Course Of Disease Research Articles

Mortality and patient stratification 30 days after Staphylococcus aureus bacteraemia in patients with cardiac implantable electronic devices - a Danish nationwide cohort study

Abstract Background Staphylococcus aureus bacteraemia (SAB) is a high-risk condition with a reported 30-day mortality of up to 25% even with timely and correct treatment. Patients with cardiac implantable electronic devices (CIEDs) are at increased risk of a complicated course of disease due to the risk of device infection. Purpose We aimed to estimate the 30-day mortality rate following SAB among adult Danish patients with a de novo CIED. Furthermore, we aimed to identify patients with low, intermediate, and high mortality risk following SAB. Methods Using The National Danish Staphylococcus Aureus Bacteriemia Database and The Danish Pacemaker and ICD Register, we identified all Danish patients aged 18 to 99 years with a de novo CIED implantation between 2000 and 2020, and subsequently positive Staphylococcus aureus blood culture. The primary outcome was 30-day all-cause mortality from date of SAB. Clinical variables significantly associated with increased 30-day mortality following SAB were identified (p<0.05 and 95% CI not including 1) using adjusted multivariable Cox regression modelling. We tested variables related to age, sex, calendar year of SAB, device type, timing of infection, previous SAB, concomitant medication, and clinically relevant pre-existing co-morbidities including valvular replacement, recent surgery, and renal dialysis. Patients were awarded 1 point for each of the significant variables present, and the sum was used to stratify into low-, intermediate-, and high-risk groups. The cut-offs between the groups were set at 0 and 2 points (0 points = low risk, 1-2 points = intermediate risk, ≥3 = high risk). Results We identified 1,393 patients with de novo CIED (pacemaker: n=983, implantable cardioverter defibrillator: n=230, cardiac resynchronization therapy w/wo defibrillator capacity: n=180) and subsequent SAB (median time to SAB from CIED implantation: 679 days [IQR 168-1,525]). Median age at the time of SAB diagnosis was 77 years [IQR 68-84] with 72.4% being males. In total, 469 patients died within the first 30 days from SAB, equivalent to an overall 30-day mortality rate of 33.7% (95% CI 31.2-36.2). We identified high age, left sided valvular disease, use of systemic corticosteroids, and SAB occurring >6 months from CIED implantation to be associated with an increased hazard of 30-day mortality following the SAB diagnosis (Fig. 1). The median total sum obtained from the stratification model was 2 points [IQR 1-2]. 30-day all-cause mortality was estimated to 16.2%, 31.6% and 54.9% for the low-, intermediate- and high-risk groups, respectively (Fig. 2). Conclusions In patients with a de novo cardiac implantable electronic device and subsequent Staphylococcus aureus bacteraemia the overall 30-day mortality from date of SAB was 33.7%. Patients with high age, recent surgery, left sided valvular disease, and use of systemic corticosteroids were particularly at risk.Fig. 1.Simplified stratification modelFig. 2.30-day mortality following SAB

PI3 kinase delta governs regulatory T-cell biology and thus confers protection against atherosclerosis progression in mice

Abstract Introduction and Purpose Atherosclerosis is a chronic inflammatory disease of arteries, critically involving innate and adaptive immune cells like macrophages as well as T and B lymphocytes. Macrophages are major drivers of disease through the ingestion of lipoproteins, foam cell formation, and secretion of inflammatory mediators. Although macrophages outnumber other leukocytes in atherosclerotic plaques, T and B cells can shape the course of disease by promoting or mitigating inflammatory responses. The phosphoinositide 3-kinase delta (PI3Kd) exerts a key role in the regulation of immune responses including activation, proliferation, differentiation, and effector function of lymphocytes. Therefore, PI3Kd may represent a promising target for the modulation of inflammatory diseases. Consequently, we aimed to analyse the role of PI3Kd during atherogenesis. Methods and Results To investigate the role of haematopoietic PI3Kd in atherosclerosis, bone marrow from PI3Kd-/- or PI3Kd+/+ mice was transplanted into Ldlr-/- mice. After a 6-weeks-challenge by high fat diet, PI3Kd-/- recipient Ldlr-/- mice displayed profoundly impaired CD4+ and CD8+ T-cell numbers, CD4+ T-cell activation, CD4+ effector T-cell differentiation, and proatherogenic CD4+ T-helper (Th) 1 responses in para-aortic lymph nodes and spleen compared with PI3Kd+/+ transplanted controls. Surprisingly, the net effect of PI3Kd deficiency was a substantial increase of aortic inflammation and atherosclerosis in Ldlr-/- mice. Whereas plaque content and functions of macrophages including foam cell formation, efferocytosis, and cytokine secretion remained largely unaffected, haematopoietic PI3Kd ablation strongly reduced mature B cells and serum immunoglobulins in Ldlr-/- mice. Importantly, PI3Kd deficiency severely impaired numbers, proliferation, immunosuppressive functions, and stability of regulatory CD4+ T cells (Tregs). Consequently, adoptive transfer of PI3Kd+/+ Tregs fully restrained the atherosclerotic plaque burden in PI3Kd-/- transplanted Ldlr-/- mice without affecting B-cell numbers and serum immunoglobulins, whereas transferred PI3Kd-/- Tregs failed to relieve atherosclerosis progression. Conclusions Here, we demonstrate that PI3Kd plays a crucial role in Tregs, Th1 cells, and B cells during atherogenesis. Lack of PI3Kd signalling specifically in atheroprotective Treg responses outplays its impact on B-cell and proatherogenic Th1 responses, thus leading to aggravated atherosclerosis. Hence, PI3Kd is a key regulator of Treg biology and thereby protects against atherosclerosis, suggesting that fine-tuning PI3Kd signalling may represent a promising target for Treg-directed therapy.

Long-term effects of patisiran on survival and cardiac parameters in patients with transthyretin-mediated cardiac amyloidosis: post hoc analysis of APOLLO-B and cardiac subpopulation of APOLLO OLE

Abstract Introduction Transthyretin-mediated (ATTR) amyloidosis is a progressive, fatal disease in which the most serious manifestations are polyneuropathy and cardiomyopathy. Patients with hereditary ATTR (ATTRv; v for variant) amyloidosis commonly develop a mixed phenotype, and patients with wild-type ATTR amyloidosis predominantly have cardiomyopathy, although polyneuropathy may coexist. Patisiran, an RNAi therapeutic that rapidly knocks down TTR, has shown long-term benefit on measures of polyneuropathy in the APOLLO open-label extension (OLE) study in patients with ATTRv amyloidosis. Purpose To evaluate the long-term benefit of patisiran on survival, hospitalisations and cardiac parameters in a pooled cohort of patients with ATTR amyloidosis and evidence of cardiac involvement, across the patisiran clinical programme (Phase [Ph] 2 launched in 2012). Methods Post hoc analysis of pooled data from cardiac subpopulations of patients with ATTRv amyloidosis and polyneuropathy from 5-year Global OLE (Ph 2 OLE and Ph 3 APOLLO; patients with baseline left ventricular [LV] wall thickness ≥13 mm; absence of history of aortic valve disease or hypertension), and Ph 3 APOLLO-B (patients with wild-type or ATTRv cardiac amyloidosis). Patients received patisiran or placebo every 3 weeks for 18 months in APOLLO and 12 months in APOLLO-B; all patients received patisiran thereafter. Analyses included Kaplan-Meier estimates and Cox regression of survival and all-cause hospitalisations, and summary statistics of cardiac biomarkers and echocardiographic parameters by initial treatment arm. Results Pooled analysis included 496 patients (initial arm placebo, n=214; initial arm patisiran, n=282). Compared with placebo, patients initially receiving patisiran had better long-term survival and fewer hospitalisations (hazard ratio [95% confidence interval] over 84 months for all-cause mortality and all-cause hospitalisations: 0.59 [0.37–0.93] [Figure 1] and 0.77 [0.60–0.99], respectively). At baseline, NT-proBNP and troponin I levels, peak longitudinal strain and LV wall thickness were comparable between patisiran vs placebo-treated patients. Placebo-treated patients showed worsening of all these parameters whilst on placebo; the rates of worsening decreased once the patients initiated patisiran. In contrast, patients who initially received patisiran demonstrated relative stability over 84 months in the Global OLE and significant benefit compared with those initially treated with placebo. Conclusion Long-term benefit of patisiran in patients with cardiomyopathy was observed on survival, hospitalisations, cardiac biomarkers and echocardiographic parameters. Outcomes were significantly more favourable for those initially randomised to patisiran than placebo, highlighting the impact of initiating treatment early in the course of disease.

Detection of ATTR cardiac amyloidosis using a novel artificial intelligence algorithm for wearable-adapted noisy single-lead electrocardiograms

Abstract Background Amyloid cardiomyopathy (ATTR-CM) is often underdiagnosed, with very few diagnosed before the onset of symptoms, leading to delayed use of disease-modifying therapies that could have substantial prognostic implications early in the disease course. In the US, the disease has a substantially higher prevalence among Black adults, who are further challenged by lower access to healthcare services and lower preventative care, further reducing the ability for clinician-led diagnosis. We sought to develop an approach for identifying ATTR-CM on noisy single-lead ECGs obtainable on portable and wearable ECG devices, allowing broad use in community screening. Purpose To develop a portable/wearable device-adapted AI-ECG algorithm capable of detecting ATTR-CM on noisy single-lead ECGs. Methods We identified patients with ATTR-CM from 2015 through June 2023 across 5 hospitals of a large U.S.-based hospital system using positive bone scintigraphy scans or pharmacotherapy with an approved transthyretin stabilizer. In the development cohort, we used lead I of 12 lead ECGs, commonly captured by portable and wearable ECG devices, to train a novel noise-adapted model explicitly designed to infer information against simulated real-world noises. For this, ECG signals were augmented using random Gaussian real-world noise within four frequency ranges at multiple signal-to-noise ratios. We tested the model in an independent set of cases and matched controls drawn from July through December 2023. Results The development cohort consisted of 1,011 ECGs from 234 patients (median age 79 years [IQR:70-85], 17% women), with 10:1 age- and sex-matched 10,110 controls with 10,110 ECGs (age 79 [IQR:70-85] years 17.7% female). In the independent test set of 139 ECGs from 47 patients (age 80 [75-86] years, 32% women) and matched controls (1390 ECGs and patients) from July through December 2023, the AUROC (area under the receiver operating characteristic curve) of the AI-ECG model for ATTR-CM was 0.90 [95%CI: 0.88-0.92] (A). The AUPRC was 0.44 [0.36-0.53]. The sensitivity and specificity of the model were 0.85 and 0.80. The positive predictive value ranged from 0.12 at a 3% prevalence level to 0.59 at a 25% prevalence (B). Conclusions A novel portable and wearable-devices adapted model demonstrates promising performance for detecting ATTR-CM on single-lead ECGs, representing a more accessible method for screening in community-dwelling adults.

Baricitinib in polymyalgia rheumatica and giant cell arteritis: report of six cases.

The objective of this case series is to describe the efficacy and safety of baricitinib (BARI) in a group of patients with polymyalgia rheumatica (PMR) and/or giant cell arteritis (GCA). These patients were treated with BARI due to either a refractory disease course or the unavailability of tocilizumab because of the pandemic. A total of six patients (five females and one male, median age 64 years, range 50-83) were treated with BARI. Two of them had isolated PMR, two had PMR with associated large vessel (LV)-GCA, one had LV-GCA presenting as fever of unknown origin, and one had cranial-GCA. All patients reported improvement with BARI. At the time of starting BARI, patients were taking a median prednisone dose of 8.75 mg/day (range 0-25), and the four patients with PMR had a median PMR-AS of 23.3 (indicating high disease activity), which decreased to 1.58 after 6 months of treatment with BARI. Two of them could stop glucocorticoids (GC) and continued BARI monotherapy. One patient suffered from pneumonia, and BARI was therefore stopped. No other adverse events attributable to BARI were detected. Our case series supports previous reports suggesting efficacy of Janus kinase inhibitors as a GC-sparing strategy in PMR and GCA.

Guideline-directed medical therapy titration for heart failure with ischaemic aetiology and its effect on cardiac remodelling and cardiovascular mortality-from a real world perspective

Abstract Background Contemporary Heart Failure (HF) pharmacological treatment has been reshaped by several landmark trials in recent years, and available evidence strongly encourages treatment up-titration to target doses. Recent literature regarding treatment sequencing demonstrated positive effects of up-titration on major outcomes regardless of HF aetiology. Purpose We investigated a contemporary Heart Failure with Reduced Ejection Fraction (HFrEF) patient cohort and ischaemic aetiology and sought to understand the effects both in terms of echocardiographic remodelling and upon mortality for cardiovascular (CV) causes of contemporary ESC guideline-directed medical therapy (GDMT) on a real-world level. Methods We retrospectively analysed data of consecutive patients with HFrEF and ischaemic genesis followed in our tertiary HF clinic between January 2019 and January 2022. Eligible patients were stratified into two groups: patients treated or not with full doses of ESC GDMT [including angiotensin-converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARB) or angiotensin receptor-neprilysin inhibitors (ARNI), beta-blockers, mineralocorticoid receptor antagonists (MRA) and sodium-glucose cotransporter-2 inhibitors (SGLT2i)]. Results Overall, 203 patients (mean age 70.1±12.3 years, 165 males) were included into the analysis. Over a mean follow-up of 1223±221.2 days, 115 (56.6) patients achieved the full recommended doses of each drug. Patients with an unsuccessful up-titration had higher end-diastolic volume at transthoracic echocardiography (p for difference at first and second follow-up <0.001; figure 1, panel A), lower left ventricular ejection fraction (40.1±4.3% vs 44.3±7.8 and 38.7±4.9% vs 42.3±5.6% at the first and second follow-up, respectively) and higher CV mortality rates compared to those treated with the maximal doses (figure 1, panel B). Conclusions Up-titration of pharmacotherapy in our real-world cohort of patients with HFrEF and ischaemic aetiology demonstrated a positive effect both on pivotal echocardiographic parameters and on CV mortality. Our data suggest that timely identification and referral of patients with coronary artery disease who fail to achieve complete positive remodelling after an acute event (or during chronic disease course) for HF contemporary treatment implementation should be envisaged.Figure 1

Improvement of left atrial function after ablation in patients with paroxysmal atrial fibrillation is associated with the presence of heart failure with preserved ejection fraction

Abstract Background Atrial fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF) often coexist and left atrial (LA) function was impaired in both AF and HFpEF. However, It remains unclear if HFpEF is linked to LA function improvement in paroxysmal atrial fibrillation (pxAF) patients post-ablation. Purpose To investigate whether the improvement of LA function after ablation in patients with pxAF combined with HFpEF is better than that in patients without HFpEF. Methods 147 patients with pxAF were enrolled and HFpEF was ascertained based on the H2FPEF score. All patients underwent transthoracic echocardiography (TTE) at baseline and 3 months after ablation. Left atrial volume index (LAVI), left atrial ejection fraction (LAEF) and left atrial peak reservoir strain (LA RS) were measured. Improvement of left atrial function is defined as the difference in the above 3 indicators at baseline and 3 months after ablation. The change of the above atrial functional parameters was compared between patients with high-probability of HFpEF [hp-HFpEF] and medium/low-probability of HFpEF [lp-HFpEF]) in univariate and multivariate analysis. Statistical analyses were conducted using independent samples t-tests, Mann-Whitney U tests, and ANCOVA. Results 147 patients were included (30 hp-HFpEF, 117 lp-HFpEF, mean age 62.6 years, 63.3% men, mean BMI 25.54kg/㎡, mean disease course 28.2 months, mean CHA2DS2-VASc score 1.97). In the univariate analysis, the following factors were significantly different between hp-HFpEF and lp-HFpEF, including BMI (26.95±3.71 vs. 25.18±3.00, p=0.007), CHA2DS2-VASc score (3[3-4] vs. 2[1-2], p＜0.001), LA function at baseline including LAVI (41.59±11.38 vs. 32.57[27.68-41.10], p=0.003), LAEF (45.97±10.26 vs. 57.23±9.08, p＜0.001), LA RS (26.43±10.68 vs. 34.43±10.60, p＜0.001), and difference at baseline and 3 months after ablation in LA function including LAVI (4.92±1.08 vs. 3.33±1.18, p＜0.001), LAEF (13.41±9.71 vs. 2.98±9.69, p＜0.001), LA RS (23.61±10.23 vs. 7.29±6.91, p＜0.001), and in left ventricular (LV) TTE indicators including E/e’ (3.10±2.30 vs. -0.32±2.68, p＜0.001), LV ejection fraction (10.5[7.0-16.5] vs. 2.0[-5.0-6.0], p＜0.001), LV global longitudinal strain (14.94±4.27 vs. 5.15[2.63-8.30], p＜0.001) and LV mass (17.79±28.67 vs 1.50[-8.75-17.00], p=0.006). After adjusted for BMI, CHA2DS2-VASc score, LA function at baseline and difference at baseline and 3 months after ablation in LV TTE indicators, the improvement of LA function 3 months after ablation in patients with hp-HFpEF is better than that in patients with lp-HFpEF: LAVI significantly decreased (4.24±0.21 vs. 3.46± 0.09, p＜0.001), LAEF significantly increased (12.90±2.13 vs. 3.09±0.86, p＜0.001) and LA RS significantly increased (21.44±1.81 vs. 8.02±0.76, p＜0.001) in hp-HFpEF compared with lp-HFpEF. Conclusion Patients with pxAF with hp-HFpEF showed better improvement in LA function after ablation than those with Ip-HFpEF.

Lipid-associated GWAS loci as important markers of the risk, severity, and clinical course of peripheral artery disease

ABSTRACT Background This study investigated the relationship between lipid-associated loci identified through genome-wide association studies (GWAS) and the risk of peripheral artery disease (PAD), its severity, as well as clinical and laboratory features. Research design and methods A study included 1263 unrelated Russian subjects, consisting of 620 patients diagnosed with PAD and 643 healthy controls. Thirteen single nucleotide polymorphisms (SNP) were genotyped using the MassArray-4 system. Results Polymorphisms rs1689800, rs55730499 and rs881844 were found to be associated with an increased risk of PAD, whereas SNPs rs1883025, rs3136441, rs3764261 and rs6065906 showed protective effects against disease (Pperm ≤ 0.05). SNPs rs1689800, rs217406, rs1883025, and rs3136441 exhibited combined effects with cigarette smoking on the PAD risk (Pperm ≤ 0.05). Polymorphisms rs55730499 (beta = 0.124, Pperm = 0.04), rs9987289 (beta = 0.558, Pperm = 0.03), and rs881844 beta = −0.171, Pperm = 0.03) correlated with the ankle-brachial index. Multiple associations have been found between the SNPs and clinically significant characteristics, including disease severity, risk of gangrene, early disease onset, plasma procoagulant and atherogenic lipid changes (Pperm ≤ 0.05). Conclusions We identified novel genetic markers associated with PAD susceptibility and disease-related clinical and laboratory features. The identified biomarkers enhance the potential for predictive genetic testing related to the risk and progression of PAD, facilitating the integration of molecular diagnostics into clinical decision-making processes.

Updates in Immunotherapy for Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with limited effective therapeutic options. Due to a variety of cancer cell-intrinsic factors, including KRAS mutations, chemokine production, and other mechanisms that elicit a dysregulated host immune response, PDAC is often characterized by poor immune infiltration and an immune-privileged fibrotic stroma. As understanding of the tumor microenvironment (TME) evolves, novel therapies are being developed to target immunosuppressive mechanisms. Immune checkpoint inhibitors have limited efficacy when used alone or with radiation. Combinations of immune therapies, along with chemotherapy or chemoradiation, have demonstrated promise in preclinical and early clinical trials. Despite dismal response rates for immunotherapy for metastatic PDAC, response rates with neoadjuvant immunotherapy are somewhat encouraging, suggesting that incorporation of immunotherapy in the treatment of PDAC should be earlier in the disease course. Precision therapy for PDAC may be informed by advances in transcriptomic sequencing that can identify immunophenotypes, allowing for more appropriate treatment selection for each individual patient. Personalized and antigen-specific therapies are an increasing topic of interest, including adjuvant immunotherapy using personalized mRNA vaccines to prevent recurrence. Further development of personalized immune therapies will need to balance precision with generalizability and cost.

Bibliometric and Content Analysis of Articles on Artificial Intelligence in Healthcare

The use of artificial intelligence in the healthcare sector is becoming widespread for reasons such as analyzing digital patient data, including it in decision-making processes, improving the quality of healthcare services, and providing cost, time, and access advantages. This study aims to evaluate published articles on bibliometric indicators and the use of artificial intelligence in the healthcare sector and examine the content of the most cited articles. Articles about artificial intelligence in the health sector in the Web of Science database were included in the study using the criteria of “keyword, publication year, and publication language”. The research covers 2,680 articles published in English by 14,195 authors from 106 countries in 1084 journals between 2020-2024. 4,671 different keywords were used in the published articles. The country that published the most was “USA”, the journal was “Journal of Medical Internet Research”, the author was “Meng Ji”, and the most cited author was “Weihua Li”. The 55 most cited (≥50) articles focused on themes related to “diagnosis of COVID-19 disease”, “diagnosis of diseases”, “detection and classification of cancerous cells”, “identification of disease risk factors and disease prediction”, “prediction of treatment outcomes”, “prediction of disease course”, “personalized treatment recommendations”, “decision-making processes”, “ethical considerations, risks, and responsibilities”. With the COVID-19 pandemic, it is seen that the number of articles on artificial intelligence in the healthcare sector has increased exponentially. In the research, articles related to artificial intelligence in the health sector were examined, and a framework was created for researchers by revealing the most publishing countries, journals, authors, most cited authors, and keywords that were used the most.

First reported case of thymoma-associated multiorgan autoimmunity induced by COVID-19.

Thymoma-associated multiorgan autoimmunity (TAMA) presents with skin symptoms similar to those of graft-versus-host disease (GVHD), liver dysfunction, and enteritis, in the absence of a history of hematopoietic stem cell or bone marrow transplantation. TAMA is a type of paraneoplastic syndrome associated with thymoma. Its etiology is unclear but is thought to be a result of breakdown of immune tolerance. Histopathologically, TAMA is characterized by epidermal acanthosis with parakeratosis, individual cell keratinization, liquefaction degeneration, and intraepidermal infiltration of CD8-positive lymphocytes. A 64-year-old female patient with a history of myasthenia gravis and thymoma treated with prednisolone (10 mg/day) and cyclosporine (150 mg/day) experienced erythema on her trunk after coronavirus disease 2019 (COVID-19) onset. A psoriatic drug eruption was suspected and the possible causative drug was discontinued, but the skin rash failed to improve. A skin biopsy demonstrated GVHD-like histopathological findings. Diarrhea, abdominal pain, and duodenal perforation occurred concurrently, leading to the diagnosis of TAMA. Thereafter, the patient continued prednisolone and cyclosporine in the same doses as the TAMA treatment and added topical steroids. During the disease course, candida fungemia and cytomegalovirus infection developed, resulting in the patient's death. The TAMA was considered to have been caused by the release of inflammatory cytokines, autoreactive T cell activation, and regulatory T cell dysfunction induced by COVID-19.

Intrathecal IgG and IgM synthesis correlates with neurodegeneration markers and corresponds to meningeal B cell presence in MS

Intrathecal synthesis of immunoglobulins (Igs) is a key hallmark of multiple sclerosis (MS). B cells are known to accumulate in the leptomeninges of MS patients and associate with pathology in the underlying cortex and a more severe disease course. However, the role of locally produced antibodies in MS brain pathology is poorly understood. Here, we quantified the protein levels of IgA, IgM, IgG and albumin in serum and cerebrospinal fluid (CSF) samples of 80 MS patients and 28 neurological controls to calculate Ig indices. In addition, we quantified presence of meningeal IgA+, IgM+ and IgG+ B cells in post-mortem brain tissue of 20 MS patients and 6 controls using immunostainings. IgM and IgG, but not IgA, indices were increased in CSF of MS patients compared to controls, with no observed differences between MS disease types. Both IgM and IgG indices correlated significantly with neurofilament light (NfL) levels in CSF, but not with clinical or radiological parameters of disease. Similarly, IgG+ and IgM+ B cells were increased in MS meninges compared to controls, whereas IgA+ B cells were not. Neuronal loss did not differ between sections with low or high IgA+, IgM+ and IgG+ B cells, but was increased in sections with high numbers of all CD19+ meningeal B cells. Similarly, high presence of CD19+ meningeal B cells and IgG+ meningeal B cells associated with increased microglial density in the underlying cortex. Taken together, intrathecal synthesis of IgG and IgM is elevated in MS, which corresponds to an increased number of IgG+ and IgM+ B cells in MS meninges. The significant correlation between intrathecal IgG and IgM production and NfL levels, and increased microglial activation in cortical areas adjacent to meningeal infiltrates with high levels of IgG+ B cells indicate a role for intrathecal IgM- and IgG-producing B cells in neuroinflammatory and degenerative processes in MS.

Radiomics-Based Machine Learning with Natural Gradient Boosting for Continuous Survival Prediction in Glioblastoma

(1) Background: Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with an aggressive disease course that requires accurate prognosis for individualized treatment planning. This study aims to develop and evaluate a radiomics-based machine learning (ML) model to estimate overall survival (OS) for patients with GBM using pre-treatment multi-parametric magnetic resonance imaging (MRI). (2) Methods: The MRI data of 865 patients with GBM were assessed, comprising 499 patients from the UPENN-GBM dataset and 366 patients from the UCSF-PDGM dataset. A total of 14,598 radiomic features were extracted from T1, T1 with contrast, T2, and FLAIR MRI sequences using PyRadiomics. The UPENN-GBM dataset was used for model development (70%) and internal validation (30%), while the UCSF-PDGM dataset served as an external test set. The NGBoost Survival model was developed to generate continuous probability estimates as well as predictions for 6-, 12-, 18-, and 24-month OS. (3) Results: The NGBoost Survival model successfully predicted survival, achieving a C-index of 0.801 on internal validation and 0.725 on external validation. For 6-month OS, the model attained an AUROC of 0.791 (95% CI: 0.742–0.832) and 0.708 (95% CI: 0.654–0.748) for internal and external validation, respectively. (4) Conclusions: The radiomics-based ML model demonstrates potential to improve the prediction of OS for patients with GBM.

MACHINE-LEARNING TECHNIQUES IN MULTIPLE SCLEROSIS PREDICTION USING EEG

The diagnosis and quantification of Multiple Sclerosis (MS) have typically depended on skilled doctors recognizing visual patterns, such as Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG), which resulted in a costly, time-consuming and non-reproducible process. The application of Machine Learning (ML) in MS diagnosis has been getting a lot of attention in the last few years due to the volume of scientific data, the heterogeneity of disease courses, and the variety of diagnostic methods. The EEG has the capability to detect important changes in the brain’s inherent electrical activity, which are influenced by changes in the neural network connections associated with inflammatory demyelinating and neural damage characteristic of the MS. Utilizing multimodal machine learning over the clinically available data may be a contemporary strategy with amazing potential to facilitate early diagnosis. Considering recent EEG investigations as well as the accessibility to their datasets would be the initial steps in utilizing the ML in MS diagnosis. This paper provides a systematic review of the latest techniques for MS diagnostic based on PRISMA guidelines with the prospect of ML application in their investigations. The goal is to find if EEG could be considered a robust and accurate technique for MS diagnosis. In accordance with PRISMA guidelines, we consider 111 papers. In our review, 404 people are considered including 209 with MS and 195 healthy controls. As a result, we generated an updated investigation looking at the ML approaches as well as utilizing EEG as an accurate, but less often used method to help with early diagnosis of MS. We summarize, analyze, discuss, and synthesize the recently published works, current trends, and open research issues. The review also points out knowledge gaps about the necessity of validating results and addressing constraints such as limited sample number. Our investigation proves that the precision of the supervised strategies such as [Formula: see text]NN and SVM is typically higher than that of the unsupervised strategies. On the other hand, by utilizing various techniques such as splitting EEG signal sub-bands, signal windowing, and identifying effective features from the data analysis approaches, we have been able to achieve significant classification accuracy higher than 99%. According to the high degree of accuracy of the results, this approach is becoming the focal point of the research works. The high diagnostic accuracy of the proposed machine learning techniques on the EEG signal analysis shows its potential capacity to become a more widespread procedure as the MS diagnostic techniques. To develop the reliability of these methods, gathering, and analyzing more EEG signals from MS patients and creating more suitable EEG protocols are essential in future studies. In the same way, for the dynamic and online analyses of the EEG signals, in-depth studies are needed to determine more effective EEG protocols and machine-learning techniques.

Study on the clinical effect of meridian massage in the treatment of lumbar disc herniation

To observe the clinical efficacy of meridian massage in the treatment of lumbar disc herniation(LDH). Between July 2020 and April 2023, 82 patients with lumbar disc herniation were selected, including 58 males and 24 females, aged from 23 to 55 years old with an average of (43.76±6.64) years old. According to the different treatment methods, they were divided into observation group and control group with 41 cases in each group. The control group was treated with routine treatment, and the observation group was treated with meridian massage on the basis of routine treatment. In the control group, there were 30 males and 11 females;aged from 22 to 52 years old with an average of (42.27±9.34) years old;the Body mass index (BMI) ranged from 19 to 28 kg·m-2 with an average of(23.82±1.08) kg·m-2;the course of disease ranged from 0.5 to 3.0 years (2.40±0.48) years. There were 28 cases in L4,5 segment and 13 cases in L5S1 segment. In the observation group, there were 28 males and 13 females;the age ranged from 19 to 54 years old (42.19±9.26) years old;the BMI ranged from 18 to 29 kg·m-2 with an average of(23.73±1.15) kg·m-2;the course of disease ranged from 0.6 to 2.8 with an average of(2.56±0.45) years;there were 26 cases in L4,5 segment and 15 cases in L5S1 segment. Visual analogue scale(VAS), Oswestry disability index(ODI), M-JOA score and TCM syndrome score were measured before and after 3 courses of treatment, and the clinical efficacy was evaluated by the standard of curative effect evaluation. After treatment, VAS [(3.24±1.45) vs(4.46±0.64)], ODI [(11.45±1.98)% vs (17.21±2.74)%] and TCM symptom score [(2.03±0.27) vs (3.99± 0.54)] of the observation group were lower than those of the control group. The score of M-JOA [(23.43±2.61) vs (19.37±1.62)] increased (P<0.05). The scores of VAS, ODI and TCM symptoms in the observation group were lower than those in the control group, while the scores of M-JOA were higher than those in the control group (P<0.05). Meridian massage is effective in the treatment of LDH, which can effectivelyrelieve low back pain, improve clinical symptoms and increaselumbar function, which is worthy of clinical promotion.

Clinical study of isthmic spondylolisthesis treated with Mis-TLIF assisted by preoperative posture reduction and intraoperative lifting reduction

To investigate the clinical effect of minimally invasive transforaminal lumbar interbody fusion(Mis-TLIF) technique combined with preoperative position reduction in the treatment of spondylolisthesis and summarize its advantages. Between July 2016 and July 2022, 60 patients with lumbar isthmic spondylolisthesis were retrospectively analyzed, including 26 males and 34 females, with an average age of (51.32±4.24) years old ranging from 35 to 72 years old. They were divided into observation group and control group according to the operation methods. There were 30 patients in the observation group, including 12 males and 18 females;the age ranged from 35 to 71 years old with an average of(51.80±6.38) years old, the course of disease ranged from 12 to 60 months with an average of (24.17±1.98) months;there were 18 cases of L4 spondylolisthesis and 12 cases of L5 spondylolisthesis;according to Meyerding classification, there were 20 cases of grade Ⅰ spondylolisthesis and 10 cases of gradeⅡ. The observation group was treated with preoperative postural reduction combined with intraoperative reduction assisted minimally invasive transforaminal lumbar fusion via Quadrant channel(Mis-TLIF). There were 30 patients in the control group, including 14 males and 16 females, with an average of (50.00±4.24) years old ranging from 36 to 72 years old;the course of disease ranged from 12 to 60 months with an average of (23.70±1.53) months;there were 16 cases of L4 spondylolisthesis and 14 cases of L5 spondylolisthesis;according to Meyerding classification, there were 19 cases of grade Ⅰ spondylolisthesis and 11 cases of grade Ⅱ. The control group was treated with open transforaminal lumbar interbody fusion(Open-TLIF). The differences of operation time, intraoperative and postoperative blood loss, hospital stay, radiation exposure time and complications between the two groups were analyzed. Visual analogue scale (VAS), Oswestry disability index (ODI) and Japanese Orthopaedic Association(JOA) score were used to evaluate the clinical effect. X-ray and CT were followed up to evaluate the interbody fusion. All patients were followed up for 12 months. There was no significant difference in operation time, VAS of low back pain, slip angle and slip rate between two groups (P>0.05). The intraoperative and postoperative blood loss in the observation group (165.50±15.56) ml and (59.17±10.59) ml were less than those in the control group (259.33±35.32) ml and (165.33 ±29.56) ml (P<0.05). The length of hospital stay in the observation group (3.53±0.68) days was less than that in the control group (5.20±0.41) days (P<0.05).The intervertebral space height, slip angle, slip rate, ODI, VAS and JOA scores were significantly improved in the two groups at the final follow-up (P<0.05). There were significant differences in ODI [(9.93±1.11)% vs (10.93±1.11)%] and JOA [ (26.07±1.01) points vs (25.43±1.25) points] between the observation group and the control group at the final follow-up (P<0.05). In the treatment of spondylolisthesis, preoperative position reduction combined with intraoperative reduction assisted Mis-Tlif technique has advantages of less trauma, less bleeding and shorter hospitalization period than traditional open surgery. It is a safe and effective technique.

High-flow nasal cannulas versus standard oxygen therapy for moderate bronchiolitis: a quasi-experimental analysis.

In the last decades none of the medical therapies investigated have shown clear efficacy in the treatment of bronchiolitis, and literature agrees on a general de-implementation of pharmacological therapies, recognizing an effective role only to nutritional support and oxygen therapy. High-flow nasal cannulas (HFNC) has become increasingly popular in the last decade, despite its lack of clear efficacy. Recent randomized controlled trials (RCT) comparing standard oxygen therapy (SOT) and HFNC did not demonstrate significant benefit of HFNC. To acquire more clinical data on HFNC efficacy we performed a retrospective, quasi-experimental analysis of patients admitted for bronchiolitis in the epidemic seasons 2021-2022 and 2022-2023. To assess the efficacy of SOT and HFNC we used a pragmatic approach, a fuzzy regression discontinuity design, which is a quasi-experimental test. Unlike RCTs, this process is not a true randomization, but may be interpreted as quasi-randomization in an observational setting. HFNC did not reduce length of oxygen therapy (LOO) nor length of hospitalization (LOS) (respectively, p: 0.383 and p: 0.454). Treatment failure was not significantly different in the treatment groups (p: 0.354). It is crucial to perform additional RCTs with uniform protocols to determine the efficacy of HFNC more accurately in the treatment of bronchiolitis. HFNC does not reduce LOO, suggesting that early use of HFNC does not change the course of disease in moderate bronchiolitis. In view of the greater complexity and higher cost, HFNC should not be routinely used as first-line treatment in children with moderate respiratory distress and mild hypoxemia.

Imaging manifestations and misdiagnosis of liposclerosing myxofibroma fumor

To focus on the imaging features of liposclerosing myxofibrous tumor (LSMFT) and diagnostic challenges to enhance clinical recognition and differential diagnosis accuracy. Retrospective analysis was conducted on the imaging and pathological data from 21 cases diagnosed with LSMFT between January 2014 and November 2022, including 14 males and 7 females (aged from 21 to 73 years; the course of disease ranged from 4 to 48 months). Patient demographics, clinical presentations, and imaging modalities including X-ray, CT, and MRI were reviewed. Pathological findings were correlated with imaging features to delineate diagnostic criteria and identify causes of misdiagnosis. All 21 patients represented primary lesions, located in 14 bilateral femurs [9 on the right and 5 on the left; 12 proximal femurs (intertrochanteric and peripheral) and 2 distal femurs], 2 proximal tibia, 2 proximal humerus, 1 proximal radius, and 1 ilium and 1 calcaneus. On X-ray and CT, all lesions showed cartographical or quasi-circular osteolytic destruction with distinct and sclerotic margins, continuous bone cortex, absence of periosteal reaction and surrounding soft tissue mass. Calcification, bone ridge and varying degrees of fat components were observed in 16 lesions, displaying mixed density;5 lesions showed ground-glass density with minimal bone ridge. On MRI, the signal intensity of the lesion was heterogeneous. T1-weighted imaging showed iso-to slightly high signal intensity, while T2-weighted imaging demonstrated unevenly high signal intensity. Fat-suppressed sequences depicted significantly elevated signal intensity within lesions, with post-contrast enhancement showing uneven patterns. 5 Cases were initially misdiagnosed as fibrous dysplasia. LSMFT is an uncommon benign bone tumor, typically localized in the proximal femur but occasionally found in other skeletal sites. Understanding its distinct imaging characteristics is crucial for accurate diagnosis. Typical cases exhibit identifiable imaging patterns, whereas atypical presentations may lead to misdiagnosis as fibrous dysplasia.

The application of artificial intelligence in diabetic retinopathy: progress and prospects

In recent years, artificial intelligence (AI), especially deep learning models, has increasingly been integrated into diagnosing and treating diabetic retinopathy (DR). From delving into the singular realm of ocular fundus photography to the gradual development of proteomics and other molecular approaches, from machine learning (ML) to deep learning (DL), the journey has seen a transition from a binary diagnosis of “presence or absence” to the capability of discerning the progression and severity of DR based on images from various stages of the disease course. Since the FDA approval of IDx-DR in 2018, a plethora of AI models has mushroomed, gradually gaining recognition through a myriad of clinical trials and validations. AI has greatly improved early DR detection, and we’re nearing the use of AI in telemedicine to tackle medical resource shortages and health inequities in various areas. This comprehensive review meticulously analyzes the literature and clinical trials of recent years, highlighting key AI models for DR diagnosis and treatment, including their theoretical bases, features, applicability, and addressing current challenges like bias, transparency, and ethics. It also presents a prospective outlook on the future development in this domain.

Digital health technology to support patient-centered shared decision making at point of care for juvenile idiopathic arthritis

Despite availability of multiple FDA approved therapies, many children with juvenile idiopathic arthritis (JIA) suffer pain and disability due to uncontrolled disease. The term JIA includes a heterogeneous set of conditions unified by chronic inflammatory arthritis, collectively affecting 1:1,000 children. When reviewing treatment options with families the rheumatologist currently refers to the experience of the average patient in relatively small controlled clinical trials, to consensus-based treatment plans, or increasingly the choice is dictated by the formulary restrictions of insurance payers. The current paradigm for treatment selection does not incorporate real-world evidence of treatment effectiveness centered to the individual patients with whom decisions are to be made. Treatment decisions based on the evidence of the average patient are not optimized to reflect the unique clinical characteristics of an individual with JIA and their disease course, nor does it account for heterogeneous treatment effects. To guide treatment choices centered around each patient, we describe a novel concept of utilizing digital health technology to bring patient-centered information into shared decision-making discussions based on comparative effectiveness analysis of electronic health record or observational clinical registry data of patients with similar characteristics. The envisioned digital tool will organize and present data relevant to the individual patient and enable evidence-based individualized treatment decision making when used in a collaborative manner with the patient family and rheumatologist. Capabilities in digital health technology, data capturing, and analytical methodologies are ripe for this endeavor. This brings the concept of a learning health system directly to the point of care.