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CanDo (Canadian Donor Milk) randomised controlled trial: pasteurised human donor milk supplementation in the well-baby unit - protocol.

INTRODUCTION: Mother's milk is the gold standard for feeding newborns. Despite lactation support while in hospital, supplementation rates remain high in Canadian well-baby units at 35-50%. When supplementation is needed, the choice between formula milk and pasteurised human donor milk (donor milk) remains uncertain with a lack of clinical trials to inform this practice. This study aims to compare the effect of supplementing mother's milk with donor milk versus formula in infants at higher risk for supplementation (infants of diabetic mothers, infants born small for gestational age or with a birth weight less than 2.5 kg and late preterm infants born between 350/7 and 366/7 weeks gestation). METHODS AND ANALYSIS: This is an ongoing, open-label, single-centre, randomised controlled trial conducted at Mount Sinai Hospital, Toronto, Canada. A total of 112 infants (56 per group) will be randomised to receive donor milk or infant formula as a supplement to mother's milk during their initial hospital stay, when supplementation is deemed necessary by the family and/or healthcare team. The primary outcome is exclusive human milk feeding at 4 months of age. Secondary outcomes include any or exclusive human milk feeding at 1, 2 and 3 months; infant growth and health indicators and breastfeeding self-efficacy. Exploratory outcomes encompass infant temperament; parental mental health (assessed using the State-Trait Anxiety Inventory and Edinburgh Postnatal Depression Scale); milk cortisol concentrations; and informal milk sharing comparing donor milk and formula supplementation. Follow-up includes monthly telephone assessments and a virtual or in-person visit at 4 months post partum. Data will be analysed using intention-to-treat principles. ETHICS AND DISSEMINATION: The CanDo trial has received ethics approval from the Mount Sinai Hospital Research Ethics Board and the University of Toronto. Results will be disseminated through peer-reviewed journals, conference presentations and stakeholder engagement with hospital and public health decision-makers. Findings will address a critical evidence gap regarding the use of donor milk supplementation in well-baby units and may inform future clinical practice and policy in newborn feeding. TRIAL REGISTRATION NUMBER: NCT06315127.

Humans

Incidence and risk factors for malignancy in patients with incidental solitary pulmonary nodules: a systematic review and meta-analysis.

BACKGROUND: The increasing use of chest imaging has led to a higher detection rate of incidental solitary pulmonary nodules (SPNs), often causing patient anxiety. Determining the malignancy rate and associated risk factors is crucial for developing appropriate follow-up strategies to prevent overdiagnosis, overtreatment, or missed diagnoses. This meta-analysis aims to investigate the malignancy rate and risk factors in patients with incidental SPNs. METHODS: A systematic search of PubMed, Embase, Web of Science, and the Cochrane Library was conducted up to June 30, 2025. Data on malignancy rates and potential risk factors were extracted from eligible studies. All pooled analyses were performed using a random-effects model. RESULTS: Fifty-four studies involving 19,985 patients were included. The pooled malignancy rate for incidental SPNs was 56.7% (95% CI: 51.5-62.0), with significant between-study heterogeneity (I2 = 98.5%, p&#x2009;<&#x2009;0.001). The pooled effect size showed a minimal change after adjustment for potential publication bias using the non-parametric Trim-and-Fill method (54.7%; 95%CI: 50.9-58.8). Risk factor analysis identified that older age, history of cancer, cigarette smoker, larger nodule diameter, spiculation, upper lobe location, lobulation, pleural indentation, vascular convergence, solid nodules, family history of cancer, and irregular or ill-defined margins were significantly associated with an increased risk of malignancy. Conversely, male sex, presence of calcification, and clear borders were significantly associated with a reduced risk of malignancy. CONCLUSION: This meta-analysis provides a comprehensive assessment of malignancy rates and risk factors in incidental SPNs. The high pooled malignancy rate should be interpreted considering the significant heterogeneity and the inclusion of a high proportion of retrospective studies and populations from high-risk regions. Nonetheless, these findings offer essential evidence for clinical risk stratification, supporting optimized follow-up and informed decision-making.

Humans

Assessing time to symptomatic progression, a patient-relevant efficacy endpoint, in the MARIPOSA study in non-small cell lung cancer.

INTRODUCTION: In the phase 3 randomized MARIPOSA study, amivantamab and lazertinib combination therapy demonstrated improved progression-free survival (PFS) and overall survival (OS) versus osimertinib in participants with previously untreated, epidermal growth factor receptor-mutated advanced non-small cell lung cancer. Time to symptomatic progression (TTSP) was introduced to assess clinical worsening and complement endpoints that investigate radiographic disease progression and patient-reported outcomes. TTSP provides an easily interpretable measure of disease-specific symptom worsening to further support patient experience. METHODS: In MARIPOSA, TTSP was quantitatively assessed as a secondary efficacy endpoint and defined as the time from randomization until participants experience disease-specific symptom worsening requiring a clinical intervention or treatment change, or death. To evaluate the impact of amivantamab and lazertinib on TTSP considering its established OS benefit against osimertinib, an exploratory analysis censoring death events was performed. RESULTS: At the final protocol-specified OS analysis (median follow up: 37.8 months), median TTSP was 43.6 months with amivantamab and lazertinib versus 29.3 months with osimertinib (hazard ratio [HR]: 0.69; 95% confidence interval [CI]: 0.57-0.83; p&#x202f;<&#x202f;0.0001). Amivantamab and lazertinib reduced deaths following a TTSP event compared to osimertinib. A strong correlation between TTSP and PFS or OS was observed. CONCLUSIONS: Amivantamab and lazertinib significantly delayed TTSP versus osimertinib. TTSP offers a clinician-validated measurement of disease-specific symptom worsening, capturing symptoms perceived by patients that prompt clinical action. TTSP is highly correlated with PFS and OS, providing complementary insights alongside traditional endpoints. TTSP enhances understanding of treatment benefit and supports informed clinical decision-making by integrating patient experience.

Humans

Misalignment between ultra-processed status and 'better for you' claims on premix alcohol products.

BACKGROUND: Premix alcohol products (also known as ready-to-drink beverages) are a rapidly expanding alcohol category and frequently marketed using 'better for you' claims (e.g., 'Low sugar', 'Natural'). Little is known about the extent to which these products are ultra-processed or whether marketing claims align with ultra-processed status. This study aimed to address this evidence gap by auditing ingredient disclosure on premix products, assessing the ultra-processed status of these products, and determining the prevalence of 'better for you' claims with a particular focus on claims relating to ultra-processed status. METHODS: 534 premix alcohol products sold in major Australian retail outlets were assessed. Products were evaluated for compliance with mandatory ingredient disclosure, classified according to ultra-processed status based on the presence of indicators of ultra-processing (additives and other industrial ingredients), and analysed to determine the prevalence and types of 'better for you' marketing claims. RESULTS: Only 79% of assessed products displayed an ingredients list. Among compliant products, 98% contained at least one additive or ingredient indicative of ultra-processing, most commonly flavours, carbonating agents, colours, and sweeteners. One-third (33%) of products containing an ultra-processing indicator displayed a claim suggesting naturalness or minimal processing. Substantially higher proportions of ultra-processed products than non-ultra-processed products carried health-related claims. DISCUSSION AND CONCLUSIONS: Premix beverages available in Australia are overwhelmingly ultra-processed, yet many are marketed in ways that may mislead consumers about their composition and healthfulness. Stronger regulatory oversight of ingredient disclosure and marketing claims in this sector is urgently needed to support informed consumer decision-making.

Alcoholic Beverages

Use of Wearable Sensors in Angelman Syndrome: A Systematic Review.

BACKGROUND: Wearable sensors are a promising method for collecting clinical trial outcome data for people with Angelman syndrome (AS). However, there has yet to be a systematic probe into the ways in which wearable sensors have been successfully used in AS. The current study aims to provide a quantitative summary of wearable sensors used in AS, including contexts of use and psychometric properties, and to present key narrative highlights. METHOD: Literature searches were performed in three electronic databases: APA PsycInfo, PubMed and Web of Science Core Collection. Data items were categorized into four categories: sample characteristics, study methodological details, wearable sensor characteristics and psychometric properties assessed. Sample characteristics included sample size, age, biological sex, race/ethnicity and cognitive/developmental functioning. Study methodological details were subdivided into study design and setting. Wearable sensor characteristics included sensor type, placement site, means of attachment, assessed construct and sensor-related data loss. Psychometric properties assessed included reliability and validity of sensor-derived data. RESULTS: We identified 16 articles through our systematic review. Wearable sensors were used to study sleep (n&#x2009;=&#x2009;10, 62.5%), language (n&#x2009;=&#x2009;2, 12.5%), gait (n&#x2009;=&#x2009;2, 12.5%), caregiver proximity (n&#x2009;=&#x2009;1, 6.3%), EEG power (n = 1, 6.3%),&#xa0;and arousal (n&#x2009;=&#x2009;1, 6.3%) in AS through actigraphs, vocalization recorders, inertial sensors, radio-frequency identification watches, wireless EEG caps,&#xa0;and functional near-infrared spectroscopy caps, respectively. Findings from these studies broadly indicate that wearable sensors are feasible, reliable and valid for assessing a range of behaviours relevant to AS. CONCLUSIONS: Wearable sensors are a promising solution to enhance assessments in AS. However, with the small extant literature characterized by small sample sizes and restricted focus on a few relevant features in AS, there remains ample opportunities to explore the use of wearable sensors in people with AS. Additional studies will better inform clinical decision-making and ultimately improve the lives of people with AS and their families.

Humans

A Dynamic Nomogram to Predict Metabolic Dysfunction-Associated Fatty Liver Disease in Patients with Metabolic Syndrome.

BACKGROUND: Metabolic syndrome (MetS) involves multiple metabolic disorders. This study aimed to identify high-risk populations for metabolic dysfunction-associated fatty liver disease (MAFLD) in patients with MetS and to establish a dynamic predictive nomogram. METHODS: A total of 627 patients with MetS from six regions in Zhejiang Province were enrolled and categorized into MAFLD and non-MAFLD groups, then randomly assigned to training and validation sets at a ratio of 7:3. Independent predictors of MAFLD were identified using least absolute shrinkage and selection operator regression and multivariable logistic regression analyses. These predictors were then used to construct a dynamic nomogram. RESULTS: A total of 627 patients with MetS were included in the final analysis, of whom 77.0% (483/627) were diagnosed with MAFLD. Multivariable logistic regression analysis identified body mass index (BMI), waist circumference (WC), total cholesterol (TC), alanine aminotransferase (ALT), MetS-defined dysglycemia, and education level as independent risk factors for MAFLD. MetS-defined dysglycemia showed the highest odds ratio (OR) for MAFLD development [OR = 1.87, 95% confidence interval (CI): 1.07-3.29]. Although the number of MetS components and the metabolic syndrome score were significantly associated with MAFLD in univariate analysis, they were not independently associated with MAFLD in the multivariate model. A dynamic nomogram for predicting MAFLD risk in patients with MetS was developed and internally validated. The area under the receiver operating characteristic curve was 0.834 (95% CI: 0.787-0.880) in the training set and 0.839 (95% CI: 0.771-0.899) in the validation set, indicating strong predictive performance. Bootstrap internal validation demonstrated good agreement between predicted and observed outcomes in calibration curves. Decision curve analysis further indicated favorable clinical applicability of the nomogram. CONCLUSION: BMI, WC, TC, ALT, MetS-defined dysglycemia, and education level are independent risk factors for MAFLD. A dynamic nomogram for predicting MAFLD risk in patients with MetS was successfully developed and validated.

Humans

Parents' Awareness of Their Adolescents' Sexual Behaviors and Experiences: A Concordance Analysis.

PURPOSE: Adolescence is a developmental period during which sexual exploration is normative. Parental awareness of adolescents' sexual behaviors can be protective during this stage; however, research suggests both parents and adolescents tend to avoid open conversations about these sensitive issues. This study aimed to examine concordance between parent proxy-reports and adolescent self-reports across three domains of adolescents' sexual behaviors and experiences. METHODS: Data were collected from a national sample of 522 parent-adolescent dyads (aged 15-17 years) from the AmeriSpeak panel (data collected May-September 2022). Prevalence-adjusted bias-adjusted kappa (PABAK) statistics were calculated to evaluate agreement. RESULTS: Findings revealed weak-to-moderate concordance regarding adolescents sending and receiving sexual photos (PABAKs = 0.54-0.79), whereas stronger concordance was observed for experiences related to nonconsensual sharing of sexual photos (PABAKs = 0.92-0.94), with high agreement largely driven by low reported prevalence of these experiences. Strong concordance regarding whether adolescents had ever had sex (PABAK = 0.80) was largely driven by both parents and adolescents reporting the adolescent had not had sex. Concordance regarding sexually transmitted infection and pregnancy prevention methods varied, ranging from weak to strong agreement across specific methods (or lack thereof; PABAKs = -0.07-0.79). DISCUSSION: Results highlight significant discrepancies in parents' knowledge about their adolescents' sexual behaviors and experiences. Interventions aimed at enhancing trust and open dialogue between parents and adolescents about sexuality-related topics, as well as ensuring adolescents have a variety of trusted sources to consult for sexual information, can help adolescents make informed sexual health decisions.

Humans

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (&#x3c1;&#xa0;=&#xa0;0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2&#xa0;&#x2248;&#xa0;12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2&#xa0;&#x2248;&#xa0;41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (&#x2248;1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans

Financial incentives and social messaging for repeat SARS-CoV-2 antibody testing among the underserved: A randomized trial.

Financial incentives may influence health behavior beyond their expected monetary value, and their effectiveness may depend on how the behavior is framed. Behavioral theories of decision making suggest that individuals may value protection against small-stakes losses more than expected utility predicts, while theories of family-centered health behavior suggest that messages emphasizing benefits to family members may strengthen participation in preventive health activities. We tested these ideas in a 2&#xd7;2 factorial randomized trial involving 625 households recruited from a Federally Qualified Health Center serving low-income Latino/Hispanic communities. Participants completed repeat SARS-CoV-2 antibody testing. The trial crossed two messaging strategies (Family vs. Personal) with two incentive structures (Loss Protection vs. Lottery) that offered equivalent expected monetary value. Family Messaging emphasized protecting one's family from COVID-19, whereas Personal Messaging emphasized protecting oneself. Loss Protection allowed participants to secure an at-risk reward through repeat testing, whereas the Lottery condition offered a chance of a large reward. Repeat testing was approximately 8 percentage points higher under Family Messaging and 7 percentage points higher under Loss Protection. Baseline trust in medical providers, financial barriers to vaccination, and risk aversion were associated with initial testing, whereas household characteristics were not associated with repeat testing. Incentive design may matter beyond expected monetary value and that framing health behaviors in terms of family welfare may increase participation in repeated healthy activities. Broadly, the results support behavioral theories emphasizing loss aversion, anticipated regret, and family-centered motivations, and suggest practical approaches for improving engagement in repeat health behaviors. CLINICALTRIALS.GOV REGISTRATION NUMBER:: NCT01901624.

Adult

Beyond survival: Testicular tissue cryopreservation for fertility preservation during childhood cancer, experiences from a single center.

INTRODUCTION: Approximately 30% of all male childhood cancer survivors receive gonadotoxic therapy increasing their risk for infertility. The only current option for potential fertility preservation in prepubertal males is through testicular tissue cryopreservation (TTC), available through clinical trials. Our aim was to evaluate our experience and identify barriers to enrollment in the TTC study. METHODS: A retrospective review was conducted to describe a single center experience with TTC, including an assessment of factors impacting the decision to enroll or not enroll in the TTC trial. RESULTS: A total of 61 patients were found to be eligible for enrollment in the TTC trial, with 23 patients (34%) choosing to enroll and undergo testicular tissue cryopreservation including 19 (83%) oncology patients. In patients who underwent TTC there were no unexpected delays in starting disease directed therapy. For families that declined enrollment, many did not see fertility preservation as a priority at the time of counseling. (n = 17, 44%). Other barriers included concerns about post-operative complications and a feeling of being overwhelmed at the time of counseling. DISCUSSION: Despite being the only preservation option for pre-pubertal boys facing risk of infertility, TTC enrollment was not pursued by a majority of eligible patients and families. Identifying potential barriers or misconceptions, particularly in regard to post operative complication risks, offer opportunities for improved counseling and education. Early introduction of the Fertility Navigation team allows for procedural coordination success and access for patients that are interested. Success is not measured in how many patients proceed with TTC, rather that all patients have the opportunity for counseling and discussion. CONCLUSION: TTC can be offered and completed safely without delays in disease-directed treatment timelines. A Fertility Navigation Program allows for equal opportunity for education and enrollment on TTC protocol which should be the goal for pediatric institutions, though is not pursued by many patients. A majority of those who declined the study did not see fertility as a priority at the time of treatment while others were concerned regarding peri-operative risks.

Humans

Toward real-time quantification of driving risks: a systematic review and research agenda of risk field theory.

In complex traffic systems, driving risk often evolves in a continuous and progressive manner prior to crash occurrence. How to effectively represent and analyze such latent risk states remains a central challenge in traffic safety research. In recent years, risk field-based approaches have introduced spatial and spatiotemporal continuous modeling paradigms, providing new perspectives for characterizing the distribution of traffic risk and its dynamic evolution. Motivated by the rapid growth of this research area and the lack of a systematic synthesis, this paper presents a comprehensive review of studies applying risk field theory to driving safety and traffic risk analysis. Following the PRISMA guidelines, relevant literature was collected through multi-database searches and analyzed using a combination of bibliometric analysis and qualitative review. The review systematically summarizes the theoretical foundations, modeling elements, data sources, analytical methods, and application domains of risk field-related research. Particular attention is given to studies that conceptualize traffic risk as a continuous field, complemented by a broader review of traffic risk factor literature to identify key elements and analytical dimensions involved in risk field modeling. On this basis, the paper synthesizes research progress in major application areas, including traffic safety state representation, driving behavior analysis, traffic conflict assessment, and autonomous driving and human-machine cooperative systems. Differences and commonalities among existing studies are compared in terms of modeling strategies, data support, and application scenarios. Through this systematic review, the paper clarifies the main research themes and methodological trends of risk field-based studies, providing a structured framework for understanding the evolution and application of this approach and offering methodological insights for risk perception modeling and safety-oriented decision support in intelligent transportation systems (ITS).

Humans

Non-genetic Risk Factors for Allopurinol-Induced Severe Cutaneous Adverse Reaction (SCAR): A Systematic Review.

BACKGROUND: Allopurinol-induced severe cutaneous adverse reactions (SCARs) are rare but potentially life threatening, particularly in Asian populations. While the genetic marker HLA-B*58:01 is a well-established risk factor, non-genetic factors may also contribute. This systematic review synthesizes evidence on associations between non-genetic risk factors and allopurinol-induced SCAR. METHODS: We searched MEDLINE, Scopus, Cochrane Library and Web of Science from inception to 29 June 2026 for observational studies examining non-genetic risk factors for SCAR, defined as Stevens-Johnson Syndrome, Toxic Epidermal Necrolysis, Acute Generalised Exanthematous Pustulosis, or Hypersensitivity Syndrome/Drug Reaction with Eosinophilia and Systemic Symptoms. Adults aged &#x2265;&#xa0;18 years were included. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random-effects model; heterogeneity was assessed with I2. Mean differences were calculated for continuous variables. NIH Study Quality Assessment Tool was used for quality assessment of the studies. RESULTS: Twenty-six studies were included. Female sex (20 studies; 3340 SCAR cases, 562,647 controls) was associated with an increased risk of allopurinol-induced SCAR (OR 2.06; 95% confidence interval (CI) 1.25-3.38). Chronic kidney disease (16 studies; 1625 SCAR cases, 553,804 controls) was also significantly associated with SCAR (OR 3.78; 95% CI 1.99-7.17). Five studies (177 SCAR cases, 1368 controls) reported higher allopurinol doses among SCAR cases than tolerant controls (mean difference 19.61 mg; 95% CI 2.97-36.24). No significant associations were observed for age or concomitant diuretic use in the primary meta-analyses. Substantial heterogeneity was observed across studies. Sensitivity analyses demonstrated consistent findings for most factors, although concomitant diuretic use became significantly associated with SCAR after exclusion of non-Asian and zero-event studies. CONCLUSION: CKD, female sex, and higher allopurinol dose were identified as significant non-genetic risk factors for allopurinol-induced SCAR. These findings support consideration of non-genetic factors alongside pharmacogenomic screening in future risk-stratification strategies. However, substantial heterogeneity and potential publication bias limit the certainty of the available evidence. Well-designed studies evaluating non-genetic predictors as primary outcomes are needed to develop robust integrated risk prediction models for clinical decision making.

Journal Article

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting ACL injuries, evaluating their methodological quality, performance, and reliability. METHOD: A comprehensive electronic search was conducted across PubMed, Scopus, Web of Science, and IEEE Xplore databases, supplemented by Google Scholar for grey literature, covering articles published between January 1, 2015, and August 30, 2025. Eligible studies were appraised using the Prediction Model Study Risk of Bias Assessment Tool (PROBAST) for methodological quality and risk of bias, and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines for quality of evidence. RESULTS: Ten studies were included. PROBAST showed eight studies had moderate risk of bias and two low risk. TRIPOD found only two studies met quality criteria. ML models included logistic regression (n&#xa0;=&#xa0;5), support vector machines (n&#xa0;=&#xa0;4), k-nearest neighbor (n&#xa0;=&#xa0;3), decision trees (n&#xa0;=&#xa0;3), random forests (n&#xa0;=&#xa0;5), neural networks (n&#xa0;=&#xa0;2), linear discriminant analysis (n&#xa0;=&#xa0;1), and pre-trained CNNs (n&#xa0;=&#xa0;1). AUC ranged from 0.63 to 0.98. Accuracy (reported in six studies) ranged from 26% to 95%; however, these values should be interpreted with caution due to the absence of confidence intervals, lack of class imbalance handling, and limited external validation across studies. Tree-based ensemble methods such as random forest achieved competitive accuracy (74-86%), while SVM, a non-ensemble classifier, reported accuracy ranging from 71% to 95%; however, the highest values were obtained in studies with notably small sample sizes (n&#xa0;=&#xa0;12 to n&#xa0;=&#xa0;39), raising concerns about overfitting and generalizability. CONCLUSION: Current ML algorithms show promise for identifying athletes at high ACL injury risk and detecting relevant risk factors. Although study quality was generally satisfactory, future research should prioritize external validation and model interpretability to support clinical translation.

Humans

An overview of the use of proteomics and peptidomics to characterize alternative protein foods.

The global protein transition is accelerating the development of alternative protein foods, mainly derived from plants, insects, algae, fungi, and cellular agriculture. Ensuring the authenticity, safety, and nutritional adequacy of these emerging protein matrices requires molecular-level characterization beyond traditional compositional analyses. Proteomics and peptidomics have emerged as transformative analytical platforms capable of decoding the molecular signatures that define protein origin, structural integrity, digestibility, functionality, and health potential. The review comprehensively examines the application of proteomics, and peptidomics for profiling alternative protein foods. Further, the source authentication strategies based on species-specific protein and peptide biomarkers, detection of adulteration in complex matrices, and allergenicity assessment is discussed. Special attention is also given to nutritional proteomics with protein digestibility, gastrointestinal peptide release, and identification of bioactive sequences. SIGNIFICANCE: The importance of this review is that proteomics and peptidomics are becoming central in the management of the fast-growing environment of alternative protein foods, such as plant-based, insect, algal, fungal, and cultured meat products. It provides an explanation of the application of mass spectrometry-based processes to decode molecular signatures defining the origin of proteins, their structural integrity, digestibility, allergenicity, and bioactive properties, and thus directly contribute to safety, nutritional analysis, and authenticity of the product. Presentation of the article includes the integration of the knowledge of traditional muscle foods with alternative systems of proteins, where validated protein and peptide biomarkers are used in authentication, fraud detection, and allergy risk assessment in a wide variety of matrices. It also indicates the role of nutritional proteomics and peptidomics in informing the formulation strategy to promote digestibility and release of health-promoting peptides. In general, this review will guide scientists, the food industry, and regulatory bodies to use modern proteomic technologies in quality assurance, and decision-making, for the advancementof sustainable protein-based foods.

Proteomics

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine learning (ML) in SLE combined heterogeneous tasks and validation strategies and may have overinterpreted model performance. OBJECTIVE: This study evaluated the diagnostic performance of ML and deep learning (DL) models for 3 clinically distinct SLE-related tasks: SLE classification or diagnosis, lupus nephritis (LN) diagnosis, and neuropsychiatric systemic lupus erythematosus (NPSLE) discrimination. We also assessed methodological quality and certainty of evidence. METHODS: PubMed, Embase, Cochrane Library, Web of Science, and IEEE Xplore were searched from January 2014 to April 2026. Eligible peer-reviewed diagnostic accuracy studies developed or validated ML or DL models for 1 of the 3 prespecified tasks, used an accepted reference standard, and provided data for a 2&#xd7;2 contingency table. Bivariate random-effects meta-analyses with the Hartung-Knapp-Sidik-Jonkman adjustment were used to pool sensitivity and specificity. We reported 95% prediction intervals (PIs), assessed risk of bias using the Quality Assessment of Diagnostic Accuracy Studies for Artificial Intelligence tool (QUADAS-AI; Viknesh Sounderajah [Imperial College London]), and evaluated certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation framework for diagnostic test accuracy. RESULTS: Twenty-nine studies were included: 17 for SLE classification, 5 for LN diagnosis, and 7 for NPSLE discrimination. In the primary task-stratified analysis, pooled sensitivity was 0.91 (95% CI 0.86-0.94; 95% PI 0.56-0.99), and pooled specificity was 0.94 (95% CI 0.91-0.96; 95% PI 0.69-0.99), with low heterogeneity (I&#xb2;=23.9% and 22.9%, respectively). DL models showed a sensitivity of 0.93 and specificity of 0.95, compared with 0.88 and 0.94 for traditional ML models. Certainty of evidence was high for most analyses but low for LN diagnosis because of inconsistency and imprecision. All studies were retrospective, and only 9 of 29 (31%) performed independent external validation. Overall risk of bias was high or unclear in 22 of 29 (75.9%) studies. No study reported model calibration, decision-curve analysis, or net clinical benefit. CONCLUSIONS: ML models showed promising diagnostic accuracy across 3 distinct SLE-related tasks, but wide PIs, limited external validation, and pervasive risk of bias restrict conclusions about real-world generalizability. Prospective multicenter studies with standardized tasks and reference standards, independent external validation, and formal assessment of calibration and clinical utility are required before clinical implementation.

Humans

Prothrombin complex concentrate (PCC) vs. non-PCC strategies for warfarin reversal in left ventricular assist device recipients: A systematic review and meta-analysis.

BACKGROUND: Left ventricular assist devices (LVADs) prolong survival in end-stage heart failure, and warfarin thromboprophylaxis is recommended to prevent device thrombosis and thromboembolic complications. When bleeding occurs or emergency surgery is required, rapid anticoagulation reversal is critical. Prothrombin complex concentrate (PCC) provides rapid reversal; however, its risk-benefit profile in LVAD recipients remains unclear. We conducted a systematic review and meta-analysis comparing PCC with non-PCC strategies for warfarin reversal in LVAD recipients. METHODS: MEDLINE, Embase, and Scopus were searched through June 2025 for studies of PCC versus non-PCC strategies for warfarin reversal in LVAD recipients. Two reviewers independently extracted data. Random-effects models were used to pool arm-level estimates and to pool head-to-head comparisons using mean differences or risk ratios (RRs). RESULTS: Eighteen studies involving 779 patients were included. Arm-level pooled estimates for PCC versus non-PCC comparators were 24.0% versus 15.8% for mortality, 16.5% versus 12.1% for thrombotic events, and 3.1 versus 5.7 for FFP units. Arm-level time to INR correction was longer with PCC overall (16.5 versus 13.6&#xa0;h), driven by one elective cohort, but faster within the ICH subgroup (6.0 versus 13.7&#xa0;h). In head-to-head comparisons, PCC achieved faster INR correction than non-PCC comparators (mean difference&#xa0;-&#xa0;7.6&#xa0;h; p&#xa0;=&#xa0;0.001) and required fewer FFP units (-2.6&#xa0;units; p&#xa0;=&#xa0;0.019), with no significant difference in all-cause mortality (RR 1.14; p&#xa0;=&#xa0;0.490) or thrombotic events (RR 1.43; p&#xa0;=&#xa0;0.176). CONCLUSIONS: In head-to-head studies, PCC was associated with faster INR correction and lower FFP requirements than non-PCC strategies, whereas mortality and thrombotic events did not differ significantly. Given the observational evidence, wide confidence intervals, and heterogeneity, equivalent safety cannot be established, and prospective studies are needed to define the relative safety and effectiveness of the two approaches. IMPLICATIONS FOR CLINICAL PRACTICE: PCC-based strategies may be considered for urgent warfarin reversal in LVAD recipients, particularly when rapid INR reduction or avoidance of large-volume plasma transfusion is clinically important. Treatment decisions should account for the indication, bleeding severity, and underlying thrombotic risk. TRIAL REGISTRATION: CRD42024573925.

Humans

HPV circulating tumor DNA as a potential prognostic and predictive biomarker in head and neck squamous cell carcinoma: a systematic review.

PURPOSE: Human papillomavirus circulating tumor DNA (HPVctDNA) has emerged as a promising prognostic biomarker in HPV-related head and neck squamous cell carcinoma (HNSCC). This systematic review aimed to synthesize current evidence on the diagnostic accuracy and prognostic value of HPVctDNA in HNSCC management. MATERIAL/METHODS: We systematically reviewed a PubMed-indexed database of studies published between January 2012 and September 2025. Eligible studies were assessed for design, primary tumor site and stage, treatment modality, HPVctDNA detection method, diagnostic accuracy (sensitivity and specificity), and reported clinical endpoints. Descriptive syntheses were performed; sensitivity and specificity were standardized to proportions and summarized as median values per group. RESULTS: A total of 60 studies, including 8,234 patients were analyzed, of which 41 (68.3%) focused exclusively on oropharyngeal squamous cell carcinoma (OPSCC) and 17 (28.3%) included mixed HPV-related HNSCC subsites and HPV-positive cancers of unknown primary. The median follow-up across the included studies was 23&#xa0;months. Among the included studies, 19 were retrospective (31.7%) and 33 were prospective (55.0%), with a small proportion of cross-sectional and randomized clinical trials. Overall, 40 (66.7%) evaluated the role of HPVctDNA in a curative setting. Plasma was the most common sample type, analyzed in 55 studies (91.7%), while 5 studies also included saliva. Detection methods varied: 40 employed droplet digital PCR (ddPCR), 16 used quantitative PCR (qPCR) and 4 applied NGS-based assays. Most of these studies (38, 63.3%) evaluated the prognostic utility of HPVctDNA, while only 4 (6.7%) assessed HPVctDNA in a screening or diagnostic setting. Regarding diagnostic accuracy, the median sensitivity across evaluable studies was 91.1%, while the median specificity was 99.4%. In OPSCC-only cohorts, the median sensitivity and specificity were 89.4% and 99.4%, respectively. Dynamic changes in HPVctDNA levels during or after treatment were consistently associated with outcomes: clearance or sustained negativity correlated with higher response rates, improved progression-free survival and overall survival, while persistent positivity or increasing levels predicted disease progression and recurrence. CONCLUSIONS: HPVctDNA demonstrates high diagnostic and prognostic accuracy in HPV-related HNSCC, especially OPSCC, supporting its use for prognosis, treatment monitoring and early detection of recurrence. However, prospective interventional studies are still required to demonstrate that HPVctDNA-guided treatment decisions improve clinical outcomes before routine implementation.

Humans