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Briefings in Bioinformatics Jan 2024Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients...
Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.
Topics: Humans; Neoplasms, Unknown Primary; Precision Medicine; Gene Expression Profiling; Microarray Analysis
PubMed: 38343328
DOI: 10.1093/bib/bbae028 -
BMC Medicine Feb 2024A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external...
BACKGROUND
A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, describe, and appraise AI-Ms of CVD prediction in the general and special populations and develop a new independent validation score (IVS) for AI-Ms replicability evaluation.
METHODS
PubMed, Web of Science, Embase, and IEEE library were searched up to July 2021. Data extraction and analysis were performed for the populations, distribution, predictors, algorithms, etc. The risk of bias was evaluated with the prediction risk of bias assessment tool (PROBAST). Subsequently, we designed IVS for model replicability evaluation with five steps in five items, including transparency of algorithms, performance of models, feasibility of reproduction, risk of reproduction, and clinical implication, respectively. The review is registered in PROSPERO (No. CRD42021271789).
RESULTS
In 20,887 screened references, 79 articles (82.5% in 2017-2021) were included, which contained 114 datasets (67 in Europe and North America, but 0 in Africa). We identified 486 AI-Ms, of which the majority were in development (n = 380), but none of them had undergone independent external validation. A total of 66 idiographic algorithms were found; however, 36.4% were used only once and only 39.4% over three times. A large number of different predictors (range 5-52,000, median 21) and large-span sample size (range 80-3,660,000, median 4466) were observed. All models were at high risk of bias according to PROBAST, primarily due to the incorrect use of statistical methods. IVS analysis confirmed only 10 models as "recommended"; however, 281 and 187 were "not recommended" and "warning," respectively.
CONCLUSION
AI has led the digital revolution in the field of CVD prediction, but is still in the early stage of development as the defects of research design, report, and evaluation systems. The IVS we developed may contribute to independent external validation and the development of this field.
Topics: Humans; Artificial Intelligence; Cardiovascular Diseases; Algorithms; Africa; Europe
PubMed: 38317226
DOI: 10.1186/s12916-024-03273-7 -
Asian Journal of Urology Jan 2024Transurethral resection of bladder tumor is one of the most common everyday urological procedures. This kind of surgery demands a set of skills that need training and... (Review)
Review
OBJECTIVE
Transurethral resection of bladder tumor is one of the most common everyday urological procedures. This kind of surgery demands a set of skills that need training and experience. In this review, we aimed to investigate the current literature to find out if simulators, phantoms, and other training models could be used as a tool for teaching urologists.
METHODS
A systematic review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement and the recommendations of the European Association of Urology guidelines for conducting systematic reviews. Fifteen out of 932 studies met our inclusion criteria and are presented in the current review.
RESULTS
The UroTrainer (Karl Storz GmbH, Tuttlingen, Germany), a virtual reality training simulator, achieved positive feedback and an excellent face and construct validity by the participants. The inspection of bladder mucosa, blood loss, tumor resection, and procedural time was improved after the training, especially for inexperienced urologists and medical students. The construct validity of UroSim® (VirtaMed, Zurich, Switzerland) was established. SIMBLA simulator (Samed GmbH, Dresden, Germany) was found to be a realistic and useful tool by experts and urologists with intermediate experience. The test objective competency model based on SIMBLA simulator could be used for evaluating urologists. The porcine model of the Asian Urological Surgery Training and Education Group also received positive feedback by the participants that tried it. The Simulation and Technology Enhanced Learning Initiative Project had an extraordinary face and content validity, and 60% of participants would like to use the simulators in the future. The 5-day multimodal training curriculum "Boot Camp" in the United Kingdom achieved an increase of the level of confidence of the participants that lasted months after the project.
CONCLUSION
Simulators and courses or curricula based on a simulator training could be a valuable learning tool for any surgeon, and there is no doubt that they should be a part of every urologist's technical education.
PubMed: 38312823
DOI: 10.1016/j.ajur.2022.08.005 -
PLOS Global Public Health 2024Hearing loss is an important global public health issue which can be alleviated through treatment with hearing aids. However, most people who would benefit from hearing...
Hearing loss is an important global public health issue which can be alleviated through treatment with hearing aids. However, most people who would benefit from hearing aids do not receive them, in part due to challenges in accessing hearing aids and related services, which are most salient in low- and middle-income countries (LMIC) and other resource-limited settings. Innovative approaches for hearing aid service delivery can overcome many of the challenges related to access, including that of limited human resources trained to provide ear and hearing care. The purpose of this systematic scoping review is to synthesize evidence on service delivery approaches for hearing aid provision in LMIC and resource-limited settings. We searched 3 databases (PubMed, Scopus, Ovid MEDLINE) for peer-reviewed articles from 2000 to 2022 that focused on service delivery approaches related to hearing aids in LMIC or resource-limited settings. Fifteen peer-reviewed articles were included, which described hospital-based (3 studies), large-scale donation program (1 studies), community-based (7 studies), and remote (telehealth; 4 studies) service delivery approaches. Key findings are that hearing aid services can be successfully delivered in hospital- and community-based settings, and remotely, and that both qualified hearing care providers and trained non-specialists can provide quality hearing aid services. Service delivery approaches focused on community-based and remote care, and task sharing among qualified hearing care providers and trained non-specialists can likely improve access to hearing aids worldwide, thereby reducing the burden of untreated hearing loss.
PubMed: 38266001
DOI: 10.1371/journal.pgph.0002823 -
Spine Deformity May 2024The purpose of this review was to evaluate the effectiveness of patient-specific rods for adult spinal deformity. (Review)
Review
PURPOSE
The purpose of this review was to evaluate the effectiveness of patient-specific rods for adult spinal deformity.
METHODS
A systematic review of the literature was performed through an electronic search of the PubMed, Scopus, and Web of Science databases. Human studies between 2012 and 2023 were included. Sample size, sagittal vertical axis (SVA), pelvic incidence-lumbar lordosis (PI-LL), pelvic tilt (PT), operation time, blood loss, follow-up duration, and complications were recorded for each study when available.
RESULTS
Seven studies with a total of 304 adult spinal deformity patients of various etiologies were included. All studies reported SVA, and PT; two studies did not report PI-LL. Four studies reported planned radiographic outcomes. Two found a significant association between preoperative plan and postoperative outcome in all three outcomes. One found a significant association for PI-LL alone. The fourth found no significant associations. SVA improved in six of seven studies, PI-LL improved in all five, and three of seven studies found improved postoperative PT. Significance of these results varied greatly by study.
CONCLUSION
Preliminary evidence suggests potential benefits of PSRs in achieving optimal spino-pelvic parameters in ASD surgery. Nevertheless, conclusions regarding the superiority of PSRs over traditional rods must be judiciously drawn, given the heterogeneity of patients and study methodologies, potential confounding variables, and the absence of robust randomized controlled trials. Future investigations should concentrate on enhancing preoperative planning, standardizing surgical methodologies, isolating specific patient subgroups, and head-to-head comparisons with traditional rods to fully elucidate the impact of PSRs in ASD surgery.
Topics: Humans; Adult; Lordosis; Treatment Outcome; Spinal Curvatures; Spine; Spinal Fusion
PubMed: 38265734
DOI: 10.1007/s43390-023-00805-8 -
Frontiers in Public Health 2023Family socioeconomic status (SES) is widely believed to be associated with depressive symptoms in children and adolescents. The correlation between SES and depressive... (Meta-Analysis)
Meta-Analysis
Family socioeconomic status (SES) is widely believed to be associated with depressive symptoms in children and adolescents. The correlation between SES and depressive symptoms changes based on social culture and the economic development level. In China, which includes many children and adolescents, the magnitude of the relationship between SES and depressive symptoms and its potential moderators remains unclear. The current meta-analysis was conducted to determine the overall association between SES and depressive symptoms in children and adolescents in mainland China. We included 197 estimates in mainland China from 2000-2023. Among 147,613 children and adolescents aged 7-18 years, the results showed a weak but significant overall negative association between SES and depression ( = -0.076). Moderator testing showed that the composite SES indicator ( = -0.104) had a stronger association with depression than parental educational level ( = -0.065) and occupational status ( = -0.025) but not family income ( = -0.088). Additionally, the negative association between SES and depression became weaker over the past 20 years in China ( = 0.010). Furthermore, the magnitude of the relationship between SES and depression was stronger in West China ( = -0.094) than in Middle China ( = -0.065), but not East China ( = -0.075). These findings indicate that the relationship between SES and depression among children and adolescents in mainland China may vary based on social contexts. It is necessary to further explore the effect of these social factors and the underlying mechanisms.
Topics: Child; Humans; Adolescent; Depression; Social Class; China; Economic Development; Educational Status
PubMed: 38264252
DOI: 10.3389/fpubh.2023.1292411 -
The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.Journal of Medical Internet Research Jan 2024Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns are growing about the... (Review)
Review
BACKGROUND
Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns are growing about the transparency, replicability, biasedness, and overall validity of artificial intelligence studies in medicine.
OBJECTIVE
We aimed to systematically review the reporting quality of machine learning (ML) studies of pediatric DM using the Minimum Information About Clinical Artificial Intelligence Modelling (MI-CLAIM) checklist, a general reporting guideline for medical artificial intelligence studies.
METHODS
We searched the PubMed and Web of Science databases from 2016 to 2020. Studies were included if the use of ML was reported in children with DM aged 2 to 18 years, including studies on complications, screening studies, and in silico samples. In studies following the ML workflow of training, validation, and testing of results, reporting quality was assessed via MI-CLAIM by consensus judgments of independent reviewer pairs. Positive answers to the 17 binary items regarding sufficient reporting were qualitatively summarized and counted as a proxy measure of reporting quality. The synthesis of results included testing the association of reporting quality with publication and data type, participants (human or in silico), research goals, level of code sharing, and the scientific field of publication (medical or engineering), as well as with expert judgments of clinical impact and reproducibility.
RESULTS
After screening 1043 records, 28 studies were included. The sample size of the training cohort ranged from 5 to 561. Six studies featured only in silico patients. The reporting quality was low, with great variation among the 21 studies assessed using MI-CLAIM. The number of items with sufficient reporting ranged from 4 to 12 (mean 7.43, SD 2.62). The items on research questions and data characterization were reported adequately most often, whereas items on patient characteristics and model examination were reported adequately least often. The representativeness of the training and test cohorts to real-world settings and the adequacy of model performance evaluation were the most difficult to judge. Reporting quality improved over time (r=0.50; P=.02); it was higher than average in prognostic biomarker and risk factor studies (P=.04) and lower in noninvasive hypoglycemia detection studies (P=.006), higher in studies published in medical versus engineering journals (P=.004), and higher in studies sharing any code of the ML pipeline versus not sharing (P=.003). The association between expert judgments and MI-CLAIM ratings was not significant.
CONCLUSIONS
The reporting quality of ML studies in the pediatric population with DM was generally low. Important details for clinicians, such as patient characteristics; comparison with the state-of-the-art solution; and model examination for valid, unbiased, and robust results, were often the weak points of reporting. To assess their clinical utility, the reporting standards of ML studies must evolve, and algorithms for this challenging population must become more transparent and replicable.
Topics: Humans; Child; Artificial Intelligence; Reproducibility of Results; Machine Learning; Diabetes Mellitus; Checklist
PubMed: 38241075
DOI: 10.2196/47430 -
The Lancet. Microbe Feb 2024Clinical bedaquiline resistance predominantly involves mutations in mmpR5 (Rv0678). However, mmpR5 resistance-associated variants (RAVs) have a variable relationship... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Clinical bedaquiline resistance predominantly involves mutations in mmpR5 (Rv0678). However, mmpR5 resistance-associated variants (RAVs) have a variable relationship with phenotypic Mycobacterium tuberculosis resistance. We did a systematic review to assess the maximal sensitivity of sequencing bedaquiline resistance-associated genes and evaluate the association between RAVs and phenotypic resistance, using traditional and machine-based learning techniques.
METHODS
We screened public databases for articles published from database inception until Oct 31, 2022. Eligible studies performed sequencing of at least mmpR5 and atpE on clinically sourced M tuberculosis isolates and measured bedaquiline minimum inhibitory concentrations (MICs). A bias risk scoring tool was used to identify bias. Individual genetic mutations and corresponding MICs were aggregated, and odds ratios calculated to determine association of mutations with resistance. Machine-based learning methods were used to define test characteristics of parsimonious sets of diagnostic RAVs, and mmpR5 mutations were mapped to the protein structure to highlight mechanisms of resistance. This study was registered in the PROSPERO database (CRD42022346547).
FINDINGS
18 eligible studies were identified, comprising 975 M tuberculosis isolates containing at least one potential RAV (mutation in mmpR5, atpE, atpB, or pepQ), with 201 (20·6%) showing phenotypic bedaquiline resistance. 84 (29·5%) of 285 resistant isolates had no candidate gene mutation. Sensitivity and positive predictive value of taking an any mutation approach was 69% and 14%, respectively. 13 mutations, all in mmpR5, had a significant association with a resistant MIC (adjusted p<0·05). Gradient-boosted machine classifier models for predicting intermediate or resistant and resistant phenotypes both had receiver operator characteristic c statistic of 0·73 (95% CI 0·70-0·76). Frameshift mutations clustered in the α1 helix DNA-binding domain, and substitutions in the α2 and α3 helix hinge region and in the α4 helix-binding domain.
INTERPRETATION
Sequencing candidate genes is insufficiently sensitive to diagnose clinical bedaquiline resistance, but where identified, some mutations should be assumed to be associated with resistance. Genomic tools are most likely to be effective in combination with rapid phenotypic diagnostics. This study was limited by selective sampling in contributing studies and only considering single genetic loci as causative of resistance.
FUNDING
Francis Crick Institute and National Institute of Allergy and Infectious Diseases at the National Institutes of Health.
Topics: United States; Humans; Antitubercular Agents; Diarylquinolines; Tuberculosis; Mycobacterium tuberculosis; Genomics
PubMed: 38215766
DOI: 10.1016/S2666-5247(23)00317-8 -
The Science of the Total Environment Feb 2024Secondhand smoke (SHS) exposure was harmful for brain development. However, the association between SHS exposure and NDDs diagnosis were unclear. (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Secondhand smoke (SHS) exposure was harmful for brain development. However, the association between SHS exposure and NDDs diagnosis were unclear.
OBJECTIVES
To evaluate associations between SHS exposure and NDDs diagnosis, identify critical time windows, and summarize the strength of evidence.
METHODS
To investigate the associations of SHS exposure and the development of NDDs, we searched Ovid, EMBASE, Web of Science, Cochrane Library, and PubMed for all the relevant studies up to 31 March 2023. The risk estimates and standardized mean differences (SMD) for the individuals with any NDDs who were exposed to SHS exposure compared with those unexposed or low-exposed.
RESULTS
The results showed that a total of 31,098 citations were identified, of which 54 studies were included. We identified significant associations between SHS exposure and the risks of NDDs including specific types of NDDs like attention deficit hyperactivity disorder (ADHD) and learning disabilities (LD) despite the observed heterogeneity for NDDs and ADHD. We also observed a significant association between cotinine exposure and ADHD. However, inconsistent ratings between the two quality-of-evidence methods for all the meta-analyses indicated the current evidence of the associations and the potential exposure window remained inconclusive.
DISCUSSION
Our findings suggested that SHS exposure was associated with a higher risk of developing ADHD and LD, with inconclusive quality-of-evidence. In addition, period-specific associations remained unclear based on current evidence.
Topics: Humans; Tobacco Smoke Pollution; Attention Deficit Disorder with Hyperactivity; Cotinine; Risk Factors
PubMed: 38159763
DOI: 10.1016/j.scitotenv.2023.169649 -
Research in Sports Medicine (Print) Dec 2023This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning... (Review)
Review
This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning (ML) approaches. Studies were included if: (1) participants were male professional soccer players; (2) carried out for at least 2 sessions, exercises, or competitions; (3) correlated training load (TL) with non-contact injuries; (4) applied ML approaches to predict TL and non-contact injuries. TL included: IL indicators (Rating of Perceived Exertion, RPE; Session-RPE, Heart Rate, HR) and EL indicators (Global Positioning System, GPS variables); the relationship between EL and IL through index, ratio, formula; ML indicators included performance measures, predictive performance of ML methods, measure of feature importance, relevant predictors, outcome variable, predictor variable, data pre-processing, features selection, ML methods. Twenty-five studies were included. Eleven addressed the relationship between EL and IL. Five used EL/IL indexes. Five studies predicted IL indicators. Three studies investigated the association between EL and IL with IR. One study predicted IR using ML. Significant positive correlations were found between S-RPE and total distance (TD) ( = 0.73; 95% CI (0.64 to 0.82)) as well as between S-RPE and player load (PL) ( = 0.76; 95% CI (0.68 to 0.84)). Association between IL and EL and their relationship with injuries were found. RPE, S-RPE, and HR were associated with different EL indicators. A positive relationship between EL and IL indicators and IR was also observed. Moreover, new indexes or ratios (integrating EL and IL) to improve knowledge regarding TL and fitness status were also applied. ML can predict IL indicators (HR and RPE), and IR. The present systematic review was registered in PROSPERO (CRD42021245312).
PubMed: 38146925
DOI: 10.1080/15438627.2023.2297190