Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate becau...Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.展开更多
<strong>Objective: </strong>To explore those differences and relationships of the initial diagnostic clinical data between confirmed cases of 2019-nCoV and suspected cases of COVID-19, and then to establis...<strong>Objective: </strong>To explore those differences and relationships of the initial diagnostic clinical data between confirmed cases of 2019-nCoV and suspected cases of COVID-19, and then to establish prediction models for predicting the probability of the first diagnosis of 2019-nCoV. <strong>Methods:</strong> A total of 81 suspected cases and 87 confirmed cases of moderate 2019-nCoV diagnosed initially in the isolation wards of the First People’s Hospital of Wuhu and the People’s Hospital of Wuwei and Wuhan Caidian Module Hospital with the help of our hospital doctors were gathered, and retrospectively analyzed. <strong>Results:</strong> The most common symptoms were fever (76.79%) and cough (64.29%) in the total of 168 cases. The median age was 45 (35 - 56) years old in the 87 confirmed cases of moderate 2019-nCoV, older than the median age 36 (29 - 50) in the 81 suspected cases. There were significant more in the former than in the latter in the incidence of myalgia, ground-glass opacity (GGO), invasions of lesion in the peripheral lobes, vascular thickening and bronchial wall thickening, interlobular septal thicking, and small pulmonary nodules. On the contrary, there were less in the former than in the latter in the total number of leukocytes and neutrophils in blood routine examination and the levels of procalcitonin (PCT). Two groups were statistically significantly different (<em>P</em> < 0.05). Multivariate logistic regression analysis showed that age, fever, myalgia, GGO, vascular thickening and bronchial wall thickening, invasions of lesion in the peripheral lobes were independent factors for identification of 2019-nCoV, and the total number of leukocytes, cough, pharyngalgia and headache were negatively related. The established mathematical equation for predicting model for predicting the probability of the first diagnosis of 2019-nCoV is: <em>P</em> = e<sup><em>x</em></sup>/(1 + e<sup><em>x</em></sup>), <em>x</em> = <span style="white-space:nowrap;">−</span>6.226 + (0.071 × ages) + (1.720 × fever) + (2.858 × myalgia) + (2.131 × GGO) + (3.000 × vascular thickening and bron-chial wall thickening) + (3.438 × invasions of lesion in the peripheral lobes) + (<span style="white-space:nowrap;">−</span>0.304 × the number of leukocytes) + (<span style="white-space:nowrap;">−</span>1.478 × cough) + (<span style="white-space:nowrap;">−</span>1.830 × pharyngalgia) + (<span style="white-space:nowrap;">−</span>2.413 × headache), where e is a natural logarithm. The area under the ROC curve (AUC) of this model was calculated to be 0.945 (0.915 - 0.976). The sensitivity is 0.920 and the specificity is 0.827 when the appropriate critical point is 0.360.<strong> Conclusions: </strong>A mathematical equation prediction model for predicting the probability of the first diagnosis of 2019-nCoV can be established based on the initial diagnostic clinical data of moderate 2019-nCoV. The prediction model is a good assistant diagnostic method for its high accurateness.展开更多
Background:Sharing biological material and clinical data from patients with uveal melanoma.Methods:Uveal melanoma is the most common intraocular malignancy in the adult population.Because uveal melanoma is primarily a...Background:Sharing biological material and clinical data from patients with uveal melanoma.Methods:Uveal melanoma is the most common intraocular malignancy in the adult population.Because uveal melanoma is primarily a sporadic cancer and familial cases are rare,it is difficult to prevent or detect it.Despite effective treatment of ocular tumors,more than 50%of patients develop incurable liver metastases mainly in the 5-10 years following the detection of the primary tumor.This cancer is relatively rare and the obtained biopsies are very small.About 20 samples are taken each year in Quebec.This provincial infrastructure is made of biological material from donors with uveal melanoma and a large clinical database.Collected tumor biopsies are used for culturing cell lines and the creation of a DNA/RNA library used for genomic and genetic studies.Results:This infrastructure plays an important role in the achievement of various research programs for a better understanding of genetic and environmental factors involved in the development of melanoma and the spread of metastasis.It allows collaboration with other researchers at a provincial,national and international level in order to make progress in basic and clinical research on uveal melanoma.Conclusions:The biological material and clinical data of this infrastructure are available upon request to VHRN members whose research project was approved by the ethics committee of the institution.展开更多
Background:Early prevention of Spontaneous Abortion(SA)is essential for the treatment of recurrent spontaneous abortion.Objective:In this retrospective study,a variety of machine learning methods were used to develop ...Background:Early prevention of Spontaneous Abortion(SA)is essential for the treatment of recurrent spontaneous abortion.Objective:In this retrospective study,a variety of machine learning methods were used to develop predictive models and diagnose the potential risk of SA.Methods:A total of 663 pregnant women participated in the case-control study,586 of which were SA patients and 77 were normal parturition women.The research data included 25 features of Traditional Chinese Medicine(TCM)constitution and clinical data related to SA.This work utilized 8 machine learning techniques including logistic regression,gradient boosting decision tree,k-nearest neighbor,classification and r-egression tree,multilayer perceptron,support vector machine,random forest and XG-Boost to predict SA.The performances of the applied models were evaluated by using the method of 10-fold cross-validation and by computing the diagnostic test characteristics,including accuracy,precision,recall,𝐹1 score,and the AUC of ROC curve.Results:The𝐹1 scores of these eight machine learning techniques were all above 97.5%.Among them,gradient boosting decision tree had the best prediction result on SA.The accuracy,precision,recall,𝐹1 score,and the AUC of ROC curve of gradient boosting decision tree were 97.9%,99%,98.6%,98.8%,and 97.3%,respectively.Conclusion:The paper has accurately predicted the risk of SA combined with TCM constitution and clinical data.展开更多
Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant ad...Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant advantages of GAs,including improved clarity,increased reader engagement,and enhanced visibility of research findings.By transforming intricate scientific data into accessible visual formats,these abstracts facilitate quick and effective knowledge transfer,crucial in clinical decision-making and patient care.However,challenges such as potential data misrepresentation due to oversimplification,the skill gap in graphic design among researchers,and the lack of standardized creation guidelines pose barriers to their widespread adoption.Additionally,while software such as Adobe Illustrator,BioRender,and Canva are commonly employed to create these visuals,not all researchers may be proficient in their use.To address these issues,we recommend that academic journals establish clear guidelines and provide necessary design training to researchers.This proactive approach will ensure the creation of high-quality GAs,promote their standardization,and expand their use in clinical reporting,ultimately benefiting the medical community and improving healthcare outcomes.展开更多
Many high quality studies have emerged from public databases,such as Surveillance,Epidemiology,and End Results(SEER),National Health and Nutrition Examination Survey(NHANES),The Cancer Genome Atlas(TCGA),and Medical I...Many high quality studies have emerged from public databases,such as Surveillance,Epidemiology,and End Results(SEER),National Health and Nutrition Examination Survey(NHANES),The Cancer Genome Atlas(TCGA),and Medical Information Mart for Intensive Care(MIMIC);however,these data are often characterized by a high degree of dimensional heterogeneity,timeliness,scarcity,irregularity,and other characteristics,resulting in the value of these data not being fully utilized.Data-mining technology has been a frontier field in medical research,as it demonstrates excellent performance in evaluating patient risks and assisting clinical decision-making in building disease-prediction models.Therefore,data mining has unique advantages in clinical big-data research,especially in large-scale medical public databases.This article introduced the main medical public database and described the steps,tasks,and models of data mining in simple language.Additionally,we described data-mining methods along with their practical applications.The goal of this work was to aid clinical researchers in gaining a clear and intuitive understanding of the application of data-mining technology on clinical big-data in order to promote the production of research results that are beneficial to doctors and patients.展开更多
Clinical data have strong features of complexity and multi-disciplinarity. Clinical data are generated both from the documentation of physicians＇ interactions with the patient and by diagnostic systems. During the ca...Clinical data have strong features of complexity and multi-disciplinarity. Clinical data are generated both from the documentation of physicians＇ interactions with the patient and by diagnostic systems. During the care process, a number of different actors and roles （physicians, specialists, nurses, etc.） have the need to access patient data and document clinical activities in different moments and settings. Thus, data sharing and flexible aggregation based on different users＇ needs have become more and more important for supporting continuity of care at home, at hospitals, at outpatient clinics. In this paper, the authors identify and describe needs and challenges for patient data management at provider level and regional- （or inter-organizational-） level, because nowadays sharing patient data is needed to improve continuity and quality of care. For each level, the authors describe state-of-the-art Information and Communication Technology solutions to collect, manage, aggregate and share patient data. For each level some examples of best practices and solution scenarios being implemented in the Italian Healthcare setting are described as well.展开更多
Background Coronary atherectomy is used to treat severely calcified coronary artery lesions which are more frequent with increasing age,but its impact in older adults has not been sufficiently examined.Methods We comp...Background Coronary atherectomy is used to treat severely calcified coronary artery lesions which are more frequent with increasing age,but its impact in older adults has not been sufficiently examined.Methods We compared adults≥18 years old who underwent coronary atherectomy during inpatient PCI in 2016–2023 from the Vizient Clinical Data Base and compared outcomes in younger(<65 years),youngest-old(65–74 years),middle-old(75–84 years),and oldest-old(≥85 years)adults.Primary outcome was in-hospital mortality,and secondary outcomes included postprocedural complications.Results Among 47,337 patients who underwent coronary atherectomy,19,862(42.0%)were younger adults and 27,475(58.0%)were older adults,including 13,583 youngest-old,10,206 middle-old,and 3,686 oldest-old adults.Compared with younger adults,youngest-old adults had higher mortality(adjusted odds ratio[aOR]=1.37,P<0.001),ischemic stroke(aOR=1.35,P=0.005),gastrointestinal hemorrhage(GIH)(aOR=1.44,P<0.001),acute kidney injury(AKI)(aOR=1.43,P<0.001),tamponade(aOR=1.86,P<0.001),and pericardiocentesis(aOR=2.32,P<0.001).Middle-old adults had higher mortality(aOR=1.80,P<0.001),GIH(aOR=1.42,P=0.002),AKI(aOR=1.63,P<0.001),tamponade(aOR=2.52,P<0.001),and pericardiocentesis(aOR=3.13,P<0.001).Oldest-old adults had the highest odds for mortality(aOR=2.03,P<0.001),GIH(aOR=1.48,P=0.016),AKI(aOR=2.26,P<0.001),tamponade(aOR=3.86,P<0.001),and pericardiocentesis(aOR=4.21,P<0.001).There was a significant interaction(P-interaction=0.035)between atherectomy and age groups with regard to the odds of in-hospital mortality.Conclusions In this large claims-based study,in-hospital mortality,GIH,AKI,tamponade,and pericardiocentesis were higher in older adults compared with younger adults,in a stepwise manner by age group.展开更多
In the health field,longitudinal studies involve the recording of clinical observations of the same sample of pa-tients over successive periods,referred to as waves.This type of database serves as a valuable source of...In the health field,longitudinal studies involve the recording of clinical observations of the same sample of pa-tients over successive periods,referred to as waves.This type of database serves as a valuable source of infor-mation and insights,particularly when examining the temporal aspect,allowing the extraction of relevant and non-obvious knowledge.The triadic concept analysis theory has been proposed to describe the ternary re-lationships between objects,attributes,and conditions.In this study,we present a methodology for exploring longitudinal health databases using both the triadic theory and triadic rules,which are similar to association rules but incorporate temporal relations.Through four case studies,we demonstrate the potential of applying triadic analysis to longitudinal databases to identify risk patterns,enhance decision-making processes,and deepen our understanding of temporal dynamics.These findings suggest a promising approach for describing longitudinal databases and obtaining insights to improve clinical decision-support systems for disease treatment.展开更多
The journal Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on"AI+BT for Big Clinical Omics Data"scheduled for publication in th...The journal Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on"AI+BT for Big Clinical Omics Data"scheduled for publication in the Autumn of 2026.展开更多
The joural Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on“AI+BT for Big Clinical Omics Data”scheduled for publication in the Autumn ...The joural Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on“AI+BT for Big Clinical Omics Data”scheduled for publication in the Autumn of 2026.This special issue seeks submissions that focus on integrating artificial intelligence(AI)and biotechnologies(BT)to largely improve the collection,modelling,analysis,and application of large-scale clinical omics data.展开更多
The journal Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on“AI+BT for Big Clinical Omics Data”scheduled for publication in the Autumn...The journal Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on“AI+BT for Big Clinical Omics Data”scheduled for publication in the Autumn of 2026.This special issue seeks submissions that focus on integrating artificial intelligence(AI)and biotechnologies(BT)to largely improve the collection,modelling,analysis,and application of large-scale clinical omics data.The goal is to address the challenges posed by the high-dimensional and dynamic nature of big clinical omics data and explore their potential to advance the diagnosis and treatment of complex diseases.展开更多
While obesity and fat intake have been associated with the risk and prognosis of epithelial ovarian cancer, the association between the lipid levels and epithelial ovarian cancer phenotype remains controversial. We co...While obesity and fat intake have been associated with the risk and prognosis of epithelial ovarian cancer, the association between the lipid levels and epithelial ovarian cancer phenotype remains controversial. We conducted a retrospective study of 349 epithelial ovarian cancer patients who received treatment at Jiangsu Cancer Hospital, China between 2011 and 2017. We analyzed age at diagnosis, blood pressure, plasma glucose content, body mass index（BMI）, lipid levels and clinical parameters. Severity of epithelial ovarian cancer was classified according to the International Federation of Gynecology and Obstetrics（FIGO） grading system. Univariate analysis of the clinical factors according to the severity of epithelial ovarian cancer was followed by logistic regression analysis to identify clinical factors significantly associated with epithelial ovarian cancer severity. Univariate analysis indicated that age,BMI, triglyceride（TG）, and high density lipoproteins（HDL） differed significantly among different stages of epithelial ovarian cancer（P〈0.05）. In the logistic regression model, elevated TG（OR： 1.883; 95% CI= 1.207-2.937）, and low HDL（OR： 0.497; 95% CI = 0.298-0.829） levels were significantly associated with the high severity epithelial ovarian cancer. Our data indicate that high TG and low HDL levels correlate with a high severity of epithelial ovarian cancer. These data provide important insight into the potential relationship between the lipid pathway and epithelial ovarian cancer phenotype and development.展开更多
Electronic machines in the guise of digital computers have transformed our world―social,family,commerce,and politics―although not yet health.Each iteration spawns expectations of yet more astonishing wonders.We wait...Electronic machines in the guise of digital computers have transformed our world―social,family,commerce,and politics―although not yet health.Each iteration spawns expectations of yet more astonishing wonders.We wait for the next unbelievable invention to fall into our lap,possibly without limit.How realistic is this?What are the limits,and have we now reached them?A recent survey in The Economist suggests that we have.It describes cycles of misery,where inflated expectations are inevitably followed,a few years later,by disillusion.Yet another Artificial Intelligence(AI)winter is coming―“After years of hype,many people feel AI has failed to deliver”.The current paper not only explains why this was bound to happen,but offers a clear and simple pathway as to how to avoid it happening again.Costly investments in time and effort can only show solid,reliable benefits when full weight is given to the fundamental binary nature of the digital machine,and to the equally unique human faculty of‘intent’.‘Intent’is not easy to define;it suffers acutely from verbal fuzziness―a point made extensively in two earlier papers:“The scientific evidence that‘intent’is vital for healthcare”and“Why Quakerism is more scientific than Einstein”.This paper argues that by putting‘intent’centre stage,first healthcare,and then democracy can be rescued.Suppose every medical consultation were supported by realistic data usage?What if,using only your existing smartphone,your entire medical history were scanned,and instantly compared,within microseconds,with up-to-the-minute information on contraindications and efficacy,from around the globe,for the actual drug you were about to receive,before you actually received it?This is real-time retrieval of clinical data―it increases the security of both doctor and patient,in a way that is otherwise unachievable.My 1980 Ph.D.thesis extolled the merits of digitising the medical record―and,just as digitisation has changed our use of audio and video beyond recognition,so a data-rich medical consultation is unprecedented―prepare to be surprised.This paper has four sections:(1)where binaries help;(2)where binaries ensure extinction;(3)computers in healthcare and civilisation;and(4)data-rich doctoring.Health is vital for economic success,as the current pandemic demonstrates,inescapably.Politics,too,is routinely corrupted―unless we rectify both,failures in AI will be the least of our troubles.展开更多
This paper deals with a stochastic approach based on the principle of the maximum entropy to investigate the effect of the parameter random uncertainties on the arterial pressure. Motivated by a hyperelastic, anisotro...This paper deals with a stochastic approach based on the principle of the maximum entropy to investigate the effect of the parameter random uncertainties on the arterial pressure. Motivated by a hyperelastic, anisotropic, and incompressible constitutive law with fiber families, the uncertain parameters describing the mechanical behavior are considered. Based on the available information, the probability density functions are attributed to every random variable to describe the dispersion of the model parameters. Numerous realizations are carried out, and the corresponding arterial pressure results are compared with the human non-invasive clinical data recorded over a mean cardiac cycle. Furthermore, the Monte Carlo simulations are performed, the convergence of the probabilistic model is proven. The different realizations are useful to define a reliable confidence region, in which the probability to have a realization is equM to 95%. It is shown through the obtained results that the error in the estimation of the arterial pressure can reach 35% when the estimation of the model parameters is subjected to an uncertainty ratio of 5%. Finally, a sensitivity analysis is performed to identify the constitutive law relevant parameters for better understanding and characterization of the arterial wall mechanical behaviors.展开更多
BACKGROUND Schizophrenic patients are prone to violence,frequent recurrence,and difficult to predict.Emotional and behavioral abnormalities during the onset of the disease,resulting in active myocardial enzyme spectru...BACKGROUND Schizophrenic patients are prone to violence,frequent recurrence,and difficult to predict.Emotional and behavioral abnormalities during the onset of the disease,resulting in active myocardial enzyme spectrum.AIM To explored the expression level of myocardial enzymes in patients with schizo-phrenia and its predictive value in the occurrence of violence.METHODS A total of 288 patients with schizophrenia in our hospital from February 2023 to January 2024 were selected as the research object,and 100 healthy people were selected as the control group.Participants’information,clinical data,and labo-ratory examination data were collected.According to Modified Overt Aggression Scale score,patients were further divided into the violent(123 cases)and non-violent group(165 cases).RESULTS The comparative analysis revealed significant differences in serum myocardial enzyme levels between patients with schizophrenia and healthy individuals.In the schizophrenia group,the violent and non-violent groups also exhibited different levels of serum myocardial enzymes.The levels of myocardial enzymes in the non-violent group were lower than those in the violent group,and the patients in the latter also displayed aggressive behavior in the past.CONCLUSION Previous aggressive behavior and the level of myocardial enzymes are of great significance for the diagnosis and prognosis analysis of violent behavior in patients with schizophrenia.By detecting changes in these indicators,we can gain a more comprehensive understanding of a patient’s condition and treatment.展开更多
OBJECTIVE: To discuss the causes and treatments of wound infections after scoliosis surgery. METHODS: Nine hundred and twenty-four caes of scoliosis were reviewed, and the clinical data of 15 cases of postoperative in...OBJECTIVE: To discuss the causes and treatments of wound infections after scoliosis surgery. METHODS: Nine hundred and twenty-four caes of scoliosis were reviewed, and the clinical data of 15 cases of postoperative infection were analysed retrospectively. RESULTS: All 15 cases underwent spinal posterior fusion with autologous bone graft using instrumentations. Seven were diagnosed as early infection, and 8 were delayed infection. Radical debridement was performed in all 15 cases. The duration of antibiotics administration was 10 to 34 days with continuous closed irrigation for 2 to approximately 4 weeks and primary closure for the wounds. All patients were followed up for an average of 3.5 years (2 to 7.5 years) with good outcomes and no recurrence. CONCLUSION: Wound infection following surgical correction of scoliosis primarily results from intraoperative seeding, although host-related and operation-related factors may contribute to its development. Once the infections are diagnosed, good results can be achieved by prompt surgical debridement, irrigation and reasonably administered antibiotics. Removal of hardware may be necessary in deep infections.展开更多
The International Committee of Medical Journal Editors （ICMJE） believes that there is an ethical obligation to responsibly share data generated by interventional clinical trials because participants have put themsel...The International Committee of Medical Journal Editors （ICMJE） believes that there is an ethical obligation to responsibly share data generated by interventional clinical trials because participants have put themselves at risk. In a growing consensus, many funders around the world - foundations, government agencies, and industry - now mandate data sharing. Here, we outline ICMJE＇s proposed requirements to help meet this obligation. We encourage feedback on the proposed requirements. Anyone can provide feedback at www. icmje.org by April 18, 2016.展开更多
Objective To investigate the clinical and genetic variation characteristics of a child with autosomal dominant lateral temporal lobe epilepsy caused by de novo variation of the MICALl gene.Methods Clinical data of the...Objective To investigate the clinical and genetic variation characteristics of a child with autosomal dominant lateral temporal lobe epilepsy caused by de novo variation of the MICALl gene.Methods Clinical data of the patient with autosomal dominant lateral temporal lobe epilepsy caused by MICALl gene variation diagnosed in Children's Hospital of Soochow University in August 2019 were collected.The whole exome sequencing was performed on the core members of the family,and the characteristics of gene variations were analyzed.Results The proband,a 10 years and 5 months old boy,was admitted to the hospital because of"intermittent convulsions for 7 years".The clinical manifestations included focal or generalized tonic-clonic seizures and hearing aura,with normal language and intellectual development.No abnormalities were found in the T,and fluid attenuated inversion recovery sequences of the cranial 3.0 T magnetic resonance imaging and 3D thinslice magnetic resonance imaging.Long-range video electroencephalogram showed the distribution of spinous and slow spinous waves in the left frontal and temporal areas.The results of whole exome gene sequencing in the core family members showed heterozygous de novo missense variation in the MICALI gene of the proband(NM_022765):c.763G>T(exon6)(p.Val255Leu)that had not been reported.According to American College of Medical Geneticsand Genomicssand Association for Molecular Pathology guidelines(2015),the mutation was considered potentially pathogenic.The application of antiepilepticdrugsswaseffectivein controllingepilepticcseizures.ConclusionAuditory symptoms are main clinical manifestations for the child with autosomal dominant lateral temporal lobe epilepsy.Antiepileptic drugs can effectively control epileptic seizures of the child,and the MICALl gene c.763G>T(p.Val255Leu)mutation is the genetic cause of the proband.展开更多
Objective To investigate the correlation between the clinical features and endoscopic ultrasound-guided portal pressure gradient(EUS-PPG)in patients with cirrhosis.Methods A total of 148 patients with cirrhosis and po...Objective To investigate the correlation between the clinical features and endoscopic ultrasound-guided portal pressure gradient(EUS-PPG)in patients with cirrhosis.Methods A total of 148 patients with cirrhosis and portal hypertension who underwent EUS-PPG measurement at the Third Xiangya Hospital of Central South University from March 15,2022 to June 20,2023 were selected.The clinical data of patients collected before EUS-PPG measurement were analyzed.Variations in the EUS-PPG across different clinical data subgroups were analyzed.Multivariate linear regression analysis was used to explore the independent factors influencing EUS-PPG.Results The EUS-PPG was significantly elevated in patients exhibiting red signs(16.62±5.33 mmHg VS 13.44±5.34 mmHg,t=3.616,P<0.001),gastroesophageal varices(15.78±5.30 mmHg VS 9.70±4.77 mmHg,t=4.247,P<0.001),hepatic encephalopathy(20.83±7.52 mmHg VS 14.92±5.35 mmHg,t=2.606,P=0.010),thrombocytopenia(15.66±5.39 mmHg VS 13.29±5.83mmHg,t=2.136,P=0.034),hypoproteinemia(16.13±5.86 mmHg VS 14.12±5.03 mmHg,t=2.230,P=0.027),and an increased international normalized ratio(16.25±6.00 mmHg VS 14.40±5.11mmHg,t=2.022,P=0.045).Conversely,the EUS-PPG was significantly reduced in patients with a history of splenectomy and devascularization(13.17±5.88mmHgVS15.73±5.34mmHg,t=-2.379,P=0.019).The EUS-PPG in patients with varying degrees of ascites(no VS slight VS moderate or severe:13.40±5.48 mmHg VS 15.90±5.49 mmHg VS 16.69±5.17 mmHg,F=5.188,P=0.007)and different Child-Pugh classifications(A VS B VS C:14.07±5.05 mmHg VS 15.69±5.74 mmHg VS 17.64±5.99 mmHg,F=3.066,P=0.049)increased gradually.Multivariable linear regression analysis showed that red signs(β=2.44,t=2.732,P=0.007),gastroesophageal varices(β=4.45,t=2.990,P=0.003),ascites(β=1.75,t=2.368,P=0.019),and hepatic encephalopathy(β=5.82,t=2.644,P=0.009)were independentftactors fortheelevated1EUS-PPG.Conclusion There is a significant correlation between EUS-PPG and the clinical features related to the severity of cirrhotic portal hypertension,which indicates the feasibility of EUS-PPG in evaluating cirrhotic portal hypertension.展开更多
文摘Heart failure prediction is crucial as cardiovascular diseases become the leading cause of death worldwide,exacerbated by the COVID-19 pandemic.Age,cholesterol,and blood pressure datasets are becoming inadequate because they cannot capture the complexity of emerging health indicators.These high-dimensional and heterogeneous datasets make traditional machine learning methods difficult,and Skewness and other new biomarkers and psychosocial factors bias the model’s heart health prediction across diverse patient profiles.Modern medical datasets’complexity and high dimensionality challenge traditional predictionmodels like SupportVectorMachines and Decision Trees.Quantum approaches include QSVM,QkNN,QDT,and others.These Constraints drove research.The“QHF-CS:Quantum-Enhanced Heart Failure Prediction using Quantum CNN with Optimized Feature Qubit Selection with Cuckoo Search in Skewed Clinical Data”system was developed in this research.This novel system leverages a Quantum Convolutional Neural Network(QCNN)-based quantum circuit,enhanced by meta-heuristic algorithms—Cuckoo SearchOptimization(CSO),Artificial BeeColony(ABC),and Particle SwarmOptimization(PSO)—for feature qubit selection.Among these,CSO demonstrated superior performance by consistently identifying the most optimal and least skewed feature subsets,which were then encoded into quantum states for circuit construction.By integrating advanced quantum circuit feature maps like ZZFeatureMap,RealAmplitudes,and EfficientSU2,the QHF-CS model efficiently processes complex,high-dimensional data,capturing intricate patterns that classical models overlook.The QHF-CS model improves precision,recall,F1-score,and accuracy to 0.94,0.95,0.94,and 0.94.Quantum computing could revolutionize heart failure diagnostics by improving model accuracy and computational efficiency,enabling complex healthcare diagnostic breakthroughs.
文摘<strong>Objective: </strong>To explore those differences and relationships of the initial diagnostic clinical data between confirmed cases of 2019-nCoV and suspected cases of COVID-19, and then to establish prediction models for predicting the probability of the first diagnosis of 2019-nCoV. <strong>Methods:</strong> A total of 81 suspected cases and 87 confirmed cases of moderate 2019-nCoV diagnosed initially in the isolation wards of the First People’s Hospital of Wuhu and the People’s Hospital of Wuwei and Wuhan Caidian Module Hospital with the help of our hospital doctors were gathered, and retrospectively analyzed. <strong>Results:</strong> The most common symptoms were fever (76.79%) and cough (64.29%) in the total of 168 cases. The median age was 45 (35 - 56) years old in the 87 confirmed cases of moderate 2019-nCoV, older than the median age 36 (29 - 50) in the 81 suspected cases. There were significant more in the former than in the latter in the incidence of myalgia, ground-glass opacity (GGO), invasions of lesion in the peripheral lobes, vascular thickening and bronchial wall thickening, interlobular septal thicking, and small pulmonary nodules. On the contrary, there were less in the former than in the latter in the total number of leukocytes and neutrophils in blood routine examination and the levels of procalcitonin (PCT). Two groups were statistically significantly different (<em>P</em> < 0.05). Multivariate logistic regression analysis showed that age, fever, myalgia, GGO, vascular thickening and bronchial wall thickening, invasions of lesion in the peripheral lobes were independent factors for identification of 2019-nCoV, and the total number of leukocytes, cough, pharyngalgia and headache were negatively related. The established mathematical equation for predicting model for predicting the probability of the first diagnosis of 2019-nCoV is: <em>P</em> = e<sup><em>x</em></sup>/(1 + e<sup><em>x</em></sup>), <em>x</em> = <span style="white-space:nowrap;">−</span>6.226 + (0.071 × ages) + (1.720 × fever) + (2.858 × myalgia) + (2.131 × GGO) + (3.000 × vascular thickening and bron-chial wall thickening) + (3.438 × invasions of lesion in the peripheral lobes) + (<span style="white-space:nowrap;">−</span>0.304 × the number of leukocytes) + (<span style="white-space:nowrap;">−</span>1.478 × cough) + (<span style="white-space:nowrap;">−</span>1.830 × pharyngalgia) + (<span style="white-space:nowrap;">−</span>2.413 × headache), where e is a natural logarithm. The area under the ROC curve (AUC) of this model was calculated to be 0.945 (0.915 - 0.976). The sensitivity is 0.920 and the specificity is 0.827 when the appropriate critical point is 0.360.<strong> Conclusions: </strong>A mathematical equation prediction model for predicting the probability of the first diagnosis of 2019-nCoV can be established based on the initial diagnostic clinical data of moderate 2019-nCoV. The prediction model is a good assistant diagnostic method for its high accurateness.
文摘Background:Sharing biological material and clinical data from patients with uveal melanoma.Methods:Uveal melanoma is the most common intraocular malignancy in the adult population.Because uveal melanoma is primarily a sporadic cancer and familial cases are rare,it is difficult to prevent or detect it.Despite effective treatment of ocular tumors,more than 50%of patients develop incurable liver metastases mainly in the 5-10 years following the detection of the primary tumor.This cancer is relatively rare and the obtained biopsies are very small.About 20 samples are taken each year in Quebec.This provincial infrastructure is made of biological material from donors with uveal melanoma and a large clinical database.Collected tumor biopsies are used for culturing cell lines and the creation of a DNA/RNA library used for genomic and genetic studies.Results:This infrastructure plays an important role in the achievement of various research programs for a better understanding of genetic and environmental factors involved in the development of melanoma and the spread of metastasis.It allows collaboration with other researchers at a provincial,national and international level in order to make progress in basic and clinical research on uveal melanoma.Conclusions:The biological material and clinical data of this infrastructure are available upon request to VHRN members whose research project was approved by the ethics committee of the institution.
文摘Background:Early prevention of Spontaneous Abortion(SA)is essential for the treatment of recurrent spontaneous abortion.Objective:In this retrospective study,a variety of machine learning methods were used to develop predictive models and diagnose the potential risk of SA.Methods:A total of 663 pregnant women participated in the case-control study,586 of which were SA patients and 77 were normal parturition women.The research data included 25 features of Traditional Chinese Medicine(TCM)constitution and clinical data related to SA.This work utilized 8 machine learning techniques including logistic regression,gradient boosting decision tree,k-nearest neighbor,classification and r-egression tree,multilayer perceptron,support vector machine,random forest and XG-Boost to predict SA.The performances of the applied models were evaluated by using the method of 10-fold cross-validation and by computing the diagnostic test characteristics,including accuracy,precision,recall,𝐹1 score,and the AUC of ROC curve.Results:The𝐹1 scores of these eight machine learning techniques were all above 97.5%.Among them,gradient boosting decision tree had the best prediction result on SA.The accuracy,precision,recall,𝐹1 score,and the AUC of ROC curve of gradient boosting decision tree were 97.9%,99%,98.6%,98.8%,and 97.3%,respectively.Conclusion:The paper has accurately predicted the risk of SA combined with TCM constitution and clinical data.
文摘Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant advantages of GAs,including improved clarity,increased reader engagement,and enhanced visibility of research findings.By transforming intricate scientific data into accessible visual formats,these abstracts facilitate quick and effective knowledge transfer,crucial in clinical decision-making and patient care.However,challenges such as potential data misrepresentation due to oversimplification,the skill gap in graphic design among researchers,and the lack of standardized creation guidelines pose barriers to their widespread adoption.Additionally,while software such as Adobe Illustrator,BioRender,and Canva are commonly employed to create these visuals,not all researchers may be proficient in their use.To address these issues,we recommend that academic journals establish clear guidelines and provide necessary design training to researchers.This proactive approach will ensure the creation of high-quality GAs,promote their standardization,and expand their use in clinical reporting,ultimately benefiting the medical community and improving healthcare outcomes.
基金the National Social Science Foundation of China(No.16BGL183).
文摘Many high quality studies have emerged from public databases,such as Surveillance,Epidemiology,and End Results(SEER),National Health and Nutrition Examination Survey(NHANES),The Cancer Genome Atlas(TCGA),and Medical Information Mart for Intensive Care(MIMIC);however,these data are often characterized by a high degree of dimensional heterogeneity,timeliness,scarcity,irregularity,and other characteristics,resulting in the value of these data not being fully utilized.Data-mining technology has been a frontier field in medical research,as it demonstrates excellent performance in evaluating patient risks and assisting clinical decision-making in building disease-prediction models.Therefore,data mining has unique advantages in clinical big-data research,especially in large-scale medical public databases.This article introduced the main medical public database and described the steps,tasks,and models of data mining in simple language.Additionally,we described data-mining methods along with their practical applications.The goal of this work was to aid clinical researchers in gaining a clear and intuitive understanding of the application of data-mining technology on clinical big-data in order to promote the production of research results that are beneficial to doctors and patients.
文摘Clinical data have strong features of complexity and multi-disciplinarity. Clinical data are generated both from the documentation of physicians＇ interactions with the patient and by diagnostic systems. During the care process, a number of different actors and roles （physicians, specialists, nurses, etc.） have the need to access patient data and document clinical activities in different moments and settings. Thus, data sharing and flexible aggregation based on different users＇ needs have become more and more important for supporting continuity of care at home, at hospitals, at outpatient clinics. In this paper, the authors identify and describe needs and challenges for patient data management at provider level and regional- （or inter-organizational-） level, because nowadays sharing patient data is needed to improve continuity and quality of care. For each level, the authors describe state-of-the-art Information and Communication Technology solutions to collect, manage, aggregate and share patient data. For each level some examples of best practices and solution scenarios being implemented in the Italian Healthcare setting are described as well.
文摘Background Coronary atherectomy is used to treat severely calcified coronary artery lesions which are more frequent with increasing age,but its impact in older adults has not been sufficiently examined.Methods We compared adults≥18 years old who underwent coronary atherectomy during inpatient PCI in 2016–2023 from the Vizient Clinical Data Base and compared outcomes in younger(<65 years),youngest-old(65–74 years),middle-old(75–84 years),and oldest-old(≥85 years)adults.Primary outcome was in-hospital mortality,and secondary outcomes included postprocedural complications.Results Among 47,337 patients who underwent coronary atherectomy,19,862(42.0%)were younger adults and 27,475(58.0%)were older adults,including 13,583 youngest-old,10,206 middle-old,and 3,686 oldest-old adults.Compared with younger adults,youngest-old adults had higher mortality(adjusted odds ratio[aOR]=1.37,P<0.001),ischemic stroke(aOR=1.35,P=0.005),gastrointestinal hemorrhage(GIH)(aOR=1.44,P<0.001),acute kidney injury(AKI)(aOR=1.43,P<0.001),tamponade(aOR=1.86,P<0.001),and pericardiocentesis(aOR=2.32,P<0.001).Middle-old adults had higher mortality(aOR=1.80,P<0.001),GIH(aOR=1.42,P=0.002),AKI(aOR=1.63,P<0.001),tamponade(aOR=2.52,P<0.001),and pericardiocentesis(aOR=3.13,P<0.001).Oldest-old adults had the highest odds for mortality(aOR=2.03,P<0.001),GIH(aOR=1.48,P=0.016),AKI(aOR=2.26,P<0.001),tamponade(aOR=3.86,P<0.001),and pericardiocentesis(aOR=4.21,P<0.001).There was a significant interaction(P-interaction=0.035)between atherectomy and age groups with regard to the odds of in-hospital mortality.Conclusions In this large claims-based study,in-hospital mortality,GIH,AKI,tamponade,and pericardiocentesis were higher in older adults compared with younger adults,in a stepwise manner by age group.
文摘In the health field,longitudinal studies involve the recording of clinical observations of the same sample of pa-tients over successive periods,referred to as waves.This type of database serves as a valuable source of infor-mation and insights,particularly when examining the temporal aspect,allowing the extraction of relevant and non-obvious knowledge.The triadic concept analysis theory has been proposed to describe the ternary re-lationships between objects,attributes,and conditions.In this study,we present a methodology for exploring longitudinal health databases using both the triadic theory and triadic rules,which are similar to association rules but incorporate temporal relations.Through four case studies,we demonstrate the potential of applying triadic analysis to longitudinal databases to identify risk patterns,enhance decision-making processes,and deepen our understanding of temporal dynamics.These findings suggest a promising approach for describing longitudinal databases and obtaining insights to improve clinical decision-support systems for disease treatment.
文摘The journal Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on"AI+BT for Big Clinical Omics Data"scheduled for publication in the Autumn of 2026.
文摘The joural Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on“AI+BT for Big Clinical Omics Data”scheduled for publication in the Autumn of 2026.This special issue seeks submissions that focus on integrating artificial intelligence(AI)and biotechnologies(BT)to largely improve the collection,modelling,analysis,and application of large-scale clinical omics data.
文摘The journal Genomics,Proteomics&Bioinformatics(GPB)invites leading scholars to contribute high-quality manuscripts for a special issue on“AI+BT for Big Clinical Omics Data”scheduled for publication in the Autumn of 2026.This special issue seeks submissions that focus on integrating artificial intelligence(AI)and biotechnologies(BT)to largely improve the collection,modelling,analysis,and application of large-scale clinical omics data.The goal is to address the challenges posed by the high-dimensional and dynamic nature of big clinical omics data and explore their potential to advance the diagnosis and treatment of complex diseases.
基金supported by Jiangsu Cancer Hospital (ZK201606ZK201610)
文摘While obesity and fat intake have been associated with the risk and prognosis of epithelial ovarian cancer, the association between the lipid levels and epithelial ovarian cancer phenotype remains controversial. We conducted a retrospective study of 349 epithelial ovarian cancer patients who received treatment at Jiangsu Cancer Hospital, China between 2011 and 2017. We analyzed age at diagnosis, blood pressure, plasma glucose content, body mass index（BMI）, lipid levels and clinical parameters. Severity of epithelial ovarian cancer was classified according to the International Federation of Gynecology and Obstetrics（FIGO） grading system. Univariate analysis of the clinical factors according to the severity of epithelial ovarian cancer was followed by logistic regression analysis to identify clinical factors significantly associated with epithelial ovarian cancer severity. Univariate analysis indicated that age,BMI, triglyceride（TG）, and high density lipoproteins（HDL） differed significantly among different stages of epithelial ovarian cancer（P〈0.05）. In the logistic regression model, elevated TG（OR： 1.883; 95% CI= 1.207-2.937）, and low HDL（OR： 0.497; 95% CI = 0.298-0.829） levels were significantly associated with the high severity epithelial ovarian cancer. Our data indicate that high TG and low HDL levels correlate with a high severity of epithelial ovarian cancer. These data provide important insight into the potential relationship between the lipid pathway and epithelial ovarian cancer phenotype and development.
文摘Electronic machines in the guise of digital computers have transformed our world―social,family,commerce,and politics―although not yet health.Each iteration spawns expectations of yet more astonishing wonders.We wait for the next unbelievable invention to fall into our lap,possibly without limit.How realistic is this?What are the limits,and have we now reached them?A recent survey in The Economist suggests that we have.It describes cycles of misery,where inflated expectations are inevitably followed,a few years later,by disillusion.Yet another Artificial Intelligence(AI)winter is coming―“After years of hype,many people feel AI has failed to deliver”.The current paper not only explains why this was bound to happen,but offers a clear and simple pathway as to how to avoid it happening again.Costly investments in time and effort can only show solid,reliable benefits when full weight is given to the fundamental binary nature of the digital machine,and to the equally unique human faculty of‘intent’.‘Intent’is not easy to define;it suffers acutely from verbal fuzziness―a point made extensively in two earlier papers:“The scientific evidence that‘intent’is vital for healthcare”and“Why Quakerism is more scientific than Einstein”.This paper argues that by putting‘intent’centre stage,first healthcare,and then democracy can be rescued.Suppose every medical consultation were supported by realistic data usage?What if,using only your existing smartphone,your entire medical history were scanned,and instantly compared,within microseconds,with up-to-the-minute information on contraindications and efficacy,from around the globe,for the actual drug you were about to receive,before you actually received it?This is real-time retrieval of clinical data―it increases the security of both doctor and patient,in a way that is otherwise unachievable.My 1980 Ph.D.thesis extolled the merits of digitising the medical record―and,just as digitisation has changed our use of audio and video beyond recognition,so a data-rich medical consultation is unprecedented―prepare to be surprised.This paper has four sections:(1)where binaries help;(2)where binaries ensure extinction;(3)computers in healthcare and civilisation;and(4)data-rich doctoring.Health is vital for economic success,as the current pandemic demonstrates,inescapably.Politics,too,is routinely corrupted―unless we rectify both,failures in AI will be the least of our troubles.
文摘This paper deals with a stochastic approach based on the principle of the maximum entropy to investigate the effect of the parameter random uncertainties on the arterial pressure. Motivated by a hyperelastic, anisotropic, and incompressible constitutive law with fiber families, the uncertain parameters describing the mechanical behavior are considered. Based on the available information, the probability density functions are attributed to every random variable to describe the dispersion of the model parameters. Numerous realizations are carried out, and the corresponding arterial pressure results are compared with the human non-invasive clinical data recorded over a mean cardiac cycle. Furthermore, the Monte Carlo simulations are performed, the convergence of the probabilistic model is proven. The different realizations are useful to define a reliable confidence region, in which the probability to have a realization is equM to 95%. It is shown through the obtained results that the error in the estimation of the arterial pressure can reach 35% when the estimation of the model parameters is subjected to an uncertainty ratio of 5%. Finally, a sensitivity analysis is performed to identify the constitutive law relevant parameters for better understanding and characterization of the arterial wall mechanical behaviors.
基金The Shaoxing Science and Technology Plan Project Plan,No.2022A14002.
文摘BACKGROUND Schizophrenic patients are prone to violence,frequent recurrence,and difficult to predict.Emotional and behavioral abnormalities during the onset of the disease,resulting in active myocardial enzyme spectrum.AIM To explored the expression level of myocardial enzymes in patients with schizo-phrenia and its predictive value in the occurrence of violence.METHODS A total of 288 patients with schizophrenia in our hospital from February 2023 to January 2024 were selected as the research object,and 100 healthy people were selected as the control group.Participants’information,clinical data,and labo-ratory examination data were collected.According to Modified Overt Aggression Scale score,patients were further divided into the violent(123 cases)and non-violent group(165 cases).RESULTS The comparative analysis revealed significant differences in serum myocardial enzyme levels between patients with schizophrenia and healthy individuals.In the schizophrenia group,the violent and non-violent groups also exhibited different levels of serum myocardial enzymes.The levels of myocardial enzymes in the non-violent group were lower than those in the violent group,and the patients in the latter also displayed aggressive behavior in the past.CONCLUSION Previous aggressive behavior and the level of myocardial enzymes are of great significance for the diagnosis and prognosis analysis of violent behavior in patients with schizophrenia.By detecting changes in these indicators,we can gain a more comprehensive understanding of a patient’s condition and treatment.
文摘OBJECTIVE: To discuss the causes and treatments of wound infections after scoliosis surgery. METHODS: Nine hundred and twenty-four caes of scoliosis were reviewed, and the clinical data of 15 cases of postoperative infection were analysed retrospectively. RESULTS: All 15 cases underwent spinal posterior fusion with autologous bone graft using instrumentations. Seven were diagnosed as early infection, and 8 were delayed infection. Radical debridement was performed in all 15 cases. The duration of antibiotics administration was 10 to 34 days with continuous closed irrigation for 2 to approximately 4 weeks and primary closure for the wounds. All patients were followed up for an average of 3.5 years (2 to 7.5 years) with good outcomes and no recurrence. CONCLUSION: Wound infection following surgical correction of scoliosis primarily results from intraoperative seeding, although host-related and operation-related factors may contribute to its development. Once the infections are diagnosed, good results can be achieved by prompt surgical debridement, irrigation and reasonably administered antibiotics. Removal of hardware may be necessary in deep infections.
文摘The International Committee of Medical Journal Editors （ICMJE） believes that there is an ethical obligation to responsibly share data generated by interventional clinical trials because participants have put themselves at risk. In a growing consensus, many funders around the world - foundations, government agencies, and industry - now mandate data sharing. Here, we outline ICMJE＇s proposed requirements to help meet this obligation. We encourage feedback on the proposed requirements. Anyone can provide feedback at www. icmje.org by April 18, 2016.
文摘Objective To investigate the clinical and genetic variation characteristics of a child with autosomal dominant lateral temporal lobe epilepsy caused by de novo variation of the MICALl gene.Methods Clinical data of the patient with autosomal dominant lateral temporal lobe epilepsy caused by MICALl gene variation diagnosed in Children's Hospital of Soochow University in August 2019 were collected.The whole exome sequencing was performed on the core members of the family,and the characteristics of gene variations were analyzed.Results The proband,a 10 years and 5 months old boy,was admitted to the hospital because of"intermittent convulsions for 7 years".The clinical manifestations included focal or generalized tonic-clonic seizures and hearing aura,with normal language and intellectual development.No abnormalities were found in the T,and fluid attenuated inversion recovery sequences of the cranial 3.0 T magnetic resonance imaging and 3D thinslice magnetic resonance imaging.Long-range video electroencephalogram showed the distribution of spinous and slow spinous waves in the left frontal and temporal areas.The results of whole exome gene sequencing in the core family members showed heterozygous de novo missense variation in the MICALI gene of the proband(NM_022765):c.763G>T(exon6)(p.Val255Leu)that had not been reported.According to American College of Medical Geneticsand Genomicssand Association for Molecular Pathology guidelines(2015),the mutation was considered potentially pathogenic.The application of antiepilepticdrugsswaseffectivein controllingepilepticcseizures.ConclusionAuditory symptoms are main clinical manifestations for the child with autosomal dominant lateral temporal lobe epilepsy.Antiepileptic drugs can effectively control epileptic seizures of the child,and the MICALl gene c.763G>T(p.Val255Leu)mutation is the genetic cause of the proband.
文摘Objective To investigate the correlation between the clinical features and endoscopic ultrasound-guided portal pressure gradient(EUS-PPG)in patients with cirrhosis.Methods A total of 148 patients with cirrhosis and portal hypertension who underwent EUS-PPG measurement at the Third Xiangya Hospital of Central South University from March 15,2022 to June 20,2023 were selected.The clinical data of patients collected before EUS-PPG measurement were analyzed.Variations in the EUS-PPG across different clinical data subgroups were analyzed.Multivariate linear regression analysis was used to explore the independent factors influencing EUS-PPG.Results The EUS-PPG was significantly elevated in patients exhibiting red signs(16.62±5.33 mmHg VS 13.44±5.34 mmHg,t=3.616,P<0.001),gastroesophageal varices(15.78±5.30 mmHg VS 9.70±4.77 mmHg,t=4.247,P<0.001),hepatic encephalopathy(20.83±7.52 mmHg VS 14.92±5.35 mmHg,t=2.606,P=0.010),thrombocytopenia(15.66±5.39 mmHg VS 13.29±5.83mmHg,t=2.136,P=0.034),hypoproteinemia(16.13±5.86 mmHg VS 14.12±5.03 mmHg,t=2.230,P=0.027),and an increased international normalized ratio(16.25±6.00 mmHg VS 14.40±5.11mmHg,t=2.022,P=0.045).Conversely,the EUS-PPG was significantly reduced in patients with a history of splenectomy and devascularization(13.17±5.88mmHgVS15.73±5.34mmHg,t=-2.379,P=0.019).The EUS-PPG in patients with varying degrees of ascites(no VS slight VS moderate or severe:13.40±5.48 mmHg VS 15.90±5.49 mmHg VS 16.69±5.17 mmHg,F=5.188,P=0.007)and different Child-Pugh classifications(A VS B VS C:14.07±5.05 mmHg VS 15.69±5.74 mmHg VS 17.64±5.99 mmHg,F=3.066,P=0.049)increased gradually.Multivariable linear regression analysis showed that red signs(β=2.44,t=2.732,P=0.007),gastroesophageal varices(β=4.45,t=2.990,P=0.003),ascites(β=1.75,t=2.368,P=0.019),and hepatic encephalopathy(β=5.82,t=2.644,P=0.009)were independentftactors fortheelevated1EUS-PPG.Conclusion There is a significant correlation between EUS-PPG and the clinical features related to the severity of cirrhotic portal hypertension,which indicates the feasibility of EUS-PPG in evaluating cirrhotic portal hypertension.
