Purpose: In developing our Patient-Centered Team Care (PCTC) program, we designed a Plan-of-Care (POC) tool to facilitate the physician-patient discussion for setting health goals. This study aimed to determine the effectiveness of the POC tool in improving clinical outcomes.
Methods: We compared baseline and 6-month or greater follow-up values for hemoglobin A1c (HbA1c), low-density lipoprotein (LDL), systolic blood pressure (SP), diastolic blood pressure (DP), and weight for PCTC patients (intervention group) and non-PCTC patients (control group). For the intervention group, we also compared POC tool completeness scores (1, low and 8, high).
Results: Of 1366 patients, 1110 (593 intervention, 517 control) had baseline and follow-up clinical measures for analysis. After adjusting for demographics, significant effects occurred in the intervention group for HbA1c (P = .0067), LDL (P = .012), and DP (P = .091). For completeness of POC, a significant association occurred between more fully completed forms (scores, 5-8) and change in HbA1c (P < .001) and SP (P = .011).
Conclusion: Patients receiving a POC showed significant improvement in 3 of 5 clinical outcomes compared with those without the tool, and those with more fully completed forms had significant improvement in 2 of 5 clinical outcomes compared with those with partially completed forms.
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http://dx.doi.org/10.1097/QMH.0b013e318213e728 | DOI Listing |
Sci Rep
December 2024
Department of Biology, University of South Dakota, 414 East Clark Street, Vermillion, SD, 57069-2390, USA.
Psychological distress, including anxiety or mood disorders, emanates from the onset of chronic/unpredictable stressful events. Symptoms in the form of maladaptive behaviors are learned and difficult to treat. While the origin of stress-induced disorders seems to be where learning and stress intersect, this relationship and molecular pathways involved remain largely unresolved.
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December 2024
Health Services Research and Pharmacoepidemiology Unit, Foundation for the Promotion of Health and Biomedical Research of Valencia Region (FISABIO), Avenida Cataluña, 21, 46020, Valencia, Spain.
Improvement of post-stroke outcomes relies on patient adherence and appropriate therapy maintenance by physicians. However, comprehensive evaluation of these factors is often overlooked. This study assesses secondary stroke prevention by differentiating patient adherence to antithrombotic treatments (ATT) from physician-initiated interruptions or switches.
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December 2024
Postgraduate Program in Health Sciences, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, RN, Brazil.
Body composition abnormalities are prognostic markers in several types of cancer, including colorectal cancer (CRC). Using our data distribution on body composition assessments and classifications could improve clinical evaluations and support population-specific opportune interventions. This study aimed to evaluate the distribution of body composition from computed tomography and assess the associations with overall survival among patients with CRC.
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December 2024
Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK.
Network hypersynchrony is emerging as an important system-level mechanism underlying seizures, as well as cognitive and behavioural impairments, in children with structural brain abnormalities. We investigated patterns of single neuron action potential behaviour in 206 neurons recorded from tubers, transmantle tails of tubers and normal looking cortex in 3 children with tuberous sclerosis. The patterns of neuronal firing on a neuron-by-neuron (autocorrelation) basis did not reveal any differences as a function of anatomy.
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December 2024
Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
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