Med Biol Eng Comput. 2025 Jan 9. doi: 10.1007/s11517-024-03264-z. Online ahead of print.

ABSTRACT

This study aimed to analyze computational techniques in ECG imaging (ECGI) reconstruction, focusing on dataset identification, problem-solving, and feature extraction. We employed a PRISMA approach to review studies from Scopus and Web of Science, applying Cochrane principles to assess risk of bias. The selection was limited to English peer-reviewed papers published from 2010 to 2023, excluding studies that lacked computational technique descriptions. From 99 reviewed papers, trends show a preference for traditional methods like the boundary element and Tikhonov methods, alongside a rising use of advanced technologies including hybrid techniques and deep learning. These advancements have enhanced cardiac diagnosis and treatment precision. Our findings underscore the need for robust data utilization and innovative computational integration in ECGI, highlighting promising areas for future research and advances. This shift toward tailored cardiac care suggests significant progress in diagnostic and treatment methods.

PMID:39779645 | DOI:10.1007/s11517-024-03264-z

J Imaging Inform Med. 2025 Jan 8. doi: 10.1007/s10278-024-01368-4. Online ahead of print.

ABSTRACT

Biopsy is considered the gold standard for diagnosing brain tumors, but its invasive nature can pose risks to patients. Additionally, tissue analysis can be cumbersome and inconsistent among observers. This research aims to develop a cost-effective, non-invasive, MRI-based computer-aided diagnosis tool that can reliably, accurately and swiftly identify brain tumor grades. Our system employs ensemble deep learning (EDL) within an MRI multiclass framework that includes five datasets: two-class (C2), three-class (C3), four-class (C4), five-class (C5) and six-class (C6). The EDL utilizes a majority voting algorithm to classify brain tumors by combining seven renowned deep learning (DL) models-EfficientNet, VGG16, ResNet18, GoogleNet, ResNet50, Inception-V3 and DarkNet-and seven machine learning (ML) models, including support vector machine, K-nearest neighbour, Naïve Bayes, decision tree, linear discriminant analysis, artificial neural network and random forest. Additionally, local interpretable model-agnostic explanations (LIME) are employed as an explainable AI algorithm, providing a visual representation of the CNN's internal workings to enhance the credibility of the results. Through extensive five-fold cross-validation experiments, the DL-based majority voting algorithm outperformed the ML-based majority voting algorithm, achieving the highest average accuracies of 100 ± 0.00%, 98.55 ± 0.35%, 98.47 ± 0.63%, 95.34 ± 1.17% and 96.61 ± 0.85% for the C2, C3, C4, C5 and C6 datasets, respectively. Majority voting algorithms typically yield consistent results across different folds of the brain tumor data and enhance performance compared to any individual deep learning and machine learning models.

PMID:39779641 | DOI:10.1007/s10278-024-01368-4

Eur Radiol. 2025 Jan 9. doi: 10.1007/s00330-024-11312-3. Online ahead of print.

ABSTRACT

BACKGROUND: Chronic liver disease (CLD) is a substantial cause of morbidity and mortality worldwide. Liver stiffness, as measured by MR elastography (MRE), is well-accepted as a surrogate marker of liver fibrosis.

PURPOSE: To develop and validate deep learning (DL) models for predicting MRE-derived liver stiffness using routine clinical non-contrast abdominal T1-weighted (T1w) and T2-weighted (T2w) data from multiple institutions/system manufacturers in pediatric and adult patients.

MATERIALS AND METHODS: We identified pediatric and adult patients with known or suspected CLD from four institutions, who underwent clinical MRI with MRE from 2011 to 2022. We used T1w and T2w data to train DL models for liver stiffness classification. Patients were categorized into two groups for binary classification using liver stiffness thresholds (≥ 2.5 kPa, ≥ 3.0 kPa, ≥ 3.5 kPa, ≥ 4 kPa, or ≥ 5 kPa), reflecting various degrees of liver stiffening.

RESULTS: We identified 4695 MRI examinations from 4295 patients (mean ± SD age, 47.6 ± 18.7 years; 428 (10.0%) pediatric; 2159 males [50.2%]). With a primary liver stiffness threshold of 3.0 kPa, our model correctly classified patients into no/minimal (< 3.0 kPa) vs moderate/severe (≥ 3.0 kPa) liver stiffness with AUROCs of 0.83 (95% CI: 0.82, 0.84) in our internal multi-site cross-validation (CV) experiment, 0.82 (95% CI: 0.80, 0.84) in our temporal hold-out validation experiment, and 0.79 (95% CI: 0.75, 0.81) in our external leave-one-site-out CV experiment. The developed model is publicly available ( https://github.com/almahdir1/Multi-channel-DeepLiverNet2.0.git ).

CONCLUSION: Our DL models exhibited reasonable diagnostic performance for categorical classification of liver stiffness on a large diverse dataset using T1w and T2w MRI data.

KEY POINTS: Question Can DL models accurately predict liver stiffness using routine clinical biparametric MRI in pediatric and adult patients with CLD? Findings DeepLiverNet2.0 used biparametric MRI data to classify liver stiffness, achieving AUROCs of 0.83, 0.82, and 0.79 for multi-site CV, hold-out validation, and external CV. Clinical relevance Our DeepLiverNet2.0 AI model can categorically classify the severity of liver stiffening using anatomic biparametric MR images in children and young adults. Model refinements and incorporation of clinical features may decrease the need for MRE.

PMID:39779515 | DOI:10.1007/s00330-024-11312-3

AJNR Am J Neuroradiol. 2025 Jan 8;46(1):41-48. doi: 10.3174/ajnr.A8482.

ABSTRACT

BACKGROUND AND PURPOSE: DWI is crucial for detecting infarction stroke. However, its spatial resolution is often limited, hindering accurate lesion visualization. Our aim was to evaluate the image quality and diagnostic confidence of deep learning (DL)-based super-resolution reconstruction for brain DWI of infarction stroke.

MATERIALS AND METHODS: This retrospective study enrolled 114 consecutive participants who underwent brain DWI. The DWI images were reconstructed with 2 schemes: 1) DL-based super-resolution reconstruction (DWIDL); and 2) conventional compressed sensing reconstruction (DWICS). Qualitative image analysis included overall image quality, lesion conspicuity, and diagnostic confidence in infarction stroke of different lesion sizes. Quantitative image quality assessments were performed by measurements of SNR, contrast-to-noise ratio (CNR), ADC, and edge rise distance. Group comparisons were conducted by using a paired t test for normally distributed data and the Wilcoxon test for non-normally distributed data. The overall agreement between readers for qualitative ratings was assessed by using the Cohen κ coefficient. A P value less than .05 was considered statistically significant.

RESULTS: A total of 114 DWI examinations constituted the study cohort. For the qualitative assessment, overall image quality, lesion conspicuity, and diagnostic confidence in infarction stroke lesions (lesion size <1.5 cm) improved by DWIDL compared with DWICS (all P < .001). For the quantitative analysis, edge rise distance of DWIDL was reduced compared with that of DWICS (P < .001), and no significant difference in SNR, CNR, and ADC values (all P > .05).

CONCLUSIONS: Compared with the conventional compressed sensing reconstruction, the DL-based super-resolution reconstruction demonstrated superior image quality and was feasible for achieving higher diagnostic confidence in infarction stroke.

PMID:39779291 | DOI:10.3174/ajnr.A8482

J Clin Neurol. 2025 Jan;21(1):21-30. doi: 10.3988/jcn.2024.0175.

ABSTRACT

BACKGROUND AND PURPOSE: Parkinson's disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information.

METHODS: We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods.

RESULTS: During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931-0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922.

CONCLUSIONS: A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.

PMID:39778564 | DOI:10.3988/jcn.2024.0175

Neural Netw. 2024 Dec 31;184:107098. doi: 10.1016/j.neunet.2024.107098. Online ahead of print.

ABSTRACT

Modifying the structure of an existing network is a common method to further improve the performance of the network. However, modifying some layers in network often results in pre-trained weight mismatch, and fine-tune process is time-consuming and resource-inefficient. To address this issue, we propose a novel technique called Identity Model Transformation (IMT), which keep the output before and after transformation in an equal form by rigorous algebraic transformations. This approach ensures the preservation of the original model's performance when modifying layers. Additionally, IMT significantly reduces the total training time required to achieve optimal results while further enhancing network performance. IMT has established a bridge for rapid transformation between model architectures, enabling a model to quickly perform analytic continuation and derive a family of tree-like models with better performance. This model family possesses a greater potential for optimization improvements compared to a single model. Extensive experiments across various object detection tasks validated the effectiveness and efficiency of our proposed IMT solution, which saved 94.76% time in fine-tuning the basic model YOLOv4-Rot on DOTA 1.5 dataset, and by using the IMT method, we saw stable performance improvements of 9.89%, 6.94%, 2.36%, and 4.86% on the four datasets: AI-TOD, DOTA1.5, coco2017, and MRSAText, respectively.

PMID:39778291 | DOI:10.1016/j.neunet.2024.107098

J Inherit Metab Dis. 2025 Jan;48(1):e12835. doi: 10.1002/jimd.12835.

ABSTRACT

Inborn errors of metabolism (IEMs) are rare genetic conditions with significant morbidity and mortality. Technological advances have increased therapeutic options, making it challenging to remain up to date. A centralized therapy knowledgebase is needed for early diagnosis and targeted treatment. This study aimed to identify all treatable IEMs through a scoping literature review, followed by data extraction and analysis according to the Treatabolome principles. Knowledge of treatable IEMs, therapeutic categories, efficacy, and evidence was integrated into the Inborn Errors of Metabolism Knowledgebase (IEMbase), an online database encompassing all IEMs. The study identified 275 treatable IEMs, 18% of all currently known 1564 IEMs, according to the International Classification of Inherited Metabolic Disorders. Disorders of fatty acid and ketone body metabolism had the highest treatability (67%), followed by disorders of vitamin and cofactor metabolism (60%), and disorders of lipoprotein metabolism (42%). The most common treatment strategies were pharmacological therapy (34%), nutritional therapy (34%), and vitamin and trace element supplementation (12%). Treatment effects were most commonly observed in nervous system abnormalities (34%), metabolism/homeostasis abnormalities (33%), and growth (7%). Predominant evidence sources included case reports with evidence levels 4 (48%) and 5 (12%), and individual cohort studies with evidence level 2b (12%). Our study generated the Metabolic Treatabolome 2024. IEMs are the largest group of monogenic disorders amenable to disease-modifying therapy. With drug repurposing efforts and advancements in gene therapies, this number will expand. IEMbase now provides up-to-date, comprehensive information on clinical and biochemical symptoms and therapeutic options, empowering patients, families, healthcare professionals, and researchers in improving patient outcomes.

PMID:39777714 | DOI:10.1002/jimd.12835

Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2025 Oct 10;42(10):34-40. doi: 10.3760/cma.j.cn511374-20240809-00433.

ABSTRACT

OBJECTIVE: To explore the clinical and genetic characteristics of two children diagnosed with two rare genetic diseases simultaneously.

METHODS: Two children with comorbidity of two genetic diseases due to dual genetic mutations diagnosed at the Third Affiliated Hospital of Zhengzhou University respectively in May 2022 and March 2023 were selected as the study subjects. Clinical and genetic data of the two children were retrospectively analyzed. This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethic No. 2021-062-01).

RESULTS: Child 1 was a 2-year-and-4-month-old boy whose clinical manifestations included facial dysmorphism, developmental delay, short stature, microcephaly, cleft palate, cryptorchidism, hypospadias, recurrent infections and immunological abnormalities. Whole exome sequencing revealed that he had harbored a heterozygous c.6595delT (p.Y2199Ifs*65) variant of the KMT2D gene and a heterozygous c.1892G>A (p.R631Q) variant of the PIK3R1 gene. This has led to a dual genetic diagnosis of Kabuki syndrome and PI3Kδ-related immunodeficiency type 36. Child 2 was a 15-year-old girl whose clinical manifestations included epilepsy, Albright's hereditary osteodystrophy, long body trunk, short limbs, hypocalcemia, hyperphosphatemia and hyperparathyroidism. The child also had a family history of short stature. Whole exome sequencing revealed that she had harbored a heterozygous c.2T>C (p.Met1?) variant of the GNAS gene and deletion of exons 2 to 6 of the SHOX gene. The two variants have led to dual diagnose of pseudohypoparathyroidism and X-linked idiopathic short stature.

CONCLUSION: When the clinical phenotype of a genetic disease is complex and cannot be fully explained with a single genetic variant, multiple pathogenic variants should be considered, and this may lead to the diagnosis of co-morbid genetic diseases. To adopt or supplement corresponding genetic testing in time and re-analyze the genetic data may facilitate accurate diagnosis of co-morbid genetic diseases.

PMID:39779334 | DOI:10.3760/cma.j.cn511374-20240809-00433

Epidemiol Serv Saude. 2024 Dec 20;33:e20240204. doi: 10.1590/S2237-96222024v33e20240204.en. eCollection 2024.

ABSTRACT

OBJECTIVE: To analyze the first referral service for rare diseases accredited by the Brazilian Ministry of Health, focusing on referral from the primary healthcare network through to diagnosis.

METHODS: This is a descriptive study with patients treated between 2016 and 2021 at a referral hospital service located in Curitiba, Paraná, Brazil. Clinical and epidemiological data were obtained from medical records, as were the results of genetic tests at the hospital's clinical analysis laboratory. Qualitative data were expressed as absolute and relative frequencies, while quantitative data were expressed as medians and interquartile ranges and compared using the Kruskal-Wallis test.

RESULTS: The study included 1,751 cases, 34.1% were diagnosed with rare diseases, with average time until diagnosis being 3.0 years, whereby mucopolysaccharidosis type II (4.0%) and tuberous sclerosis (3.9%) were the most common. Greater length of time for obtaining diagnosis (p-value 0.004) and receiving specialized care (p-value<0.001) was found in patients from the interior region of Paraná state, compared to those residing in Curitiba city and its metropolitan region.

CONCLUSION: Diagnosis of rare diseases occurred in approximately one third of cases. The average time until diagnosis suggests a possible positive impact of implementing the referral service. The longer time until diagnosis and specialized care found among patients from the interior region of Paraná represent challenges regarding adequate referral to specialized services.

PMID:39776132 | DOI:10.1590/S2237-96222024v33e20240204.en

Nature. 2025 Jan 8. doi: 10.1038/s41586-024-08391-z. Online ahead of print.

ABSTRACT

Transcriptional regulation, which involves a complex interplay between regulatory sequences and proteins, directs all biological processes. Computational models of transcription lack generalizability to accurately extrapolate to unseen cell types and conditions. Here we introduce GET (general expression transformer), an interpretable foundation model designed to uncover regulatory grammars across 213 human fetal and adult cell types1,2. Relying exclusively on chromatin accessibility data and sequence information, GET achieves experimental-level accuracy in predicting gene expression even in previously unseen cell types3. GET also shows remarkable adaptability across new sequencing platforms and assays, enabling regulatory inference across a broad range of cell types and conditions, and uncovers universal and cell-type-specific transcription factor interaction networks. We evaluated its performance in prediction of regulatory activity, inference of regulatory elements and regulators, and identification of physical interactions between transcription factors and found that it outperforms current models4 in predicting lentivirus-based massively parallel reporter assay readout5,6. In fetal erythroblasts7, we identified distal (greater than 1 Mbp) regulatory regions that were missed by previous models, and, in B cells, we identified a lymphocyte-specific transcription factor-transcription factor interaction that explains the functional significance of a leukaemia risk predisposing germline mutation8-10. In sum, we provide a generalizable and accurate model for transcription together with catalogues of gene regulation and transcription factor interactions, all with cell type specificity.

PMID:39779852 | DOI:10.1038/s41586-024-08391-z

Osteoporos Int. 2025 Jan 8. doi: 10.1007/s00198-024-07352-6. Online ahead of print.

ABSTRACT

BACKGROUD: Hypoparathyroidism (hypoPT) is characterized by acute and chronic complications due to insufficient parathyroid hormone (PTH) production or action. Several management guidelines have been developed, but mostly based on evidence from Western countries. Data from Eastern countries have not been systematically compared with those from Western countries.

METHODS: Literatures regarding to the epidemiology, genetics, risk factors, clinical manifestations and therapies for hypoPT in Easten and Western countries, including China, South Korea, Japan, India, and USA, Canada, Italy, and etc., were searched through PubMed and CNKI. This review was officially endorsed by European Calcified Tissue Society (ECTS) board.

RESULTS: Postoperative hypoPT is the major form of hypoPT in both Western and Eastern countries. The genetic profiles and clinical features of hypoPT are similar in Eastern and Western countries. The most commonly used medications in Eastern countries are calcium and native vitamin D or active vitamin D analogues, similar to their Western counterparts. While PTH replacement therapy is not available and approved to use in most Eastern countries.

CONCLUSION: Physicians and surgeons should follow the guidelines on the management of thyroid nodules, taking more care of protecting parathyroid glands during surgery. The cross-talk between East and West in the management of hypoPT should be continued. Direct comparisons of the management strategies in patients with hypoPT between Eastern and Wester countries regarding to the morbidity, mortality, quality of life, optimal dosage, efficacies and side-effects of conventional therapies or newer medications, as well as pharmacogenetics and pharmacoeconomics, would be valuable.

PMID:39777494 | DOI:10.1007/s00198-024-07352-6

NPJ Biofilms Microbiomes. 2025 Jan 8;11(1):8. doi: 10.1038/s41522-024-00637-y.

ABSTRACT

Chronic infections represent a significant global health and economic challenge. Biofilms, which are bacterial communities encased in an extracellular polysaccharide matrix, contribute to approximately 80% of these infections. In particular, pathogens such as Pseudomonas aeruginosa and Staphylococcus aureus are frequently co-isolated from the sputum of patients with cystic fibrosis and are commonly found in chronic wound infections. Within biofilms, bacteria demonstrate a remarkable increase in resistance and tolerance to antimicrobial treatment. We investigated the efficacy of combining the last-line antibiotic colistin with a membrane- and stringent stress response-targeting anti-biofilm peptide DJK-5 against co-biofilms comprised of multidrug-resistant P. aeruginosa and methicillin-resistant S. aureus (MRSA). Colistin lacks canonical activity against S. aureus. However, our study revealed that under co-biofilm conditions, the antibiofilm peptide DJK-5 synergized with colistin against S. aureus. Similar enhancement was observed when daptomycin, a cyclic lipopeptide against Gram-positive bacteria, was combined with DJK-5, resulting in increased activity against P. aeruginosa. The combinatorial treatment induced morphological changes in both P. aeruginosa and S. aureus cell shape and size within co-biofilms. Importantly, our findings also demonstrate synergistic activity against both P. aeruginosa and S. aureus in a murine subcutaneous biofilm-like abscess model. In conclusion, combinatorial treatments with colistin or daptomycin and the anti-biofilm peptide DJK-5 show significant potential for targeting co-biofilm infections. These findings offer promising avenues for developing new therapeutic approaches to combat complex chronic infections.

PMID:39779734 | DOI:10.1038/s41522-024-00637-y

J Cyst Fibros. 2025 Jan 7:S1569-1993(24)01860-5. doi: 10.1016/j.jcf.2024.12.009. Online ahead of print.

ABSTRACT

BACKGROUND: Cystic fibrosis (CF) is caused by variants in a gene that encodes a protein essential for water and ion transport in the epithelial cells of exocrine organs. Given the possible relationship of this protein and conjunctival and corneal epithelium, the aim of this study was to evaluate ophthalmologic alterations in people with CF.

METHODS: Forty-five people with CF underwent pulmonary evaluation including inflammatory score (IS). These people along with 98 sex-matched controls underwent ophthalmologic evaluation including dry eye disease (DED) testing, corneal topography using Pentacam™ and macular and peripapillary retinal nerve fiber layer (pRNFL) thickness with optical coherence tomography (OCT).

RESULTS: The CF group presented a higher percentage of pathologic tear break-up time (T-BUT) (55.6 % vs 25 %, p = 0.001) and Schirmer's test 1 (40 % versus 19.4 %, p = 0.009) than the control group. In the CF group, an inverse correlation was observed between T-BUT and IS (r=- 0.373, p = 0.012), as well as T-BUT and peripheral eosinophilia (r=-0.338; p = 0.023). People with CF presented lower values of central corneal thickness (p = 0.009), thinnest point (p = 0.006), anterior chamber volume (p = 0.034), and anterior chamber angle (p = 0.011) than the control group and lower pRNLF thickness in the superior temporal sector (p = 0.002).

CONCLUSIONS: Our findings indicate a higher prevalence of dry eye disease (DED) among people with CF compared to controls. The severity of the condition increases with higher systemic inflammation. Additionally, CF may affect the anterior segment of the eye, leading to a reduction in the nerve fiber layer and early signs of glaucoma.

PMID:39779380 | DOI:10.1016/j.jcf.2024.12.009

J Clin Pathol. 2025 Jan 8:jcp-2024-209899. doi: 10.1136/jcp-2024-209899. Online ahead of print.

ABSTRACT

AIMS: In cystic fibrosis lung transplant recipients (LTRs), graft dysfunction due to acute infections, rejection or chronic lung allograft dysfunction (CLAD) is difficult to distinguish. Characterisation of the airway inflammatory milieu could help detect and prevent graft dysfunction. We speculated that an eosinophil or neutrophil-rich milieu is associated with higher risk of CLAD.

METHODS: A retrospective, single-centre observational study of cystic fibrosis LTRs between 2002 and 2021 was performed. Data from biopsy slides, pulmonary function testing and bronchoalveolar lavage fluid microbiology tests were collected. The primary outcome was bronchiolitis obliterans syndrome (BOS) or death after transplant, with an 8-year follow-up period.

RESULTS: 40 patients were identified with an average age of 35.3 at first transplantation, including 5 redo lung transplants. Fungal infections were correlated with higher rejection scores (p<0.01) and survival status (p=0.027). Fungal and bacterial infection rates were reduced in later transplants (2014-2021) compared with earlier (2002-2014). Fungal infections were associated with significantly worsened outcomes (p≤0.001). Eosinophils in large airways was associated with worse BOS-free survival (p=0.03).

CONCLUSIONS: Subcategorisation of the inflammatory milieu (particularly noting eosinophils) in surveillance biopsies may help detect CLAD earlier and improve long-term outcomes in cystic fibrosis LTRs.

PMID:39779317 | DOI:10.1136/jcp-2024-209899

Eur Respir Rev. 2025 Jan 8;34(175):240131. doi: 10.1183/16000617.0131-2024. Print 2025 Jan.

ABSTRACT

The systemic use of corticosteroids for patients with severe community-acquired pneumonia (sCAP) remains controversial in clinical practice, particularly in terms of the safety profile of these drugs. This narrative review aims to analyse the available literature data concerning the safety of short-term steroid use in the treatment of sCAP, while also highlighting potential future research directions. Several trials and meta-analyses have evaluated corticosteroid therapy as an adjuvant treatment for sCAP, yielding heterogeneous results regarding its efficacy and safety. Despite the wide variability in results, it is generally accepted that steroids are not associated with a significant risk of healthcare-associated infections, gastrointestinal bleeding or acute kidney injury in patients with sCAP in the short term. Nevertheless, such drugs are linked to hyperglycaemia, necessitating regular monitoring and appropriate management. The influence of steroids on long-term outcomes and their potential risks in viral sCAP still needs to be investigated.

PMID:39778921 | DOI:10.1183/16000617.0131-2024

Int Forum Allergy Rhinol. 2025 Jan 8. doi: 10.1002/alr.23524. Online ahead of print.

ABSTRACT

BACKGROUND: Steroid rinses and steroid-eluting stents are both options for preventing postoperative stenosis after frontal sinus surgery. This study aimed to assess whether steroid-eluting stents offer added benefit over steroid rinses alone in postoperative healing and long-term frontal sinus patency.

METHODS: A randomized controlled trial enrolled patients with CRS with nasal polyps (CRSwNP) who underwent surgery for bilateral and equal frontal sinusitis after failing prior medical therapy. Each patient served as their own control, with each patient randomized to stent placement in either right or left frontal sinuses. Exclusion criteria included unequal frontal sinusitis, aspirin exacerbated respiratory disease, cystic fibrosis, primary ciliary dyskinesia, and immunocompromise. All patients used steroid rinses postoperatively. Scarring, edema, patency, and the need for additional treatments were assessed at 1, 3, 12, and 24 weeks postoperatively. Univariate and multivariate analyses were performed.

RESULTS: Sixty-two patients were enrolled. Postoperatively, scarring, edema, patency, and the need for further treatment were similar in both groups at 24 weeks (p = 0.878, 0.688, 0.817, 1.00, and 1.00, respectively). Multivariable regression analysis identified time as an independent risk factor for scarring (OR = 1.32, [1.03‒1.71]) and patency (OR = 1.39, [1.10‒1.82]), while it was an independent protective factor for edema (OR = 0.40, [0.32‒0.49]). The steroid-eluting stent did not significantly affect this.

CONCLUSION: For CRSwNP, with or without asthma, without other underlying systemic disease factors, steroid-eluting stents may not add benefit over steroid rinses in reducing postoperative scarring and edema, improving long-term frontal sinus patency, or reducing the need for additional treatments, as long as patients continue topical therapy and know how to rinse effectively.

PMID:39778085 | DOI:10.1002/alr.23524

Pediatr Pulmonol. 2025 Jan 7:e27471. doi: 10.1002/ppul.27471. Online ahead of print.

ABSTRACT

INTRODUCTION: While the diagnosis of cystic fibrosis (CF) is often straightforward and reliant on correlation between genetic testing and clinical signs and symptoms, there is a subset where the distinction is not nearly as clearcut. This has previously been reported in patients identified through newborn screening but not meeting full CF diagnostic criteria, earning the label of CF Screen Positive, Inconclusive Diagnosis (CFSPID) instead. A homologous diagnostic category in adults is named CF Transmembrane Conductance Regulator-Related Disorder (CFTR-RD).

METHODS: Through a retrospective chart review, this study reports on a relatively large adult cohort (n = 23) that presented to pulmonology clinic at a single center with intermediate or positive sweat chloride tests but non-diagnostic full CFTR gene analysis.

RESULTS: Median sweat chloride result was 48 mmol/L, and a majority of the cohort had chronic lung disease with atypical pathogens on sputum culture, including Pseudomonas aeruginosa, non-tuberculous Mycobacteria, Acinetobacter species, amongst others.

CONCLUSIONS: This clinical picture suggests CFTR dysfunction or similar mechanism in the absence of an identified genetic cause. Alternate chloride channels and their respective genes or candidates of genetic modifiers to the CF-phenotype could be targets of further research in this cohort or similar patients. Such genetic modifiers include loci that have been implicated in inflammation, the CFTR interactome, and/or co-/post-translational modification of CFTR.

PMID:39778078 | DOI:10.1002/ppul.27471

BMC Med Inform Decis Mak. 2025 Jan 8;25(1):10. doi: 10.1186/s12911-024-02843-2.

ABSTRACT

Vitiligo, alopecia areata, atopic, and stasis dermatitis are common skin conditions that pose diagnostic and assessment challenges. Skin image analysis is a promising noninvasive approach for objective and automated detection as well as quantitative assessment of skin diseases. This review provides a systematic literature search regarding the analysis of computer vision techniques applied to these benign skin conditions, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The review examines deep learning architectures and image processing algorithms for segmentation, feature extraction, and classification tasks employed for disease detection. It also focuses on practical applications, emphasizing quantitative disease assessment, and the performance of various computer vision approaches for each condition while highlighting their strengths and limitations. Finally, the review denotes the need for disease-specific datasets with curated annotations and suggests future directions toward unsupervised or self-supervised approaches. Additionally, the findings underscore the importance of developing accurate, automated tools for disease severity score calculation to improve ML-based monitoring and diagnosis in dermatology. TRIAL REGISTRATION: Not applicable.

PMID:39780145 | DOI:10.1186/s12911-024-02843-2