Aim: To assess the feasibility of a patient-centered complex intervention for multimorbidity (CIM) based on general practice in collaboration with community health-care centers and outpatient clinics.
Methods: Inclusion criteria were age ≥18 years, diagnoses of two or more of three chronic conditions (diabetes, chronic obstructive pulmonary disease (COPD), and chronic heart conditions), and a hospital contact during the previous year. The CIM included extended consultations and nurse care manager support in general practice and intensified cross-sectorial collaboration. Elements included a structured care plan based on patients' care goals, coordination of services, and, if appropriate, shifting outpatient clinic visits to general practice, medication review, referral to rehabilitation, and home care. The acceptability dimension of feasibility was assessed with validated questionnaires, observations, and focus groups.
Results: Forty-eight patients were included (mean age 72.2 (standard deviation (SD) 9.5, range 52-89); 23 (48%) were men. Thirty-seven patients had two diseases; most commonly COPD and cardiovascular disease (46%), followed by diabetes and cardiovascular disease (23%), and COPD and diabetes (15%). Eleven (23%) patients had all three conditions. Focus group interviews with patients with multimorbidity identified three main themes: (1) lack of care coordination existed across health-care sectors before the CIM, (2) extended consultations provided better care coordination, and (3) patients want to be involved in planning their treatment and care. In focus groups, health-care professionals discussed two main themes: (1) patient-centered care and (2) culture and organizational change. Completion rates for questionnaires were 98% (47/48).
Conclusions: Patients and health-care professionals found the CIM acceptable.
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http://dx.doi.org/10.1177/2235042X20935312 | DOI Listing |
Gastric Cancer
January 2025
Department of Medical Oncology, Hospital Clinico Universitario, INCLIVA, Biomedical Research Institute, University of Valencia, Avenida Menendez Pelayo nro 4 accesorio, Valencia, Spain.
Introduction: Gastric cancer (GC) burden is currently evolving with regional differences associated with complex behavioural, environmental, and genetic risk factors. The LEGACy study is a Horizon 2020-funded multi-institutional research project conducted prospectively to provide comprehensive data on the tumour biological characteristics of gastroesophageal cancer from European and LATAM countries.
Material And Methods: Treatment-naïve advanced gastroesophageal adenocarcinoma patients were prospectively recruited in seven European and LATAM countries.
Int J Comput Assist Radiol Surg
January 2025
Faculty of Computer Science and Research Campus STIMULATE, Otto-von-Guericke University of Magdeburg, Magdeburg, Germany.
Purpose: Structured abdominal examination is an essential part of the medical curriculum and surgical training, requiring a blend of theory and practice from trainees. Current training methods, however, often do not provide adequate engagement, fail to address individual learning needs or do not cover rare diseases.
Methods: In this work, an application for structured Abdominal Examination Training using Augmented Reality (AETAR) is presented.
NPJ Prim Care Respir Med
January 2025
Université Paris Cité, Department of general practice, Paris, France, Paris, France.
Streptococcus pneumoniae (SP) remains an important cause of community acquired pneumonia (CAP). We aimed to describe the prevalence and characteristics of outpatients with radiologically confirmed pneumococcal CAP. Between November 2017 and December 2019, a French network of general practitioners enrolled CAP-suspected adults, with ≥1 clinical signs of infection and ≥1 signs of pulmonary localization in an observational study.
View Article and Find Full Text PDFNat Commun
January 2025
Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs & Fisheries college, Jimei University, Xiamen, Fujian, People's Republic of China.
Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains challenging. In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms.
View Article and Find Full Text PDFEnviron Health
January 2025
Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 bus 7001 block h, Leuven, 3000, Belgium.
Background: The detection of a local per- and polyfluoroalkyl substances (PFAS) pollution hotspot in Zwijndrecht (Belgium) necessitated immediate action to address health concerns of the local community. Several human biomonitoring (HBM) studies were initiated, gathering cross-sectional exposure data from more than 10,000 participants. The linkage of these HBM data with primary care health registries might be a useful new tool in environmental health analysis.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!