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Journal of Fungi (Basel, Switzerland) May 2024It has long been accepted that trauma is one of the most important and frequent predisposing factors for onychomycoses. However, the role of direct trauma in the...
It has long been accepted that trauma is one of the most important and frequent predisposing factors for onychomycoses. However, the role of direct trauma in the pathogenesis of fungal nail infections has only recently been elucidated in a series of 32 cases of post-traumatic single-digit onychomycosis. The importance of repeated trauma due to foot and toe abnormalities was rarely investigated. : This is a multicenter single-author observational study over a period of 6 years performed at specialized nail clinics in three countries. All patient photographs taken by the author during this period were screened for toenail alterations, and all toe onychomycosis cases were checked for whether they contained enough information to evaluate potential foot and toe abnormalities. Particular attention was paid to the presence of , , , inward rotation of the big toe, and outward rotation of the little toe, as well as splay foot. Only cases with unequivocal proof of fungal nail infection by either histopathology, mycologic culture, or polymerase chain reaction (PCR) were accepted. Of 1653 cases, 185 were onychomycoses, proven by mycologic culture, PCR, or histopathology. Of these, 179 involved at least one big toenail, and 6 affected one or more lesser toenails. Three patients consulted us for another toenail disease, and onychomycosis was diagnosed as a second disease. Eight patients had a pronounced . Relatively few patients had a normal big toe position ( = 9). Most of the cases had a mild to marked (HV) (105) and a (HVI) (143), while was observed in 43 patients, and the combination of HV and HVI was observed 83 times. The very high percentage of foot and toe deformations was surprising. It may be hypothesized that this is not only a pathogenetically important factor but may also play an important role in the localization of the fungal infection, as no marked deviation was noted in onychomycoses that affected the lesser toes only. As the management of onychomycoses is a complex procedure involving the exact diagnosis with a determination of the pathogenic fungus, the nail growth rate, the type of onychomycosis, its duration, and predisposing factors, anomalies of the toe position may be important. Among the most commonly mentioned predisposing factors are peripheral circulatory insufficiency, venous stasis, peripheral neuropathy, immune deficiency, and iatrogenic immunosuppression, whereas foot problems are not given enough attention. Unfortunately, many of these predisposing and aggravating factors are difficult to treat or correct. Generally, when explaining the treatment of onychomycoses to patients, the importance of these orthopedic alterations is not or only insufficiently discussed. In view of the problems encountered with the treatment of toenail mycoses, this attitude should be changed in order to make the patient understand why there is such a low cure rate despite excellent minimal inhibitory drug concentrations in the laboratory.
PubMed: 38921385
DOI: 10.3390/jof10060399 -
Geriatrics (Basel, Switzerland) Jun 2024Several studies have reported subtle differences in cognition between individuals with subjective cognitive decline (SCD) compared to those with normal cognition. This...
Several studies have reported subtle differences in cognition between individuals with subjective cognitive decline (SCD) compared to those with normal cognition. This study aimed to (i) identify these differences using discrepancy scores (e.g., categorial-phonemic verbal fluency performance) derived from neuropsychological tests in three cognitive domains (memory: Wechsler's Word List and Digits; executive functions: Stroop and verbal fluency; and language: BNT and ECCO_Senior) and (ii) determine which discrepancy scores are significant for classification. Seventy-five older adults were included: 32 who were labeled SCD+ (age 71.50 ± 5.29), meeting Jessen et al.'s criteria, and 43 in the normal cognition group (SCD-; age 69.81 ± 4.62). Both groups completed a protocol including screening and the specified neuropsychological tests. No differences were found between the groups in their age, education, episodic memory, global cognitive state, or mood. Significant differences between the groups were observed regarding the discrepancy scores derived from BNT (naming) and ECCO_Senior (sentence comprehension). These scores accurately classified participants (71.6%), with ECCO_Senior having a primary role. ROC curves indicated a poor-to-fair model quality or diagnostic accuracy (AUC_ = 0.690; AUC_ = 0.722). In conclusion, discrepancy scores in the language domain are important for distinguishing between individuals with SCD and normal cognition, complementing previous findings in this domain. However, given their relatively poor diagnostic accuracy, they should be used with caution as part of a more detailed neuro-psychological assessment.
PubMed: 38920439
DOI: 10.3390/geriatrics9030083 -
Frontiers in Digital Health 2024In the big data era, where corporations commodify health data, non-fungible tokens (NFTs) present a transformative avenue for patient empowerment and control. NFTs are...
INTRODUCTION
In the big data era, where corporations commodify health data, non-fungible tokens (NFTs) present a transformative avenue for patient empowerment and control. NFTs are unique digital assets on the blockchain, representing ownership of digital objects, including health data. By minting their data as NFTs, patients can track access, monetize its use, and build secure, private health information systems. However, research on NFTs in healthcare is in its infancy, warranting a comprehensive review.
METHODS
This study conducted a systematic literature review and thematic analysis of NFTs in healthcare to identify use cases, design models, and key challenges. Five multidisciplinary research databases (Scopus, Web of Science, Google Scholar, IEEE Explore, Elsevier Science Direct) were searched. The approach involved four stages: paper collection, inclusion/exclusion criteria application, screening, full-text reading, and quality assessment. A classification and coding framework was employed. Thematic analysis followed six steps: data familiarization, initial code generation, theme searching, theme review, theme definition/naming, and report production.
RESULTS
Analysis of 19 selected papers revealed three primary use cases: patient-centric data management, supply chain management for data provenance, and digital twin development. Notably, most solutions were prototypes or frameworks without real-world implementations. Four overarching themes emerged: data governance (ownership, tracking, privacy), data monetization (commercialization, incentivization, sharing), data protection, and data storage. The focus lies on user-controlled, private, and secure health data solutions. Additionally, data commodification is explored, with mechanisms proposed to incentivize data maintenance and sharing. NFTs are also suggested for tracking medical products in supply chains, ensuring data integrity and provenance. Ethereum and similar platforms dominate NFT minting, while compact NFT storage options are being explored for faster data access.
CONCLUSION
NFTs offer significant potential for secure, traceable, decentralized healthcare data exchange systems. However, challenges exist, including dependence on blockchain, interoperability issues, and associated costs. The review identified research gaps, such as developing dual ownership models and data pricing strategies. Building an open standard for interoperability and adoption is crucial. The scalability, security, and privacy of NFT-backed healthcare applications require further investigation. Thus, this study proposes a research agenda for adopting NFTs in healthcare, focusing on governance, storage models, and perceptions.
PubMed: 38919876
DOI: 10.3389/fdgth.2024.1377531 -
NPP-digital Psychiatry and Neuroscience 2024Reductions in default mode (DMN) connectivity strength have been reported in posttraumatic stress disorder (PTSD). However, the specificity of DMN connectivity deficits...
Reductions in default mode (DMN) connectivity strength have been reported in posttraumatic stress disorder (PTSD). However, the specificity of DMN connectivity deficits in PTSD compared to major depressive disorder (MDD), and the sensitivity of these alterations to acute stressors are not yet known. 52 participants with a primary diagnosis of PTSD ( = 28) or MDD ( = 24) completed resting-state functional magnetic resonance imaging immediately before and after a mild affective stressor. A 2 × 2 design was conducted to determine the effects of group, stress, and group*stress on DMN connectivity strength. Exploratory analyses were completed to identify the brain region(s) underlying the DMN alterations. There was significant group*stress interaction ( = 0.03), reflecting stress-induced reduction in DMN strength in PTSD ( = 0.02), but not MDD ( = 0.50). Nodal exploration of connectivity strength in the DMN identified regions of the ventromedial prefrontal cortex and the precuneus potentially contributing to DMN connectivity deficits. The findings indicate the possibility of distinct, disease-specific, patterns of connectivity strength reduction in the DMN in PTSD, especially following an experimental stressor. The identified dynamic shift in functional connectivity, which was perhaps induced by the stressor task, underscores the potential utility of the DMN connectivity and raises the question whether these disruptions may be inversely affected by antidepressants known to treat both MDD and PTSD psychopathology.
PubMed: 38919723
DOI: 10.1038/s44277-024-00011-y -
NPJ Digital Medicine Jun 2024The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an...
The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.
PubMed: 38918595
DOI: 10.1038/s41746-024-01170-0 -
Scientific Reports Jun 2024Cognitive impairment (CI) is prevalent in central nervous system demyelinating diseases, such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorders...
Cognitive impairment (CI) is prevalent in central nervous system demyelinating diseases, such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD). We developed a novel tablet-based modified digital Symbol Digit Modalities Test (MD-SDMT) with adjustable protocols that feature alternating symbol-digit combinations in each trial, lasting one or two minutes. We assessed 144 patients (99 with MS and 45 with NMOSD) using both MD-SDMT protocols and the traditional paper-based SDMT. We also gathered participants' feedback through a questionnaire regarding their preferences and perceived reliability. The results showed strong correlations between MD-SDMT and paper-based SDMT scores (Pearsons correlation: 0.88 for 2 min; 0.85 for 1 min, both p < 0.001). Among the 120 respondents, the majority preferred the digitalized SDMT (55% for the 2 min, 39% for the 1 min) over the paper-based version (6%), with the 2 min MD-SDMT reported as the most reliable test. Notably, patients with NMOSD and older individuals exhibited a preference for the paper-based test, as compared to those with MS and younger patients. In summary, even with short test durations, the digitalized SDMT effectively evaluates cognitive function in MS and NMOSD patients, and is generally preferred over the paper-based method, although preferences may vary with patient characteristics.
Topics: Humans; Male; Female; Adult; Middle Aged; Multiple Sclerosis; Neuromyelitis Optica; Neuropsychological Tests; Cognitive Dysfunction; Reproducibility of Results; Aged; Demyelinating Diseases; Surveys and Questionnaires; Young Adult; Computers, Handheld
PubMed: 38918552
DOI: 10.1038/s41598-024-65486-3 -
NPJ Digital Medicine Jun 2024Digital health technologies (DHTs) have become progressively more integrated into the healthcare of people with multiple sclerosis (MS). To ensure that DHTs meet... (Review)
Review
Digital health technologies (DHTs) have become progressively more integrated into the healthcare of people with multiple sclerosis (MS). To ensure that DHTs meet end-users' needs, it is essential to assess their usability. The objective of this study was to determine how DHTs targeting people with MS incorporate usability characteristics into their design and/or evaluation. We conducted a scoping review of DHT studies in MS published from 2010 to the present using PubMed, Web of Science, OVID Medline, CINAHL, Embase, and medRxiv. Covidence was used to facilitate the review. We included articles that focused on people with MS and/or their caregivers, studied DHTs (including mhealth, telehealth, and wearables), and employed quantitative, qualitative, or mixed methods designs. Thirty-two studies that assessed usability were included, which represents a minority of studies (26%) that assessed DHTs in MS. The most common DHT was mobile applications (n = 23, 70%). Overall, studies were highly heterogeneous with respect to what usability principles were considered and how usability was assessed. These findings suggest that there is a major gap in the application of standardized usability assessments to DHTs in MS. Improvements in the standardization of usability assessments will have implications for the future of digital health care for people with MS.
PubMed: 38918483
DOI: 10.1038/s41746-024-01162-0 -
PLOS Digital Health Jun 2024For a number of antiarrhythmics, drug loading requires a 3-day hospitalization with continuous monitoring for QT-prolongation. Automated QT monitoring with wearable ECG...
For a number of antiarrhythmics, drug loading requires a 3-day hospitalization with continuous monitoring for QT-prolongation. Automated QT monitoring with wearable ECG monitors would enable out-of-hospital care. We therefore develop a deep learning model that infers QT intervals from ECG Lead-I-the lead that is often available in ambulatory ECG monitors-and use this model to detect clinically meaningful QT-prolongation episodes during Dofetilide drug loading. QTNet-a deep neural network that infers QT intervals from Lead-I ECG-was trained using over 3 million ECGs from 653 thousand patients at the Massachusetts General Hospital and tested on an internal-test set consisting of 633 thousand ECGs from 135 thousand patients. QTNet is further evaluated on an external-validation set containing 3.1 million ECGs from 667 thousand patients at another healthcare institution. On both evaluations, the model achieves mean absolute errors of 12.63ms (internal-test) and 12.30ms (external-validation) for estimating absolute QT intervals. The associated Pearson correlation coefficients are 0.91 (internal-test) and 0.92 (external-validation). Finally, QTNet was used to detect Dofetilide-induced QT prolongation in a publicly available database (ECGRDVQ-dataset) containing ECGs from subjects enrolled in a clinical trial evaluating the effects of antiarrhythmic drugs. QTNet detects Dofetilide-induced QTc prolongation with 87% sensitivity and 77% specificity. The negative predictive value of the model is greater than 95% when the pre-test probability of drug-induced QTc prolongation is below 25%. These results show that drug-induced QT prolongation risk can be tracked from ECG Lead-I using deep learning.
PubMed: 38917157
DOI: 10.1371/journal.pdig.0000539 -
JAMIA Open Jul 2024Electronic health record textual sources such as medication signeturs (sigs) contain valuable information that is not always available in structured form. Commonly...
IMPORTANCE
Electronic health record textual sources such as medication signeturs (sigs) contain valuable information that is not always available in structured form. Commonly processed through manual annotation, this repetitive and time-consuming task could be fully automated using large language models (LLMs). While most sigs include simple instructions, some include complex patterns.
OBJECTIVES
We aimed to compare the performance of GPT-3.5 and GPT-4 with smaller fine-tuned models (ClinicalBERT, BlueBERT) in extracting the average daily dose of 2 immunomodulating medications with frequent complex sigs: hydroxychloroquine, and prednisone.
METHODS
Using manually annotated sigs as the gold standard, we compared the performance of these models in 702 hydroxychloroquine and 22 104 prednisone prescriptions.
RESULTS
GPT-4 vastly outperformed all other models for this task at any level of in-context learning. With 100 in-context examples, the model correctly annotates 94% of hydroxychloroquine and 95% of prednisone sigs to within 1 significant digit. Error analysis conducted by 2 additional manual annotators on annotator-model disagreements suggests that the vast majority of disagreements are model errors. Many model errors relate to ambiguous sigs on which there was also frequent annotator disagreement.
DISCUSSION
Paired with minimal manual annotation, GPT-4 achieved excellent performance for language regression of complex medication sigs and vastly outperforms GPT-3.5, ClinicalBERT, and BlueBERT. However, the number of in-context examples needed to reach maximum performance was similar to GPT-3.5.
CONCLUSION
LLMs show great potential to rapidly extract structured data from sigs in no-code fashion for clinical and research applications.
PubMed: 38915730
DOI: 10.1093/jamiaopen/ooae051 -
BioRxiv : the Preprint Server For... Jun 2024The mouse digit tip regenerates following amputation, a process mediated by a cellularly heterogeneous blastema. We previously found the gene Mest to be highly expressed...
The mouse digit tip regenerates following amputation, a process mediated by a cellularly heterogeneous blastema. We previously found the gene Mest to be highly expressed in mesenchymal cells of the blastema and a strong candidate pro-regenerative gene. We now show Mest digit expression is regeneration-specific and not upregulated in post-amputation fibrosing proximal digits. Mest homozygous knockout mice exhibit delayed bone regeneration though no phenotype is found in paternal knockout mice, inconsistent with the defined maternal genomic imprinting of Mest. We demonstrate that promoter switching, not loss of imprinting, regulates biallelic Mest expression in the blastema and does not occur during embryogenesis, indicating a regeneration-specific mechanism. Requirement for Mest expression is tied to modulating neutrophil response, as revealed by scRNAseq and FACS comparing wildtype and knockout blastemas. Collectively, the imprinted gene Mest is required for proper digit tip regeneration and its blastema expression is facilitated by promoter switching for biallelic expression.
PubMed: 38915675
DOI: 10.1101/2024.06.12.598713