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Journal of Integrative Neuroscience Jun 2024Perioperative neurocognitive disorders (PND) are a group of prevalent neurological complications that often occur in elderly individuals following major or emergency...
Differentially Expressed Proteins in the Serum of Elderly Patients Who Experienced Perioperative Neurocognitive Disorders Following Transurethral Resection of the Prostate.
OBJECTIVE
Perioperative neurocognitive disorders (PND) are a group of prevalent neurological complications that often occur in elderly individuals following major or emergency surgical procedures. The etiologies are not fully understood. This study endeavored to investigate novel targets and prediction methods for the occurrence of PND.
METHODS
A total of 229 elderly patients diagnosed with prostatic hyperplasia who underwent transurethral resection of the prostate (TURP) combined with spinal cord and epidural analgesia were included in this study. The patients were divided into two groups, the PND group and non-PND group, based on the Z-score method. According to the principle of maintaining consistency between preoperative and intraoperative conditions, three patients from each group were randomly chosen for serum sample collection. isobaric tags for relative and absolute quantification (iTRAQ) proteomics technology was employed to analyze and identify the proteins that exhibited differential expression in the serum samples from the two groups. Bioinformatics analysis was performed on the proteins that exhibited differential expression.
RESULTS
Among the 1101 serum proteins analyzed in the PND and non-PND groups, eight differentially expressed proteins were identified in PND patients. Of these, six proteins showed up-regulation, while two proteins showed down-regulation. Further bioinformatics analysis of the proteins that exhibited differential expression revealed their predominant involvement in cellular biological processes, cellular component formation, as well as endocytosis and phagocytosis Additionally, these proteins were found to possess the RING domain of E3 ubiquitin ligase.
CONCLUSION
The iTRAQ proteomics technique was employed to analyze the variation in protein expression in serum samples from patients with PND and those without PND. This study successfully identified eight proteins that exhibited differential expression levels between the two groups. Bioinformatics analysis indicates that proteins exhibiting differential expression are primarily implicated in the biological processes associated with microtubules. Investigating the microtubule formation process as it relates to neuroplasticity and synaptic formation may offer valuable insights for enhancing our comprehension and potential prevention of PND.
CLINICAL TRIAL REGISTRATION
Registered (ChiCTR2000028836). Date (20190306).
Topics: Humans; Male; Aged; Transurethral Resection of Prostate; Proteomics; Prostatic Hyperplasia; Neurocognitive Disorders; Postoperative Cognitive Complications; Perioperative Period; Aged, 80 and over; Blood Proteins; Computational Biology
PubMed: 38940081
DOI: 10.31083/j.jin2306123 -
Frontiers in Bioscience (Landmark... Jun 2024Existing animal models for testing therapeutics in the skin are limited. Mouse and rat models lack similarity to human skin in structure and wound healing mechanism....
BACKGROUND
Existing animal models for testing therapeutics in the skin are limited. Mouse and rat models lack similarity to human skin in structure and wound healing mechanism. Pigs are regarded as the best model with regards to similarity to human skin; however, these studies are expensive, time-consuming, and only small numbers of biologic replicates can be obtained. In addition, local-regional effects of treating wounds that are closely adjacent to one-another with different treatments make assessment of treatment effectiveness difficult in pig models. Therefore, here, a novel nude mouse model of xenografted porcine hypertrophic scar (HTS) cells was developed. This model system was developed to test if supplying hypo-pigmented cells with exogenous alpha melanocyte stimulating hormone (α-MSH) will reverse pigment loss .
METHODS
Dyschromic HTSs were created in red Duroc pigs. Epidermal scar cells (keratinocytes and melanocytes) were derived from regions of hyper-, hypo-, or normally pigmented scar or skin and were cryopreserved. Dermal fibroblasts (DFs) were isolated separately. Excisional wounds were created on nude mice and a grafting dome was placed. DFs were seeded on day 0 and formed a dermis. On day 3, epidermal cells were seeded onto the dermis. The grafting dome was removed on day 7 and hypo-pigmented xenografts were treated with synthetic α-MSH delivered with microneedling. On day 10, the xenografts were excised and saved. Sections were stained using hematoxylin and eosin hematoxylin and eosin (H&E) to assess xenograft structure. RNA was isolated and quantitative real-time polymerase chain reaction (qRT-PCR) was performed for melanogenesis-related genes , , and .
RESULTS
The seeding of HTSDFs formed a dermis that is similar in structure and cellularity to HTS dermis from the porcine model. When hyper-, hypo-, and normally-pigmented epidermal cells were seeded, a fully stratified epithelium was formed by day 14. H&E staining and measurement of the epidermis showed the average thickness to be 0.11 ± 0.07 µm 0.06 ± 0.03 µm in normal pig skin. Hypo-pigmented xenografts that were treated with synthetic α-MSH showed increases in pigmentation and had increased gene expression of , , and compared to untreated controls (TYR: 2.7 ± 1.1 0.3 ± 1.1; TYRP1: 2.6 ± 0.6 0.3 ± 0.7; DCT 0.7 ± 0.9 0.3 ± 1-fold change from control; n = 3).
CONCLUSIONS
The developed nude mouse skin xenograft model can be used to study treatments for the skin. The cells that can be xenografted can be derived from patient samples or from pig samples and form a robust dual-skin layer containing epidermis and dermis that is responsive to treatment. Specifically, we found that hypo-pigmented regions of scar can be stimulated to make melanin by synthetic α-MSH .
Topics: Animals; Mice, Nude; Cicatrix, Hypertrophic; Mice; Disease Models, Animal; Swine; alpha-MSH; Humans; Skin; Fibroblasts; Melanocytes; Keratinocytes; Transplantation, Heterologous; Wound Healing; Skin Pigmentation
PubMed: 38940034
DOI: 10.31083/j.fbl2906230 -
JACC. Advances Apr 2024The progression rate of aortic stenosis differs between patients, complicating clinical follow-up and management.
BACKGROUND
The progression rate of aortic stenosis differs between patients, complicating clinical follow-up and management.
OBJECTIVES
This study aimed to identify predictors associated with the progression rate of aortic stenosis.
METHODS
In this retrospective longitudinal single-center cohort study, all patients with moderate aortic stenosis who presented between December 2011 and December 2022 and had echocardiograms available were included. The individual aortic stenosis progression rate was calculated based on aortic valve area (AVA) from at least 2 echocardiograms performed at least 6 months apart. Baseline factors associated with the progression rate of AVA were determined using linear mixed-effects models, and the association of progression rate with clinical outcomes was evaluated using Cox regression.
RESULTS
The study included 540 patients (median age 69 years and 38% female) with 2,937 echocardiograms (median 5 per patient). Patients had a linear progression with a median AVA decrease of 0.09 cm/y and a median peak jet velocity increase of 0.17 m/s/y. Rapid progression was independently associated with all-cause mortality (HR: 1.77, 95% CI: 1.26-2.48) and aortic valve replacement (HR: 3.44, 95% CI: 2.55-4.64). Older age, greater left ventricular mass index, atrial fibrillation, and chronic kidney disease were associated with a faster decline of AVA.
CONCLUSIONS
AVA decreases linearly in individual patients, and faster progression is independently associated with higher mortality. Routine clinical and echocardiographic variables accurately predict the individual progression rate and may aid clinicians in determining the optimal follow-up interval for patients with aortic stenosis.
PubMed: 38939659
DOI: 10.1016/j.jacadv.2024.100879 -
Frontiers in Molecular Biosciences 2024This study aimed to evaluate 10 estimating glomerular filtration rate (eGFR) equations in central China population and construct a diagnostic prediction model for...
Evaluation of the clinical value of 10 estimating glomerular filtration rate equations and construction of a prediction model for kidney damage in adults from central China.
OBJECTIVES
This study aimed to evaluate 10 estimating glomerular filtration rate (eGFR) equations in central China population and construct a diagnostic prediction model for assessing the kidney damage severity.
METHODS
The concordance of 10 eGFR equations was investigated in healthy individuals from central China, and their clinical effectiveness in diagnosing kidney injury was evaluated. Subsequently, relevant clinical indicators were selected to develop a clinical prediction model for kidney damage.
RESULTS
The overall concordance between CKD-EPI and CKD-EPI was the highest (weightedκ = 0.964) in healthy population. The CG formula, CKD-EPI and CKD-EPI performed better than others in terms of concordance with referenced GFR (rGFR), but had poor ability to distinguish between rGFR < 90 or < 60 mL/min·1.73 m. This finding was basically consistent across subgroups. Finally, two logistic regression prediction models were constructed based on rGFR < 90 or 60 mL/min·1.73 m. The area under the curve of receiver operating characteristic values of two prediction models were 0.811 vs 0.846 in training set and 0.812 vs 0.800 in testing set.
CONCLUSION
The concordance of CKD-EPI and CKD-EPI was the highest in the central China population. The Cockcroft-Gault formula, CKD-EPI, and CKD-EPI more accurately reflected true kidney function, while performed poorly in the staging diagnosis of CKD. The diagnostic prediction models showed the good clinical application performance in identifying mild or moderate kidney injury. These findings lay a solid foundation for future research on renal function assessment and predictive equations.
PubMed: 38939508
DOI: 10.3389/fmolb.2024.1408503 -
JACC. Advances Aug 2023Detection of heart failure with preserved ejection fraction (HFpEF) involves integration of multiple imaging and clinical features which are often discordant or...
BACKGROUND
Detection of heart failure with preserved ejection fraction (HFpEF) involves integration of multiple imaging and clinical features which are often discordant or indeterminate.
OBJECTIVES
The authors applied artificial intelligence (AI) to analyze a single apical 4-chamber transthoracic echocardiogram video clip to detect HFpEF.
METHODS
A 3-dimensional convolutional neural network was developed and trained on apical 4-chamber video clips to classify patients with HFpEF (diagnosis of heart failure, ejection fraction ≥50%, and echocardiographic evidence of increased filling pressure; cases) vs without HFpEF (ejection fraction ≥50%, no diagnosis of heart failure, normal filling pressure; controls). Model outputs were classified as HFpEF, no HFpEF, or nondiagnostic (high uncertainty). Performance was assessed in an independent multisite data set and compared to previously validated clinical scores.
RESULTS
Training and validation included 2,971 cases and 3,785 controls (validation holdout, 16.8% patients), and demonstrated excellent discrimination (area under receiver-operating characteristic curve: 0.97 [95% CI: 0.96-0.97] and 0.95 [95% CI: 0.93-0.96] in training and validation, respectively). In independent testing (646 cases, 638 controls), 94 (7.3%) were nondiagnostic; sensitivity (87.8%; 95% CI: 84.5%-90.9%) and specificity (81.9%; 95% CI: 78.2%-85.6%) were maintained in clinically relevant subgroups, with high repeatability and reproducibility. Of 701 and 776 indeterminate outputs from the Heart Failure Association-Pretest Assessment, Echocardiographic and Natriuretic Peptide Score, Functional Testing (HFA-PEFF), and Final Etiology and Heavy, Hypertensive, Atrial Fibrillation, Pulmonary Hypertension, Elder, and Filling Pressure (H2FPEF) scores, the AI HFpEF model correctly reclassified 73.5% and 73.6%, respectively. During follow-up (median: 2.3 [IQR: 0.5-5.6] years), 444 (34.6%) patients died; mortality was higher in patients classified as HFpEF by AI (HR: 1.9 [95% CI: 1.5-2.4]).
CONCLUSIONS
An AI HFpEF model based on a single, routinely acquired echocardiographic video demonstrated excellent discrimination of patients with vs without HFpEF, more often than clinical scores, and identified patients with higher mortality.
PubMed: 38939447
DOI: 10.1016/j.jacadv.2023.100452 -
JACC. Advances Aug 2023COVID-19 is known to be associated with acute myocardial infarction (MI).
BACKGROUND
COVID-19 is known to be associated with acute myocardial infarction (MI).
OBJECTIVES
The purpose of this study was to evaluate the outcomes of 30-day readmissions for MI among survivors of COVID-19 hospitalization.
METHODS AND RESULTS
We used the U.S. Nationwide Readmission Database to identify COVID-19 admissions from April 1, 2020, to November 30, 2020, using International Classification of Diseases-10th Revision-Clinical Modification (ICD-10-CM) claims. The primary outcome was 30-day readmission incidence for MI. A total of 521,251 cases of COVID-19 were included, of which 11.6% were readmitted within 30 days of discharge. The 30-day readmission incidence for MI was 0.6%. The 30-day all-cause readmission mortality incidence was 1.3%. Patients readmitted for MI were more frequently males (61.6% vs 38.4%) and had a higher Charlson comorbidity burden score (7 vs 4). The most common diagnosis among 30-day MI readmission was type 2 MI (51.1%), followed by a diagnosis of a type 1 non-ST-segment elevation MI (41.7%). ST-segment elevation MI cases constituted 7.6% of all MI-readmission whereas 0.6% of patients had unstable angina. 30-day MI readmissions with a recurrent diagnosis of COVID-19 had higher readmission mortality and incidence of complications. Conversely, the odds of performing revascularization procedures were lower for MI with recurrent COVID-19. Furthermore, MI readmissions with recurrent COVID-19 had a higher length of stay (7 vs 5 days) and cost of hospitalization ($18,398 vs $16,191) when compared with non-COVID-19 MI readmissions.
CONCLUSIONS
Among survivors of COVID-19 hospitalization, 5.2% of all-cause 30-day readmissions and 12% of all-cause readmission mortality were attributed to MI. MI-related readmissions were a significant source of mortality, morbidity, and resource utilization.
PubMed: 38939438
DOI: 10.1016/j.jacadv.2023.100453 -
JACC. Advances Feb 2024With an increasing interest in using large claims databases in medical practice and research, it is a meaningful and essential step to efficiently identify patients with...
BACKGROUND
With an increasing interest in using large claims databases in medical practice and research, it is a meaningful and essential step to efficiently identify patients with the disease of interest.
OBJECTIVES
This study aims to establish a machine learning (ML) approach to identify patients with congenital heart disease (CHD) in large claims databases.
METHODS
We harnessed data from the Quebec claims and hospitalization databases from 1983 to 2000. The study included 19,187 patients. Of them, 3,784 were labeled as true CHD patients using a clinician developed algorithm with manual audits considered as the gold standards. To establish an accurate ML-empowered automated CHD classification system, we evaluated ML methods including Gradient Boosting Decision Tree, Support Vector Machine, Decision tree, and compared them to regularized logistic regression. The Area Under the Precision Recall Curve was used as the evaluation metric. External validation was conducted with an updated data set to 2010 with different subjects.
RESULTS
Among the ML methods we evaluated, Gradient Boosting Decision Tree led the performance in identifying true CHD patients with 99.3% Area Under the Precision Recall Curve, 98.0% for sensitivity, and 99.7% for specificity. External validation returned similar statistics on model performance.
CONCLUSIONS
This study shows that a tedious and time-consuming clinical inspection for CHD patient identification can be replaced by an extremely efficient ML algorithm in large claims database. Our findings demonstrate that ML methods can be used to automate complicated algorithms to identify patients with complex diseases.
PubMed: 38939385
DOI: 10.1016/j.jacadv.2023.100801 -
JACC. Advances Feb 2024Cardiac implantable electronic devices (CIEDs) infection remains a serious complication, causing increased morbidity and mortality. Early recognition and escalation to...
BACKGROUND
Cardiac implantable electronic devices (CIEDs) infection remains a serious complication, causing increased morbidity and mortality. Early recognition and escalation to definitive therapy including extraction of the infected device often pose challenges.
OBJECTIVES
The purpose of this study was to assess U.S.-based physicians current practices in diagnosing and managing CIED infections and explore potential extraction barriers.
METHODS
An observational survey was performed by the American College of Cardiology including U.S. physicians managing CIEDs from February to March 2022. Sampling techniques and screener questions determined eligibility. The survey featured questions on knowledge and experience with CIED infection patients and case scenarios.
RESULTS
Of 387 physicians completing the survey (20% response rate), 49% indicated familiarity with current guidelines regarding CIED infection. Electrophysiologists (EPs) (91%) were more familiar with these guidelines, compared to non-EP cardiologists (29%) and primary care physicians (23%). Only 30% of physicians specified that their institution had guideline-based protocols in place for managing patients with CIED infection. When presented with pocket infection cases, approximately 89% of EPs and 50% of non-EP cardiologists would follow guideline recommendation to do complete CIED system removal, while 70% of primary care physicians did not recommend guideline-directed treatment.
CONCLUSIONS
There are gaps in familiarity of guidelines as well as the knowledge in practical management of CIED infection with non-extracting physicians. Most institutions lack a definite pathway. Addressing discrepancies, including guideline education and streamlining care or referral pathways, will be a key factor to bridging the gap and improving CIED infection patient outcomes.
PubMed: 38939375
DOI: 10.1016/j.jacadv.2023.100773 -
Frontiers in Oncology 2024This study aims to elucidate the clinical features observed in cases of pediatric acute myeloid leukemia (AML) initially presenting with cardiac tamponade and to share...
OBJECTIVE
This study aims to elucidate the clinical features observed in cases of pediatric acute myeloid leukemia (AML) initially presenting with cardiac tamponade and to share treatment experiences.
MATERIALS AND METHODS
Five pediatric patients were initially diagnosed with AML accompanied by cardiac myeloid sarcoma (MS). The diagnosis was established by examining our hospital records and reviewing pertinent literature from 1990 to July 2023, accessible through MEDLINE/PubMed. We comprehensively assessed the clinical characteristics and treatment modalities employed for these patients.
RESULT
Five pediatric patients presented with acute symptoms, including shortness of breath, malaise, cough, and fever, leading to their hospitalization. Physical examination revealed irritability, hypoxia, tachypnea, tachycardia, and hypotension. Initial detection utilized chest X-ray or echocardiogram, leading to subsequent diagnoses based on pericardial effusion and/or bone marrow examination. Two patients received chemotherapy at the time of initial diagnosis, one with cytarabine and etoposide, and the other with cytarabine and cladribine. Post-treatment, their bone marrow achieved remission, and over a 2.5-year follow-up, their cardiac function remained favorable. Unfortunately, the remaining three patients succumbed within two weeks after diagnosis, either due to receiving alternative drugs or without undergoing chemotherapy.
CONCLUSION
This is the first and largest case series of pediatric AML patients with cardiac MS, manifesting initially with cardiac tamponade. It highlights the rarity and high mortality associated with this condition. The critical factors for reducing mortality include identifying clinical manifestations, conducting thorough physical examinations, performing echocardiography promptly, initiating early and timely pericardial drainage, and avoiding cardiotoxic chemotherapy medications.
PubMed: 38939339
DOI: 10.3389/fonc.2024.1391768 -
Frontiers in Oncology 2024Malignant pleural effusion (MPE) is prevalent among cancer patients, indicating pleural metastasis and predicting poor prognosis. However, accurately identifying MPE in...
BACKGROUND
Malignant pleural effusion (MPE) is prevalent among cancer patients, indicating pleural metastasis and predicting poor prognosis. However, accurately identifying MPE in clinical settings is challenging. The aim of this study was to establish an innovative nomogram-derived model based on clinical indicators and serum metal ion levels to identify MPE.
METHODS
From July 2020 to May 2022, 428 patients diagnosed with pleural effusion (PE) were consecutively recruited. Comprehensive demographic details, clinical symptoms, imaging data, pathological information, and laboratory results, including serum metal ion levels, were systematically collected. The nomogram was created by incorporating the most significant predictors identified through LASSO and multivariate logistic regression analysis. The predictors were assigned weighted points based on their respective regression coefficients, allowing for the calculation of a total score that corresponds to the probability of MPE. Internal validation using bootstrapping techniques assessed the nomogram's performance, including calibration, discrimination, and clinical applicability.
RESULTS
Seven key variables were identified using LASSO regression and multiple regression analysis, including dyspnea, fever, X-ray/CT compatible with malignancy, pleural carcinoembryonic antigen(pCEA), serum neuron-specific enolase(sNSE), serum carcinoembryonic antigen(sCEA), and pleural lactate dehydrogenase(pLDH). Internal validation underscored the superior performance of our model (AUC=0.940). Decision curve analysis (DCA) analysis demonstrated substantial net benefit across a probability threshold range > 1%. Additionally, serum calcium and copper levels were significantly higher, while serum zinc levels were significantly lower in MPE patients compared to benign pleural effusion (BPE) patients.
CONCLUSION
This study effectively developed a user-friendly and reliable MPE identification model incorporating seven markers, aiding in the classification of PE subtypes in clinical settings. Furthermore, our study highlights the clinical value of serum metal ions in distinguishing malignant pleural effusion from BPE. This significant advancement provides essential tools for physicians to accurately diagnose and treat patients with MPE.
PubMed: 38939338
DOI: 10.3389/fonc.2024.1431318