Clinical and microbiological profiles in post-chemotherapy neutropenic fever in hematological malignancy: exploration of clinical phenotype patterns by two-step cluster analysis.

BACKGROUND: Epidemiology of infectious diseases causing febrile illness varies geographically with human attributes. Periodic institutional surveillance of clinical and microbiological profiles in adding data to updating trends, modulating pharmatherapeutics, signifying possible excessive treatments and risk of drug resistance in post-chemotherapy neutropenic fever (NF) in hematological malignancy (HM) is limited. We aimed to review institutional clinical and microbiological data and explore clinical phenotype pattern groups among data. METHODS: Available data from 372 NF episodes were included. Demographics, types of malignancies, laboratory data, antimicrobial treatments and febrile-related outcome data such as predominant pathogens and microbiological diagnosed infections (MDIs) were collected. Descriptive statistics, two-step cluster analysis and non-parametric tests were employed. RESULTS: The occurrences of microbiological diagnosed bacterial infections (MDBIs; 20.2%) and microbiological diagnosed fungal infections (MDFIs; 19.9%) were almost equal. Gram-negative pathogens (11.8%) were comparable with gram-positive pathogens (9.9%), with gram-negative being slightly predominant. Death rate was 7.5%. Two-step cluster analysis yielded four distinct clinical phenotype pattern (cluster) groups: cluster 1 'lymphomas without MDIs', cluster 2 'acute leukemias MDBIs', cluster 3 'acute leukemias MDFIs' and cluster 4 'acute leukemias without MDIs'. Considerable NF events with antibiotic prophylaxis being not identified as MDI might have cases in low-risk with non-infectious reasons causing febrile reactions that might possibly not require prophylaxis. CONCLUSIONS: Regular institutional surveillance with active parameter assessments to signify risk levels in the post-chemotherapy stage, even prior to the onset of fever, might be an evidence-based strategy in the management of NF in HM.

Investigation of the multidimensional determinants of negative nutrition coping strategies and tradeoffs in adults accessing food relief: A secondary data analysis.

BACKGROUND: Multidimensional determinants influence negative nutrition coping strategies and tradeoffs in households accessing food relief. AIMS: This study examined coping strategies and tradeoffs at different levels of food insecurity from individuals accessing food relief and how these behaviors relate to experience-based food insecurity dimensions and subpopulations at risk. METHODS: A secondary analysis of cross-sectional data from the Sunshine State Hunger Survey (SSHS) was conducted. The SSHS was a paper-based, 48-question survey, including questions about coping strategies and tradeoffs, use of food assistance programs, and food security. RESULTS: Out of 616 respondents who completed the survey, 73.9% identified as food insecure while 19.1%, as food secure. The average age of participants was 59.6 years and 62.6% were female. One-way analysis of variance indicated increases in negative nutrition coping strategies and tradeoffs with increasing levels of food insecurity status. The most common coping strategy reported by those with very low food security was "Eating less so children or others have enough food," while the most common tradeoff was "Trading off medicine or medical care for food." Two-step cluster analysis identified homogeneous subgroups by behavior and demographic characteristics: (1) late adult worriers, (2) middle adult traders, and (3) middle/late adult copers. CONCLUSION: Identifying coping strategies and tradeoffs used by participants accessing food relief is a multidimensional approach to addressing determinants of food insecurity. Future research on conceptual pathways is warranted to see if experience-based food insecurity variables help to understand relationships across a continuum, including barriers and influencers.

Segments of military ration pack eaters: Choice preferences among groups.

Best-Worst Scaling (BWS) has the potential to improve menu design by determining the most and least preferred combat ration pack (CRP) items by military personnel. However, individual differences among large groups means that a ration pack design based on the average of preferences may leave many individuals dissatisfied. This paper extends the existing literature by segmenting Australian military personnel based on the preferences for specific ration pack items. Military personnel (n = 300) provided BWS data via an online survey providing product preferences for 21 items. Participants were randomly allocated to one of four different military scenarios developed and refined by Australian Defence Force (ADF) personnel, ensuring consistency with typical operational and training exercises. The four scenarios were presented with two environment variations (hot/dry or hot/humid) and two resupply variations (daily or resupply on day four and day seven) creating four survey sub-groups. Two-step cluster analysis revealed three military segments (Snackers, Balanced eaters, and Mindful eaters) with distinct CRP item preferences across the larger military group. This study provides insights of the feasibility and usefulness of segmenting military personnel based on ration pack item preferences. This approach could streamline the process for decision makers responsible for designing and developing ration packs, and ultimately increase consumption so that personnel obtain essential nutrition to support their performance.

Discovering healthcare provider behavior patterns through the lens of Medicare excess charge.

BACKGROUND: The phenomenon of excess charge, where a healthcare service provider bills Medicare beyond the limit allowed for a medical procedure, is quite common in the United States public healthcare system. For example, in 2014, healthcare providers charged an average of 3.27 times (and up to 528 times) the allowable limit for cataract surgery. Previous research contends that such excess charges may be indicative of the actual amount that providers bill to non-Medicare patients and subsequent cost-shifting behavior, where a healthcare provider tries to recoup underpayment by Medicare from privately insured, self-pay, out-of-network, and uninsured patients. OBJECTIVES: The objective of this study is to examine the drivers of a provider's excess charge patterns, especially the extent to which the degree of excess charges may be associated with physician characteristics, Medicare reimbursement policy, or socioeconomic status and demographics of a provider's patient base. METHODS: Using data from the 2014 Medicare Provider Utilization files, we identify three procedures with the highest variation in Medicare reimbursements to study the excess charge phenomenon. We then employ a two-step cluster analysis within each procedure to identify distinct provider groups. RESULTS: Each procedure code yielded distinct healthcare provider segments with specific patient demographics and related behavior patterns. Cluster silhouette coefficients indicate that these segments are unique. Three random subsamples from each procedure establish the stability of the clusters. CONCLUSIONS: For each of the three procedures investigated in this study, a sizeable number of healthcare providers serving poorer, riskier patients are often paid significantly lower than their peers, and subsequently have the highest excess charges. For some providers, excess charges reveal possible cost-shifting to private insurance. Patterns of excess charges also indicate an imbalance of market power, especially in areas with lower provider competition and access to health care, thus leading to urban-rural healthcare disparities. Our results reinforce the call for price transparency and an upper limit to overbilling.

A multi-faceted, location-specific assessment of land degradation threats to peri-urban agriculture at a traditional grain base in northeastern China.

Urbanization-induced cultivated land degradation can hamper the ability of peri-urban agriculture (PUA) to deliver clean food and agroecosystem services. Detailed geo-information about which cultivated lands are being influenced by urbanization will be important to designing future measures for the conservation of PUA. This information will be especially relevant for traditional grain bases because PUA is often underappreciated in these regions. For this reason, we performed a multi-faceted and location-specific assessment, including soil pollution, soil fertility, basic tillage conditions and land fragmentation, of cultivated land in a rural-urban transition zone outside of a city in northeast China. We also illustrated the combined risks in different urbanized environments via GIS-based two-step spatial clustering. The results indicated that, in general, cultivated lands were more polluted and fragmented, as well as less fertile and tillable, the closer they were to the urban area. Most of the affected cultivated lands were located within 8 km of the urban periphery. Furthermore, certain urban environments exposed the surrounding cultivated lands to specific degradation in relation to different combined risks. PUA in long-standing industrial areas mainly faced risks of polluted agricultural production, underutilization and impaired landscape ecological security (LES), whereas cultivated lands close to a recently developed residential area were characterized by risks of supplying service disruption, unsustainable agricultural production, underutilization and impaired LES. The present study highlighted that PUA associated with traditional grain bases must be preserved to enhance urban sustainability and resilience, and suggests that measures which can adapt to multi-faceted local degradation issues will be the most effective protection for peri-urban areas. Furthermore, the results also suggest that multi-functional and profitable agriculture will contribute to breaking the vicious circle of land degradation in peri-urban cultivated areas of traditional grain bases.

Learning what our target audiences think and do: extending segmentation to all four bases.

BACKGROUND: While acknowledged as one of social marketing's necessities, limited reporting of segmentation exists. The current study seeks to extend segmentation drawing on all four segmentation bases within the context of Queensland young adult sexual health behaviour. METHODS: An online survey was used to collect data from 15 to 29 year old people in Queensland, Australia. Data collection was undertaken online to capture the broader population of young adults and in person on campuses to gather data from students who were currently enrolled at University. Quotas were set to ensure a broad representation was attained reflecting the States demography. RESULTS: Two-step cluster analysis revealed three different segments. The most important variables in segment formation were age, household type, experience of risky sexual encounters and previously being tested or treated for sexually transmissible infections (STIs). The results suggest that demographic and behavioural variables were the most effective in segment definition. CONCLUSIONS: This study investigated young people aged 15-29 in Queensland, Australia to examine group differences drawing from four bases. This study revealed three distinct segments in a sexual health context and highlighted the importance of behavioural variables in segment formation, insight and understanding.

Spinal posture changes using dynamic rasterstereography during the modified Matthiass test discriminate between postural weak and strong healthy children (10-14 years): a pilot study.

The aim of this pilot study was to investigate whether the clinical Matthiass test can be objectified by means of dynamic rasterstereography in children. We aimed at discriminating between postural weak and strong children. Dynamic rasterstereography was used to capture sagittal spinal posture changes during the modified Matthiass test (mMT). Primary outcomes were spinal posture changes (trunk inclination, kyphotic and lordotic angles) during the test. Two-step cluster analysis was run jointly on the three primary outcomes. Data of 101 healthy children (10-14 years, 46% girls) were assessed. Cluster analysis identified two groups of participants with significantly different postural performance levels during the mMT (low vs. high performers). Low performers showed a higher increase in backward lean, as well as kyphosis and lordosis (4°-5°, respectively) when compared to high performers. The two performance groups were age-, BMI-, and activity-matched.Conclusion: This pilot study established preliminary normative data on spinal posture changes during the Matthiass test (high performers) and provided corresponding cutoff values for postural weakness (low performers). These results could provide a basis for future longitudinal and interventional studies targeting long-term consequences of childhood postural weakness and the prevention of back pain. What is Known: • The prevalence of postural insufficiencies in children is high. • No consensus exists about the postural assessment in children. • A common clinical test to identify postural insufficiency is the Matthiass test yet criticized for its subjective assessment. What is New: • This pilot study objectified the modified Matthiass test by rasterstereography and statistically identified two groups of healthy children with different postural performance levels. • It established preliminary normative data on spinal posture changes and provided corresponding cutoff values for postural weakness.

Enhancing Pulmonary Embolism Mortality Risk Stratification Using Machine Learning: The Role of the Neutrophil-to-Lymphocyte Ratio.

(1) Background: Acute pulmonary embolism (PE) is a significant public health concern that requires efficient risk estimation to optimize patient care and resource allocation. The purpose of this retrospective study was to show the correlation of NLR (neutrophil-to-lymphocyte ratio) and PESI (pulmonary embolism severity index)/sPESI (simplified PESI) in determining the risk of in-hospital mortality in patients with pulmonary thromboembolism. (2) Methods: A total of 160 patients admitted at the County Clinical Emergency Hospital of Sibiu from 2019 to 2022 were included and their hospital records were analyzed. (3) Results: Elevated NLR values were significantly correlated with increased in-hospital mortality. Furthermore, elevated NLR was associated with PESI and sPESI scores and their categories, as well as the individual components of these parameters, namely increasing age, hypotension, hypoxemia, and altered mental status. We leveraged the advantages of machine learning algorithms to integrate elevated NLR into PE risk stratification. Utilizing two-step cluster analysis and CART (classification and regression trees), several distinct patient subgroups emerged with varying in-hospital mortality rates based on combinations of previously validated score categories or their defining elements and elevated NLR, WBC (white blood cell) count, or the presence COVID-19 infection. (4) Conclusion: The findings suggest that integrating these parameters in risk stratification can aid in improving predictive accuracy of estimating the in-hospital mortality of PE patients.

New Interpretation of Neonatal Outcomes by Phenotypically Classified Preterm Syndrome: A Retrospective Cohort Study.

OBJECTIVE: The global aim to lower preterm birth rates has been hampered by the insufficient and incomplete understanding of its etiology, classification, and diagnosis. This study was designed to evaluate the association of phenotypically classified preterm syndromes with neonatal outcomes; to what extent would these outcomes be modified after the obstetric interventions, including use of glucocorticoid, magnesium sulfate, and progesterone. METHODS: This was a retrospective cohort study conducted at Tongji Hospital (composed of Main Branch, Optical Valley Branch and Sino-French New City Branch) in Wuhan. A total of 900 pregnant women and 1064 neonates were retrospectively enrolled. The outcomes were the distribution of different phenotypes among parturition signs and pathway to delivery, the association of phenotypically classified clusters with short-term unfavorable neonatal outcomes, and to what extent these outcomes could be modified by obstetric interventions. RESULTS: Eight clusters were identified using two-step cluster analysis, including premature rupture of fetal membranes (PPROM) phenotype, abnormal amniotic fluid (AF) phenotype, placenta previa phenotype, mixed condition phenotype, fetal distress phenotype, preeclampsia-eclampsia & hemolysis, elevated liver enzymes, and low platelets syndrome (PE-E&HELLP) phenotype, multiple fetus phenotype, and no main condition phenotype. Except for no main condition phenotype, the other phenotypes were associated with one or more complications, which conforms to the clinical practice. Compared with no main condition phenotype, some phenotypes were significantly associated with short-term adverse neonatal outcomes. Abnormal AF phenotype, mixed condition phenotype, PE-E&HELLP phenotype, and multiple fetus phenotype were risk factors for neonatal small-for gestation age (SGA); placenta previa phenotype was not associated with adverse outcomes except low APGAR score being 0-7 at one min; mixed condition phenotype was associated with low APGAR scores, SGA, mechanical ventilation, and grade HI-W intraventricular hemorrhage (IVH); fetal distress phenotype was frequently associated with neonatal SGA and mechanical ventilation; PE-E&HELLP phenotype was correlated with low APGAR score being 0-7 at one min, SGA and neonatal intensive care unit (NICU) admission; multiple fetus phenotype was not a risk factor for the outcomes included except for SGA. Not all neonates benefited from obstetric interventions included in this study. CONCLUSION: Our research disclosed the independent risk of different preterm phenotypes for adverse pregnancy outcomes. This study is devoted to putting forward the paradigm of classifying preterm birth phenotypically, with the ultimate purpose of defining preterm phenotypes based on multi-center studies and diving into the underlying mechanisms.

Prognostic analysis of breast cancer in Xinjiang based on Cox proportional hazards model and two-step cluster method.

Objective: To examine the factors that affect the prognosis and survival of breast cancer patients who were diagnosed at the Affiliated Cancer Hospital of Xinjiang Medical University between 2015 and 2021, forecast the overall survival (OS), and assess the clinicopathological traits and risk level of prognosis of patients in various subgroups. Method: First, nomogram model was constructed using the Cox proportional hazards models to identify the independent prognostic factors of breast cancer patients. In order to assess the discrimination, calibration, and clinical utility of the model, additional tools such as the receiver operating characteristic (ROC) curve, calibration curve, and clinical decision curve analysis (DCA) were used. Finally, using two-step cluster analysis (TCA), the patients were grouped in accordance with the independent prognostic factors. Kaplan-Meier survival analysis was employed to compare prognostic risk among various subgroups. Result: T-stage, N-stage, M-stage, molecular subtyping, type of operation, and involvement in postoperative chemotherapy were identified as the independent prognostic factors. The nomogram was subsequently constructed and confirmed. The area under the ROC curve used to predict 1-, 3-, 5- and 7-year OS were 0.848, 0.820, 0.813, and 0.791 in the training group and 0.970, 0.898, 0.863, and 0.798 in the validation group, respectively. The calibration curves of both groups were relatively near to the 45° reference line. And the DCA curve further demonstrated that the nomogram has a higher clinical utility. Furthermore, using the TCA, the patients were divided into two subgroups. Additionally, the two groups' survival curves were substantially different. In particular, in the group with the worse prognosis (the majority of patients did not undergo surgical therapy or postoperative chemotherapy treatment), the T-, N-, and M-stage were more prevalent in the advanced, and the total points were likewise distributed in the high score side. Conclusion: For the survival and prognosis of breast cancer patients in Xinjiang, the nomogram constructed in this paper has a good prediction value, and the clustering results further demonstrated that the selected factors were important. This conclusion can give a scientific basis for tailored treatment and is conducive to the formulation of focused treatment regimens for patients in practical practice.

Using two-step cluster analysis to classify inpatients with primary biliary cholangitis based on autoantibodies: A real-world retrospective study of 537 patients in China.

Background: A variety of autoantibodies have been detected in primary biliary cholangitis (PBC), while the presence of autoantibody clusters and their clinical significance have not been fully understood. We aimed at defining autoantibody clusters and to better understand the clinical features and prognosis of PBC patients based on autoantibody clusters under real-world conditions. Methods: We retrospectively analyzed 788 inpatients with PBC evaluated between October 2008 and July 2019, and included 537 patients. Nineteen autoantibodies which were measured routinely were investigated for cluster analysis. Two-step clustering, Kaplan-Meier survival, and Cox regression analyses were used. Results: Five clusters were defined. A cluster of antinuclear antibodies (ANA) and anti-gp210 positive patients were identified with a high rate of cirrhosis at baseline and low survival rate; a cluster of ANA, anti-centromere antibodies (ACA) and/or anti-CENP-B female dominant patients with older disease onset, low level of platelet count at baseline, high rate of hepatic decompensation, and low survival rate was also characterized; and another cluster of anti-mitochondrial antibodies (AMA) and/or AMA-M2, anti-Ro52 and a high rate of anti-gp210 positive patients were identified with a high proportion of male patients and low survival rate. A subgroup of patients with anti-SSA and/or anti-SSB coexists with SjS was also identified; patients with only AMA and/or AMA-M2-positive with a benign clinical outcome and relatively high complication of non-alcoholic fatty liver disease (NAFLD) were also identified. Only anti-gp210 was considered as a significant predictor for poor outcomes especially in patients with cirrhosis. Conclusion: Clustering methods allow the identification of distinct autoantibody profiles of PBC that form clinical subsets and can be useful for personalized approaches to diagnosis, clinical management, and the prediction of clinical outcomes. Anti-gp210 was the strongest predictive factor for poor outcomes especially in PBC patients with cirrhosis under real-world conditions.

Characterizing Organizational Lifecycle through Strategic and Structural Flexibility: Insights from MSMEs in Mexico.

Today's lifespan of companies tends to be low in the so-called micro-, small-, and medium-sized enterprises (MSMEs). Organizational life cycle (OLC) theory indicates that organizational aging is related, but not determined, by the firm chronological age or its size. Therefore, a firm's aging should be analyzed by other factors such as flexibility. The literature considers flexibility as an essential capability, a source of competitive advantage, and an enabler of long-term growth for MSMEs. However, little attention in emerging economies has been paid to examine the nuances of this concept in relation to the OLC in this type of companies. Additionally, studies tend to analyze flexibility as a general term, ignoring that it is a polymorphic concept. That is why there is a need to research the different categories of flexibility. Drawing on a quantitative approach conducting a factor analysis, a two-step cluster, and decision tree analysis to interrogate data from 257 MSMEs in Mexico, this study provides evidence of different dimensions of strategic and structural flexibility that help to characterize and predict the growth, maturity, and declining stages of MSMEs. Our results show that mature firms present more strategic and structural flexible characteristics than those involved in growth or decline stages. The flexible factors that help classify and predict an MSME in the maturity stage include open communication, decentralized decision making, and formalization. We provide a model with these results to illuminate unaddressed issues regarding the broad term of flexibility and its relationship to OLC.

Clinical Implications of Phenotypes of Hemodialysis Patients With Central Venous Occlusion or Central Venous Stenosis Defined by Cluster Analysis.

Objective: This study aims to investigate the association between clinical factors of patients with central (superior vena cava, brachiocephalic, or subclavian) venous occlusion or central venous stenosis (CVO/CVS) and the difficulty of interventional recanalization as well as the duration of postoperative patency. Methods: A total of 103 hemodialysis patients with CVO/CVS treated with endovascular treatment were enrolled. The two-step cluster analysis was selected to differentiate the cases into distinct phenotypes automatically. Differences in characteristics, the difficulty of interventional recanalization, and the duration of postoperative primary patency time between the two clusters were statistically compared. Results: The 103 cases were divided into distinct two clusters by the two-step cluster analysis with 48 (46.6%) in cluster 1 and 55 (53.4%) in cluster 2. Compared to cluster 2, patients in cluster 1 have a higher proportion of blunt stump, side branches, occlusion lesions >2 cm, calcification, or organization. Moreover, the above four factors were, in turn, the most critical four predictors distinguishing 103 patients into two clusters. The remaining six factors were, in turn, occlusion located in the superior vena cava (SVC), duration of central venous catheterization (CVC), lesion location, vessel diameter, number of CVC, and previously failed lesion. Of the four most important factors, with the exception of occlusion lesions exceeding 2 cm, there were significant differences in the length of procedure time between the groups grouped by the remaining three factors. And there was a significant difference in the primary patency rate between the group with blunt stump and the group without blunt stump and also between the group with occlusion lesions ≥ 2 cm and the group with occlusion lesions <2 cm. The operation time of cluster 1 was longer than that of cluster 2. In terms of postoperative patency time, the primary patency time was significantly longer in the patients of cluster 2 compared with cluster 1 (P = 0.025). Conclusion: Patients were divided into distinct two clusters. CVO/CVS of patients in cluster 1 was more challenging to be recanalized than that in cluster 2, and the primary patency time was significantly longer in the patients of cluster 2 compared with cluster 1. Blunt stump, side branches, occlusion lesions exceeding 2 cm, and calcification or organization are the four most critical predictors distinguishing 103 patients into two clusters.

Homelessness Is Socially Created: Cluster Analysis of Social Determinants of Homelessness (SODH) in North West England in 2020.

Poverty creates social conditions that increase the likelihood of homelessness. These include exposure to traumatic life experiences; social disadvantages such as poor educational experiences; being raised in a broken family, care homes or foster care; physical, emotional, and sexual abuse; and neglect at an early age. These conditions reduce people's ability to negotiate through life challenges. This cross-sectional study documents the clustering and frequency of adverse social conditions among 152 homeless people from four cities in North West England between January and August 2020. Two-step cluster analysis showed that having parents with a criminal record, care history, and child neglect/abuse history was predictive of homelessness. The cluster of indicator variables among homeless people included sexual abuse (χ2 (N = 152) = 220.684, p < 0.001, Cramer's V = 0.7), inappropriate sexual behaviour (χ2 (N = 152) = 207.737, p < 0.001, Cramer's V = 0.7), emotional neglect (χ2 (N = 152) = 181.671, p < 0.001, Cramer's V = 0.7), physical abuse by step-parent (χ2 (N = 152) = 195.882, p < 0.001, Cramer's V = 0.8), and physical neglect (χ2 (N = 152) = 205.632, p < 0.001, Cramer's V = 0.8). Poverty and homelessness are intertwined because of the high prevalence of poverty among the homeless. Poverty sets up a chain of interactions between social conditions that increase the likelihood of unfavourable outcomes: homelessness is at the end of the interaction chain. Interventions supporting families to rise out of poverty may also reduce entry into homelessness.

Symptom burden, quality of life, functioning and emotional distress in survivors of human papillomavirus associated oropharyngeal cancer: An Australian cohort.

BACKGROUND: This cross-sectional study examines patient-reported outcomes and functioning-based subgroups in human papillomavirus-associated oropharyngeal cancer survivors treated with chemoradiotherapy ≥12 months prior. METHOD: Survivors completed EORTC QLQ-C30, MDASI-HN and PROMIS-Emotional distress questionnaires. Subgroups were identified via two-step clustering of QLQ-C30 functioning scales. RESULTS: 136 patients were enrolled. Clinicians' graded 19/136 (14%) patients as having at least one severe (Grade 3 CTCAE) toxicity, whereas 68/136 (50%) patients self-reported at least one toxicity in the severe range (MDASI-HN ≥ 7). QLQ-C30 Global health status score (mean 76, SD = 20) was comparable to population norms. Rates of moderate/severe anxiety (10%/1%) and depression (4%/1%) were low. Two functioning-based subgroups were formed based on auto-clustering statistics: high- (n = 93) and low-functioning (n = 41). Differences on all functioning scales were large (d: 1.57-2.29), as were differences on the remaining QLQ-C30 scales/items, most MDASI-HN symptom severity/interference scales, and PROMIS scales (d: 0.80-2.03). Differences and associations with patient/clinical characteristics were not significant. CONCLUSION: In this Australian cohort of HPV-OPC survivors there was significant discordance between clinician- and patient-reported toxicity. We observed population comparable global quality of life and low rates of emotional distress. However, we identified a low-functioning subgroup reporting significantly worse outcomes on a range of patient-reported measures who may benefit from targeted support.

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

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.

[Classification of idiopathic inflammatory myopathies based on clinical manifestations and myositis-specific antibodies].

OBJECTIVE: To investigate the classification of idiopathic inflammatory myopathies (IIM) based on clinical manifestations and myositis- specific antibodies using cluster analysis. METHODS: We retrospectively analyzed the data of patients with IIM admitted in Nanfang Hospital in 2015-2019. The clinical data of the patients including serum creatine kinase (CK), interstitial lung disease (ILD), cancer, and myositis-specific antibodies were collected for two-step cluster analysis to identify the distinct clusters of patients, whose clinical characteristics were subsequently analysed. RESULTS: A total of 71 patients with IIM were included in this study, including 30 (42.3%) with polymyositis (PM), 20 (28.2%) with classic dermatomyositis (DM), 16 (22.5%) with amyopathic dermatomyositis (CADM), and 5 (7.0%) with immune-mediated necrotizing myopathy (IMNM). Two-step cluster analysis identified 3 distinctive subgroups: Cluster 1 of 15 (51.7%) patients characterized by rash, positive anti-MDA5 antibody and hypoproteinemia (P < 0.05) with normal or slightly elevated CK level, mainly corresponding to CADM; Cluster 2 of 4 (57.1%) patients with significantly elevated CK and positive anti-SRP antibody (P < 0.001) corresponding to IMNM; and Cluster 3 of 17 (48.6%) patients consisting primarily of patients with PM, characterized by positivity for anti- aminoacyl transfer RNA synthetases antibodies (P=0.022) corresponding to antisynthetase syndrome (ASS). CONCLUSIONS: Patients with IIM can be divided into 3 subgroups based on their clinical and serological characteristics (especially myositis-specific antibodies), and among them ASS may represent an independent IIM subgroup with unique clinical characteristics.

Well-being, familial risk, and transfusion interval in thalassemia-affected families: A two-step cluster analysis.

BACKGROUND: Thalassemia is an inherited blood disorder which is one of the common genetic disorders among children that is increasing worldwide. AIM AND OBJECTIVE: This study aimed to identify clustering patterns among thalassemia-affected families based on their well-being, transfusion interval, and risk factors using two-step cluster analysis (TCA). METHODS: The study design is a descriptive, analytical cross-sectional study. The study sample consisted of 125 thalassemia children along with either one of the parents who referred to a thalassemia treatment center of a pediatric hospital in Chennai, Tamil Nadu. The parents and children were evaluated using the Ryff Psychological Well-being Scale and Kidscreen Questionnaire respectively. Data were analyzed using SPSS version 16.0 software. RESULTS: Out of 125 parents, 86 were father (68.8%) and 39 were mother (31.2%). The mean age of parents was 38 years. Similarly, out of 125 thalassemia-affected children, the mean age of children was 13 years. Six clusters were deducted from the TCA. Parents' well-being variable does not have discriminating power to form cluster division. Three cluster formations were meaningful. CONCLUSION: TCA, in this study, helps in finding the clusters of families with thalassemia-affected children associated with poor well-being and familial risks, which require attention for medical counseling.

Predictability and interpretability of hybrid link-level crash frequency models for urban arterials compared to cluster-based and general negative binomial regression models.

Machine learning (ML) techniques have higher prediction accuracy compared to conventional statistical methods for crash frequency modelling. However, their black-box nature limits the interpretability. The objective of this research is to combine both ML and statistical methods to develop hybrid link-level crash frequency models with high predictability and interpretability. For this purpose, M5' model trees method (M5') is introduced and applied to classify the crash data and then calibrate a model for each homogenous class. The data for 1134 and 345 randomly selected links on urban arterials in the city of Charlotte, North Carolina was used to develop and validate models, respectively. The outputs from the hybrid approach are compared with the outputs from cluster-based negative binomial regression (NBR) and general NBR models. Findings indicate that M5' has high predictability and is very reliable to interpret the role of different attributes on crash frequency compared to other developed models.