Search results for "Disease cluster"

showing 10 items of 101 documents

Four Wellbeing Patterns and their Antecedents in Millennials at Work

2018

Literature suggests that job satisfaction and health are related to each other in a synergic way. However, this might not always be the case, and they may present misaligned relationships. Considering job satisfaction and mental health as indicators of wellbeing at work, we aim to identify four patterns (i.e., satisfied-healthy, unsatisfied-unhealthy, satisfied-unhealthy, and unsatisfied-healthy) and some of their antecedents. In a sample of 783 young Spanish employees, a two-step cluster analysis procedure showed that the unsatisfied-unhealthy pattern was the most frequent (33%), followed by unsatisfied-healthy (26.6%), satisfied-unhealthy (24.8%) and, finally, the satisfied-healthy patter…

AdultMaleAdolescentHealth Toxicology and Mutagenesismedia_common.quotation_subjectHealth Statuslcsh:Medicine050109 social psychologySample (statistics)WorkloadDisease clusterRole conflictArticleYoung Adultwellbeing0502 economics and businessHumans0501 psychology and cognitive sciencesMillennialsmedia_commonjob satisfactionwellbeing misalignment05 social scienceslcsh:RPublic Health Environmental and Occupational HealthOverqualificationhealthAmbiguityLinear discriminant analysisMental healthMental HealthSpainJob satisfactionFemalePsychologySocial psychology050203 business & managementInternational Journal of Environmental Research and Public Health
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Occurrence and clinical characteristics of Compulsive Sexual Behavior Disorder (CSBD): A cluster analysis in two independent community samples.

2020

AbstractBackground and aimsCompulsive Sexual Behavior Disorder (CSBD) is characterized by a persistent failure to control intense and recurrent sexual impulses, urges, and/or thoughts, resulting in repetitive sexual behavior that causes a marked impairment in important areas of functioning. Despite its recent inclusion in the forthcoming ICD-11, concerns regarding its assessment, diagnosis, prevalence or clinical characteristics remain. The purpose of this study was to identify participants displaying CSBD through a novel data-driven approach in two independent samples and outline their sociodemographic, sexual, and clinical profile.MethodsSample 1 included 1,581 university students (female…

AdultMaleAdolescentUniversitiesSexual Behavior030508 substance abuseMedicine (miscellaneous)occurrenceDisease clusterSeverity of Illness Index03 medical and health sciencesYoung Adult0302 clinical medicineIndependent samplesSensation seekingCluster AnalysisHumansStudentsPsychiatric Status Rating ScalesParaphilic DisordersGeneral Medicineclinical profile030227 psychiatryDisruptive Impulse Control and Conduct DisordersPsychiatry and Mental healthClinical PsychologySexual behaviorErotophiliaCompulsive BehaviorFemaleCompulsive Sexual Behavior Disorder (CSBD)0305 other medical sciencePsychologycluster analysisClinical psychologyJournal of behavioral addictions
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Prediction of the hemoglobin level in hemodialysis patients using machine learning techniques

2013

HighlightsDifferent prediction algorithms were used to predict Hb levels in CRF patients.Prediction errors in the validation cohorts of patients were around 0.6g/dl.Difficulty to obtain lower errors due to the measuring machine precision (0.2g/dl).Relevance analysis of features have been applied for each predictor. Patients who suffer from chronic renal failure (CRF) tend to suffer from an associated anemia as well. Therefore, it is essential to know the hemoglobin (Hb) levels in these patients. The aim of this paper is to predict the hemoglobin (Hb) value using a database of European hemodialysis patients provided by Fresenius Medical Care (FMC) for improving the treatment of this kind of …

AdultMaleAdolescentmedicine.medical_treatmentHealth InformaticsMachine learningcomputer.software_genreDisease clusterSensitivity and SpecificityHemoglobinsYoung AdultArtificial IntelligenceRenal DialysismedicineHumansComputer SimulationCluster analysisErythropoietinAgedAged 80 and overDose-Response Relationship DrugArtificial neural networkbusiness.industryModels CardiovascularLinear modelReproducibility of ResultsAnemiaMiddle AgedRegressionDrug Therapy Computer-AssistedComputer Science ApplicationsSupport vector machineTreatment OutcomeAdaptive resonance theoryFemaleHemodialysisArtificial intelligenceDrug MonitoringbusinesscomputerAlgorithmsBiomarkersSoftwareComputer Methods and Programs in Biomedicine
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Visualizing knowledge and attitude factors related to influenza vaccination of physicians

2014

To characterize groups of primary healthcare physicians according to sociodemographic data, years of professional experience and knowledge of and attitudes to influenza, and to evaluate differences between groups with respect to influenza vaccination in the 2011-2012 season.We carried out an anonymous web survey of Spanish primary healthcare physicians in 2012. Information on vaccination, and knowledge of and attitudes to influenza was collected. Multiple correspondence analysis and cluster analysis were used to define groups of physicians.We included 835 physicians and identified three types. Type B were physicians with low professional experience of influenza. Types A and C were physician…

AdultMaleHealth Knowledge Attitudes Practicemedicine.medical_specialtyAttitude of Health PersonnelPrimary health careSevere diseaseSociodemographic dataDisease clusterMultiple correspondence analysisPhysiciansSurveys and QuestionnairesInfluenza HumanmedicineHumansGeneral VeterinaryGeneral Immunology and MicrobiologyTransmission (medicine)business.industryData CollectionVaccinationPublic Health Environmental and Occupational Healthvirus diseasesMiddle AgedVaccinationInfectious DiseasesFamily medicineMolecular MedicineFemalebusinessWeb surveyVaccine
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Personality Disorders in Obsessive-Compulsive Disorder: A Comparative Study versus Other Anxiety Disorders

2013

Objective. The purpose of this paper is to provide evidence for the relationship between personality disorders (PDs), obsessive compulsive disorder (OCD), and other anxiety disorders different from OCD (non-OCD) symptomatology.Method. The sample consisted of a group of 122 individuals divided into three groups (41 OCD; 40 non-OCD, and 41 controls) matched by sex, age, and educational level. All the individuals answered the IPDE questionnaire and were evaluated by means of the SCID-I and SCID-II interviews.Results. Patients with OCD and non-OCD present a higher presence of PD. There was an increase in cluster C diagnoses in both groups, with no statistically significant differences between t…

AdultMaleObsessive-Compulsive Disordermedicine.medical_specialtyArticle Subjectmedia_common.quotation_subjectlcsh:MedicineAnxietyDisease clusterPersonality Disorderslcsh:Technologybehavioral disciplines and activitiesGeneral Biochemistry Genetics and Molecular BiologyObsessive compulsiveSurveys and Questionnairesmental disordersmedicineHumansPersonalityPsychiatrylcsh:ScienceGeneral Environmental Sciencemedia_commonbusiness.industrylcsh:Tlcsh:RGeneral MedicineMiddle Agedmedicine.diseasePersonality disordersObsessive–compulsive personality disorderhumanitiesAnxietyFemalelcsh:Qmedicine.symptombusinessAnxiety disorderResearch ArticleThe Scientific World Journal
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Association Between Clinical and Microbiologic Cluster Profiles and Peri-implantitis

2017

Purpose: The correlation between associated local factors and peri-implantitis remains unknown. The aim of this study was to investigate the association between the clinical and microbiologic profiles and periimplantitis to eventually categorize different groups of this disease. Materials and Methods: Subjects with at least one implant presenting signs of peri-implantitis were selected. The clinical, radiographic, occlusal, and microbiologic profiles of these infected implants were collected. Cases were classified into five peri-implantitis groups according to potential disease-triggering factors: surgically, prosthetically, biomechanically, purely plaque-associated, and a combination of th…

AdultMalePeri-implantitisGingival and periodontal pocketCross-sectional studyColony Count MicrobialDental PlaqueDentistry02 engineering and technologyReal-Time Polymerase Chain ReactionDisease cluster03 medical and health sciencesassociated risk factors peri-implant disease peri-implantitisperi-implant disease0302 clinical medicineRisk FactorsHumansPeriodontal PocketMedicineGeneralized estimating equationassociated risk factorsAgedAged 80 and overDental ImplantsBacteriabusiness.industryDental Plaque Index030206 dentistryGeneral MedicineMiddle Aged021001 nanoscience & nanotechnologyPeri-ImplantitisDental Plaque IndexCross-Sectional StudiesEtiologyFemaleImplantOral Surgery0210 nano-technologybusinessThe International Journal of Oral & Maxillofacial Implants
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Subtyping treatment-seeking gaming disorder patients

2021

Abstract Background and aims Gaming Disorder (GD) is characterized by a pattern of persistent and uncontrolled gaming behavior that causes a marked impairment in important areas of functioning. The evolution of the worldwide incidence of this disorder warrants further studies focused on examining the existence of different subtypes within clinical samples, in order to tailor treatment. This study explored the existence of different profiles of patients seeking treatment for GD through a data-driven approach. Methods The sample included n = 107 patients receiving treatment for GD (92% men and 8% women) ranging between 14 and 60 years old (mean age = 24.1, SD = 10). A two-step clustering anal…

AdultMalePsychology PathologicalAdolescentmedia_common.quotation_subjectMedicine (miscellaneous)Dysfunctional familyToxicologyDisease clusterPersonality DisordersDSM-5Young AdultCluster AnalysisHumansPersonalityMedicineBig Five personality traitsPathologicalmedia_commonbusiness.industryIncidence (epidemiology)Joc compulsiuMiddle AgedPsicopatologiaBehavior AddictiveDisruptive Impulse Control and Conduct DisordersPsychiatry and Mental healthClinical PsychologyFemaleGaming Disorder; Personality; Internet Gaming Disorder; DSM-5; Diagnosis; Cluster Analysis; Clustering; ProfilesCompulsive gamblingbusinessPersonalityClinical psychologyPsychopathologyAddictive Behaviors
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Statistical analysis of life history calendar data

2016

The life history calendar is a data-collection tool for obtaining reliable retrospective data about life events. To illustrate the analysis of such data, we compare the model-based probabilistic event history analysis and the model-free data mining method, sequence analysis. In event history analysis, we estimate instead of transition hazards the cumulative prediction probabilities of life events in the entire trajectory. In sequence analysis, we compare several dissimilarity metrics and contrast data-driven and user-defined substitution costs. As an example, we study young adults' transition to adulthood as a sequence of events in three life domains. The events define the multistate event…

AdultMaleStatistics and ProbabilityAdolescentEpidemiologyComputer sciencedistance-based dataDisease clustercomputer.software_genre01 natural sciencesLife Change EventsYoung Adult010104 statistics & probability0504 sociologyHealth Information Managementprediction probabilityStatisticsData MiningHumansLongitudinal StudiesProspective Studieslife history calendar multidimensional sequence analysis0101 mathematicsFinlandSurvival analysisProbabilityRetrospective StudiesSequence (medicine)Complement (set theory)ta112DepressionData Collection05 social sciencesProbabilistic logic050401 social sciences methodsContrast (statistics)multistate modelMiddle ageLife course approachFemaleData mininglife history calendarlife course analysiscomputermultidimensional sequence analysisStatistical Methods in Medical Research
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A hierarchical cluster analysis to determine whether injured runners exhibit similar kinematic gait patterns

2020

Previous studies have suggested that runners can be subgrouped based on homogeneous gait patterns, however, no previous study has assessed the presence of such subgroups in a population of individuals across a wide variety of injuries. Therefore, the purpose of this study was to assess whether distinct subgroups with homogeneous running patterns can be identified among a large group of injured and healthy runners and whether identified subgroups are associated with specific injury location. Three‐dimensional kinematic data from 291 injured and healthy runners, representing both sexes and a wide range of ages (10‐66 years) was clustered using hierarchical cluster analysis. Cluster analysis r…

AdultMalemedicine.medical_specialtyAdolescentmedicine.medical_treatmentPopulationPhysical Therapy Sports Therapy and RehabilitationKinematicsBiologyDisease clusterRunningjuoksuYoung Adult03 medical and health sciences0302 clinical medicinePhysical medicine and rehabilitationInjury preventionmedicineCluster AnalysisHumansOrthopedics and Sports MedicineChildeducationGaitAgedurheiluvammateducation.field_of_studyliikeoppiRehabilitation030229 sport sciencesMiddle AgedBiomechanical PhenomenaHierarchical clusteringkoneoppiminenLower ExtremityHomogeneousFemaleAnalysis of variancehuman activities030217 neurology & neurosurgeryScandinavian Journal of Medicine & Science in Sports
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Association between night-time extubation and clinical outcomes in adult patients

2021

Background: Whether night-time extubation is associated with clinical outcomes is unclear. Objective: The aim of this systematic review and meta-analysis was to evaluate the association between night-time extubation and the reintubation rate, mortality, ICU and in-hospital LOS in adult patients, compared with daytime extubation. Design: A systematic review and meta-analysis. Data sources: PubMed, EMBASE, CINAHL and Web of Science from inception to 2 January 2021 (PROSPERO registration - CRD42020222812). Eligibility criteria: Randomised, quasi and cluster randomised, and nonrandomised studies describing associations between adult patients' outcomes and time of extubation (daytime/night-time)…

AdultMechanical ventilationmedicine.medical_specialtyextubationCritical CareAdult patientsbusiness.industrymedicine.medical_treatmentRetrospective cohort studyCINAHLLength of StayDisease clusterRandom effects modelRespiration ArtificialIntensive Care UnitsAnesthesiology and Pain MedicineMeta-analysisIntensive careEmergency medicineAirway ExtubationmedicineHumansbusinessRetrospective StudiesEuropean Journal of Anaesthesiology
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