Dataset Information

Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients.

ABSTRACT: The heterogeneity of cognitive profiles among psychiatric patients has been reported to carry significant clinical information. However, how to best characterize such cognitive heterogeneity is still a matter of debate. Despite being well suited for clinical data, cluster analysis techniques, like the Two-Step and the Latent Class, received little to no attention in the literature. The present study aimed to test the validity of the cluster solutions obtained with Two-Step and Latent Class cluster analysis on the cognitive profile of a cross-diagnostic sample of 387 psychiatric inpatients. Two-Step and Latent Class cluster analysis produced similar and reliable solutions. The overall results reported that it is possible to group all psychiatric inpatients into Low and High Cognitive Profiles, with a higher degree of cognitive heterogeneity in schizophrenia and bipolar disorder patients than in depressive disorders and personality disorder patients.

SUBMITTER: Benassi M

PROVIDER: S-EPMC7299079 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients.

Benassi Mariagrazia M Garofalo Sara S Ambrosini Federica F Sant'Angelo Rosa Patrizia RP Raggini Roberta R De Paoli Giovanni G Ravani Claudio C Giovagnoli Sara S Orsoni Matteo M Piraccini Giovanni G

Frontiers in psychology 20200610

The heterogeneity of cognitive profiles among psychiatric patients has been reported to carry significant clinical information. However, how to best characterize such cognitive heterogeneity is still a matter of debate. Despite being well suited for clinical data, cluster analysis techniques, like the Two-Step and the Latent Class, received little to no attention in the literature. The present study aimed to test the validity of the cluster solutions obtained with Two-Step and Latent Class clust ...[more]

PMID: 32587546

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Project description:Heterogeneity of injury severity among children with traumatic brain injury (TBI) classified by the Glasgow Coma Scale (GCS) makes comparisons across research cohorts, enrollment in clinical trials, and clinical predictions of outcomes difficult. The present study uses latent class analysis (LCA) to distinguish severity subgroups from a prospective cohort of 433 children 2.5-15 years of age with TBI who were recruited from two level 1 pediatric trauma centers. Indicator variables available within 48 h post-injury including emergency department (ED) GCS, hospital motor GCS, Abbreviated Injury Score (AIS), Rotterdam Score, hypotension in the ED, and pre-hospital loss of consciousness, intubation, seizures, and sedation were evaluated to define subgroups. To understand whether latent class subgroups were predictive of clinically meaningful outcomes, the Pediatric Injury Functional Outcome Scale (PIFOS) at 6 and 12 months, and the Behavior Rating Inventory of Executive Function at 12 months, were compared across subgroups. Then, outcomes were examined by GCS (primary) and AIS (secondary) classification alone to assess whether LCA provided improved outcome prediction. LCA identified four distinct increasing severity subgroups (1-4). Unlike GCS classification, mean outcome differences on PIFOS at 6 months showed decreasing function across classes. PIFOS differences relative to the lowest latent class (LC1) were: LC2 2.27 (0.83, 3.72), LC3 3.99 (1.88, 6.10), and LC4 11.2 (7.04, 15.4). Differences in 12 month outcomes were seen between the most and least severely injured groups. Differences in outcomes in relation to AIS were restricted to the most and less severely injured at both time points. This study distinguished four latent classes that are clinically meaningful, distinguished a more homogenous severe injury group, and separated children by 6-month functional outcomes better than GCS alone. Systematic reporting of these variables would allow comparisons across research cohorts, potentially improve clinical predictions, and increase sensitivity to treatment effects in clinical trials.

Project description:BACKGROUND:Maternal depression in the postpartum period confers substantial morbidity and mortality, but the definition of postpartum depression remains controversial. We investigated the heterogeneity of symptoms with the aim of identifying clinical subtypes of postpartum depression. METHODS:Data were aggregated from the international perinatal psychiatry consortium Postpartum Depression: Action Towards Causes and Treatment, which represents 19 institutions in seven countries. 17,912 unique subject records with phenotypic data were submitted. We applied latent class analyses in a two-tiered approach to assess the validity of empirically defined subtypes of postpartum depression. Tier one assessed heterogeneity in women with complete data on the Edinburgh postnatal depression scale (EPDS) and tier two in those with postpartum depression case status. FINDINGS:6556 individuals were assessed in tier one and 4245 in tier two. A final model with three latent classes was optimum for both tiers. The most striking characteristics associated with postpartum depression were severity, timing of onset, comorbid anxiety, and suicidal ideation. Women in class 1 had the least severe symptoms (mean EPDS score 10·5), followed by those in class 2 (mean EPDS score 14·8) and those in class 3 (mean EPDS score 20·1). The most severe symptoms of postpartum depression were significantly associated with poor mood (mean EPDS score 20·1), increased anxiety, onset of symptoms during pregnancy, obstetric complications, and suicidal ideation. In class 2, most women (62%) reported symptom onset within 4 weeks postpartum and had more pregnancy complications than in other two classes (69% vs 67% in class 1 and 29% in class 3). INTERPRETATION:PPD seems to have several distinct phenotypes. Further assessment of PPD heterogeneity to identify more precise phenotypes will be important for future biological and genetic investigations. FUNDING:Sources of funding are listed at the end of the article.

Project description:BackgroundTyphoid fevers are infections caused by the bacteria Salmonella enterica serovar Typhi (Salmonella Typhi) and Paratyphi A, B and C (Salmonella Paratyphi). Approximately 17.8 million incident cases of typhoid fever occur annually, and incidence is highest in children. The accuracy of current diagnostic tests of typhoid fever is poorly understood. We aimed to determine the comparative accuracy of available tests for the pediatric population.MethodsWe first conducted a systematic literature review to identify studies that compared diagnostic tests for typhoid fever in children (aged ≤15 years) to blood culture results. We applied a Bayesian latent-class extension to a network meta-analysis model. We modelled known diagnostic properties of bone marrow culture and the relationship between bone marrow and blood culture as informative priors in a Bayesian framework. We tested sensitivities for the proportion of negative blood samples that were false as well as bone marrow sensitivity and specificity.ResultsWe found 510 comparisons from 196 studies and 57 specific to the pediatric population. IgM-based tests outperformed their IgG-based counterparts for ELISA and Typhidot tests. The lateral flow IgG test performed comparatively well with 92% sensitivity (72% to 98% across scenario analyses) and 94% specificity. The most sensitive test of those investigated for the South Asian pediatric population was the Reverse Passive Hemagglutination Assay with 99% sensitivity (98% - 100% across scenario analyses). Adding a Widal slide test to other typhoid diagnostics did not substantially improve diagnostic performance beyond the single test alone, however, a lateral flow-based IgG rapid test combined with the typhoid/paratyphoid (TPT) assay yielded improvements in sensitivity without substantial declines in specificity and was the best performing combination test in this setting.ConclusionIn the pediatric population, lateral-flow IgG, TPT and Reverse Passive Hemagglutination tests had high diagnostic accuracy compared to other diagnostics. Combinations of tests may provide a feasible option to increase diagnostic sensitivity. South Asia has the most informed set of data on typhoid diagnostic testing accuracy, and the evidence base in other important regions needs to be expanded.

Dataset Information

Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients.

Publications

Using Two-Step Cluster Analysis and Latent Class Cluster Analysis to Classify the Cognitive Heterogeneity of Cross-Diagnostic Psychiatric Inpatients.

Similar Datasets

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