning (n = 8), and random forests (n = 3). Remaining studies involved radiomics (n = 3), support vector machines (n = 3), and decision trees (n = 1). Purposes of ML included predominantly prediction of metastasis, detection of risk factors, prediction of survival, and prediction of postoperative complications. Other purposes were predictions of TNM staging, chemotherapy response, tumor resectability, and optimal therapy. Conclusions: Machine Learning algorithms seem to contribute to the prediction of postoperative complications and the course of disease after upper gastrointestinal surgery for malignancies. However, due to the retrospective character of ML studies, these results require trials or prospective studies to validate this application of ML. [ABSTRACT FROM AUTHOR]

Persons with diabetes mellitus may have an increased risk of severe illness or death from COVID-19 compared to persons without diabetes. Prior studies indicate that immune response and thus vaccine effectiveness might be lower in persons with diabetes. We aimed to systematically review the effectiveness of COVID-19 vaccines in adults with diabetes. Pubmed, Embase, Web of Science and Cochrane Library were searched for studies that evaluated the effectiveness of COVID-19 vaccines in adults with diabetes, published before 4 March 2022. Risk of bias in the included studies was evaluated using the ROBINS-I tool. At least two reviewers conducted the study selection, data extraction, and risk of bias assessment independently. After screening of 2196 studies, a total of 17 articles were included. Six different COVID-19 vaccines (Ad5-nCoV-S, AZD1222, BNT162b2, CoronaVac, JNJ-78436735, and mRNA-1273) were included in the synthesis. Vaccine effectiveness was reported for SARS-CoV-2 infection, symptomatic COVID-19, hospitalization, and death, and ranged from 24 to 96% in persons with diabetes, and from 33 to 97% in total study populations; effectiveness was generally lower for persons with diabetes. Odds ratios for breakthrough infection or severe COVID-19 ranged from 1.03 to 2.41 in vaccinated persons with diabetes compared to persons without diabetes. Even though the included studies were very heterogeneous, results from the synthesis indicate that effectiveness of COVID-19 vaccines might be lower in persons with diabetes. More research is needed on the comparison of vaccine effectiveness between persons with and without diabetes, and the effectiveness of repeat COVID-19 vaccinations. [ABSTRACT FROM AUTHOR]

Background: Machine learning (ML) has been introduced in various fields of healthcare. In colorectal surgery, the role of ML has yet to be reported. In this systematic review, an overview of machine learning models predicting surgical outcomes after colorectal surgery is provided. Methods: Databases PubMed, EMBASE, Cochrane, and Web of Science were searched for studies using machine learning models for patients undergoing colorectal surgery. To be eligible for inclusion, studies needed to apply machine learning models for patients undergoing colorectal surgery. Absence of machine learning or colorectal surgery or studies reporting on reviews, children, study abstracts were excluded. The Probast risk of bias tool was used to evaluate the methodological quality of machine learning models. Results: A total of 1821 studies were analysed, resulting in the inclusion of 31 articles. A vast proportion of ML algorithms have been used to predict the course of disease and response to neoadjuvant chemoradiotherapy. Radiomics have been applied most frequently, along with predictive accuracies up to 91%. However, most studies included a retrospective study design without external validation or calibration. Conclusions: Machine learning models have shown promising potential in predicting surgical outcomes after colorectal surgery. However, large-scale data is warranted to bridge the gap between calibration and external validation. Clinical implementation is needed to demonstrate the contribution of ML within daily practice. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is the most common malignancy in men of middle and older age. The standard treatment strategy for PCa ranges from active surveillance in low-grade, localized PCa to radical prostatectomy, external beam radiation therapy, hormonal treatment and chemotherapy. Recently, the use of prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) for metastatic castration-resistant PCa has been approved. PSMA is predominantly, but not exclusively, expressed on PCa cells. Because of its high expression in PCa, PSMA is a promising target for diagnostics and therapy. To understand the currently used RLT, knowledge about pharmacokinetics (PK) and pharmacodynamics (PD) of the PSMA ligand and the PSMA protein itself is crucial. PK and PD properties of the ligand and its target determine the duration and extent of the effect. Knowledge on the concentration–time profile, the target affinity and target abundance may help to predict the effect of RLT. Increased specific binding of radioligands to PSMA on PCa cells may be associated with better treatment response, where nonspecific binding may increase the risk of toxicity in healthy organs. Optimization of the radioligand, as well as synergistic effects of concomitant agents and an improved dosing strategy, may lead to more individualized treatment and better overall survival. [ABSTRACT FROM AUTHOR]

Simple Summary: Patients with HER2-positive metastatic breast cancer develop brain metastases in up to 30% of cases. The aim of this systematic review and meta-analysis was to determine the effect of different systemic therapies in patients with HER2-positive metastatic breast cancer and brain metastases, acknowledging the heterogeneity and sometimes low quality of 51 included studies. Tucatinib (combined with trastuzumab and capecitabine) and trastuzumab-deruxtecan appear to constitute the most effective systemic therapy, while pyrotinib might be an option in Asian patients. Preferably, future research will comprise of randomized controlled trials, including patients with active and/or inactive brain metastases. Aim: Patients with HER2-positive (HER2+) metastatic breast cancer (mBC) develop brain metastases (BM) in up to 30% of cases. Treatment of patients with BM can consist of local treatment (surgery and/or radiotherapy) and/or systemic treatment. We undertook a systematic review and meta-analysis to determine the effect of different systemic therapies in patients with HER2+ mBC and BM. Methods: A systematic search was performed in the databases PubMed, Embase.com, Clarivate Analytics/Web of Science Core Collection and the Wiley/Cochrane Library. Eligible articles included prospective or retrospective studies reporting on the effect of systemic therapy on objective response rate (ORR) and/or median progression free survival (mPFS) in patients with HER2+ mBC and BM. The timeframe within the databases was from inception to 19 January 2022. Fixed-effects meta-analyses were used. Quality appraisal was performed using the ROBINS-I tool. Results: Fifty-one studies were included, involving 3118 patients. Most studies, which contained the largest patient numbers, but also often carried a moderate-serious risk of bias, investigated lapatinib and capecitabine (LC), trastuzumab-emtansine (T-DM1) or pyrotinib. The best quality data and/or highest ORR were described with tucatinib (combined with trastuzumab and capecitabine, TTC) and trastuzumab-deruxtecan (T-DXd). TTC demonstrated an ORR of 47.3% in patients with asymptomatic and/or active BM. T-DXd achieved a pooled ORR of 64% (95% CI 43–85%, I2 0%) in a heavily pretreated population with asymptomatic BM (3 studies, n = 96). Conclusions: Though our meta-analysis should be interpreted with caution due to the heterogeneity of included studies and a related serious risk of bias, this review provides a comprehensive overview of all currently available systemic treatment options. T-Dxd and TTC that appear to constitute the most effective systemic therapy in patients with HER2+ mBC and BM, while pyrotinib might be an option in Asian patients. [ABSTRACT FROM AUTHOR]

Objective: The objective of the review was to identify, appraise, and synthesise qualitative studies on the lived experience of individuals diagnosed with leprosy, the impact of the disease, and how they coped with the disease burden. Introduction: Leprosy is a chronic disease with long-term biopsychosocial impact and is a leading cause of preventable disabilities. It traps the individuals with leprosy in a vicious circle of disease, stigma, and poverty. The efforts to reduce stigma and discrimination and improve their quality of life have not kept pace with the success of the multidrug treatment. Inclusion criteria: This review considered published literature on the lived experience of individuals diagnosed with leprosy. There were no limitations on gender, background, or country. All qualitative or mixed-methods studies were accepted. Methods: The review followed the JBI meta-aggregation approach for qualitative systematic reviews. A structured literature search was undertaken using multiple electronic databases: PubMed, Embase, Web of Science, and CINAHL. Results: The search identified 723 publications, and there were 446 articles after deduplication. Forty-nine studies met the inclusion criteria. The final 173 findings were synthesised into ten categories and aggregated into four synthesised findings: biophysical impact, social impact, economic impact, and mental and emotional impact. These synthesised findings were consistent across the included studies from a patient's perspective. The way people coped with leprosy depended on their interpretation of the disease and its treatment. It affected their help-seeking behaviour and their adherence to treatment and self-care. The review has identified a multi-domain effect on the affected individuals, which goes beyond the biological and physical effects, looking at the social issues, specific difficulties, emotions, and economic hardships. Conclusions: The researchers, health professionals, and policymakers could use the synthesised findings to address the concerns and needs of the leprosy-affected individuals and offer appropriate support to manage their lives. Systematic review registration number: PROSPERO Registration number: CRD42021243223 Author summary: Leprosy is a chronic, granulomatous disease caused by Mycobacterium leprae and is a major cause of preventable disability. As a result of their disfigurements and deteriorating physical impairments, the leprosy-affected individuals experienced negative social attitudes, stigma, isolation, and discrimination, thus, impacting their lives and relationships with others. Due to the chronicity of leprosy, studying the lived experience of the affected individuals will allow us a deeper understanding of the effects of the disease, how they seek help and adhere to its treatment, and cope with the disease. We conducted a systematic literature review involving 49 articles, highlighting the four synthesised findings: biophysical impact, social impact, economic impact, and mental and emotional impact. These synthesised findings were not new, but they were consistent across the included studies from a patient's perspective. Our findings contributed to establishing the biopsychosocial and economic approach for understanding what leprosy-affected people experience by considering changes in their biophysical, sociocultural, psychological dynamics, and economics. It served as a guide for delivering care and treatment to these people. The information will be helpful to the researchers, health professionals, decision, and policymakers to plan and tailor their support for these individuals, their families, and the community. [ABSTRACT FROM AUTHOR]

Background: Machine learning (ML) has been successful in several fields of healthcare, however the use of ML within bariatric surgery seems to be limited. In this systematic review, an overview of ML applications within bariatric surgery is provided. Methods: The databases PubMed, EMBASE, Cochrane, and Web of Science were searched for articles describing ML in bariatric surgery. The Cochrane risk of bias tool and the PROBAST tool were used to evaluate the methodological quality of included studies. Results: The majority of applied ML algorithms predicted postoperative complications and weight loss with accuracies up to 98%. Conclusions: In conclusion, ML algorithms have shown promising capabilities in the prediction of surgical outcomes after bariatric surgery. Nevertheless, the clinical introduction of ML is dependent upon the external validation of ML. [ABSTRACT FROM AUTHOR]

Background: Massive perivillous fibrin deposition (MPFD) is associated with adverse pregnancy outcomes and is mainly caused by maternal factors with limited involvement of fetal or genetic causes. We present one consanguineous couple with six fetuses developing Fetal Akinesia Deformation Sequence (FADS) and MPFD, with a possible underlying genetic cause. This prompted a literature review on prevalence of FADS and MPFD. Methods: Fetal ultrasound examination, motor assessment, genetic testing, postmortem examination, and placenta histology are presented (2009–2019). Literature was reviewed for the association between congenital anomalies and MPFD. Results: All six fetuses developed normally during the first trimester. Thereafter, growth restriction, persistent flexed position, abnormal motility, and contractures in 4/6, consistent with FADS occurred. All placentas showed histologically confirmed MPFD. Genetic analyses in the five available cases showed homozygosity for two variants of unknown significance in two genes, VARS1 (OMIM*192150) and ABCF1 (OMIM*603429). Both parents are heterozygous for these variants. From 63/1999 manuscripts, 403 fetal outcomes were mobilized. In 14/403 fetuses, congenital abnormalities in association with MPFD were seen of which two fetuses with contractures/FADS facial anomalies. Conclusion: The low prevalence of fetal contractures/FADS facial anomalies in association with MPFD in the literature review supports the possible fetal or genetic contribution causing FADS and MPFD in our family. This study with literature review supports the finding that fetal, fetoplacental, and/or genetic components may play a role in causing a part of MPFDs. [ABSTRACT FROM AUTHOR]

High rates of oxidative stress are common in preterm born infants and have short- and long-term consequences. The antioxidant properties of human milk limits the consequences of excessive oxidative damage. However, as the mother's own milk it is not always available, donor milk may be provided as the best alternative. Donor milk needs to be pasteurized before use to ensure safety. Although pasteurization is necessary for safety reasons, it may affect the activity and concentration of several biological factors, including antioxidants. This literature review describes the effect of different pasteurization methods on antioxidant properties of human milk and aims to provide evidence to guide donor milk banks in choosing the best pasteurization method from an antioxidant perspective. The current literature suggests that Holder pasteurization reduces the antioxidant properties of human milk. Alternative pasteurization methods seem promising as less reduction is observed in several studies. [ABSTRACT FROM AUTHOR]