ArticlePloS one2020
Exploring demands of hemodialysis patients in Taiwan: A two-step cluster analysis.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05833451 (Is Reiki Effective In Coping With the Symptoms Experienced by Patients Undergoing Hemodialysis?), which is not on this map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Is Reiki Effective In Coping With the Symptoms Experienced by Patients Undergoing Hemodialysis?: Single-Blind Randomized Controlled Trial
Who cites it
7 citing papers in PubMed.
- Data-driven cluster analysis identifies three clinical phenotypes in hemodialysis patients.Renal failure · 2025Article
- A novel scoring system for better management of small bowel obstruction.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2025Article
- Factors Associated with the Quality of Life and Needs of Hemodialysis Patients in Saudi Arabia: A Basis for Improved Care.Medicina (Kaunas, Lithuania) · 2025Article
- Article
- Factors Related to Quality of Life of Hemodialysis Patients during the COVID-19 Pandemic.Healthcare (Basel, Switzerland) · 2023Article
- Complementary Feeding and Malnutrition among Infants and Young Children Aged 6-23 Months in Rural Areas of China.Nutrients · 2022Article
- The Effect of Statins in Cancer Risk Reduction in Patients on Dialysis: A Population-Based Case-Control Study.Journal of clinical medicine · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AIMS AND
objectivesTo classify hemodialysis patients into subgroups via cluster analysis according to the Somatic Symptoms Disturbance Index, Taiwanese Depression Scale, and Herth Hope Index scores. Patient demands in each cluster were also examined.
backgroundOverall patient demands among hemodialysis patients have been demonstrated in numerous reports; however, variables among subgroups have not been explored.
methodsData were analyzed from a cross-sectional survey of 114 hemodialysis patients recruited from dialysis centers in Northern Taiwan. Hope, depression, and symptom disturbance were used as parameters for clustering because they have been shown to be important factors affecting patient demands. A two-step cluster analysis was performed to classify participants into clusters. Patient demands in each cluster were analyzed.
resultsAmong the 114 participants, there was a negative correlation between hope and depression as well as between hope and symptom disturbance; there was a positive correlation between depression and symptom disturbance. Two clusters were identified: Cluster 1 (n = 49) included patients with moderate levels of hope and symptom disturbance, and high levels of depression; and Cluster 2 (n = 65) included patients with low levels of depression and symptom disturbance and high levels of hope. Demographic profiles differed between the two clusters. Regarding patient demands, medical demand showed the highest average score; whereas, occupational demand exhibited the lowest average score. Psychological and occupational demands differed significantly between the two clusters. The two clusters were defined as subgroups: Cluster 1 was labeled "resting"; Cluster 2 was labeled "active".
conclusionsCluster analysis may further classify hemodialysis patients into distinct subgroups base on their specific patient demands. A better understanding of patient demands may help health professionals to provide a holistic individualized treatment to improve patients' outcomes.
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