Background: To investigate patients' perspectives on polypharmacy and the use of a digital decision support system to assist general practitioners (GPs) in performing medication reviews.
Methods: Qualitative interviews with patients or informal caregivers recruited from participants in a cluster-randomized controlled clinical trial (cRCT). The interviews were transcribed verbatim and analyzed using thematic analysis.
Results: We conducted 13 interviews and identified the following seven themes: the patients successfully integrated medication use in their everyday lives, used medication plans, had both good and bad personal experiences with their drugs, regarded their healthcare providers as the main source of medication-related information, discussed medication changes with their GPs, had trusting relationships with them, and viewed the use of digital decision support tools for medication reviews positively. No unwanted adverse effects were reported.
Conclusions: Despite drug-related problems, patients appeared to cope well with their medications. They also trusted their GPs, despite acknowledging polypharmacy to be a complex field for them. The use of a digital support system was appreciated and linked to the hope that reasons for selecting specific medication regimens would become more comprehensible. Further research with a more diverse sampling might add more patient perspectives.
Trial Registration: ClinicalTrials.gov, NCT03430336 . Registered on February 6, 2018.
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http://dx.doi.org/10.1186/s12875-021-01517-6 | DOI Listing |
PeerJ
December 2024
Department of General Surgery, Nanjing Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Background: Postoperative complications are prone to occur in patients after radical pancreaticoduodenectomy (PD). This study aimed to construct and validate a model for predicting postoperative major complications in patients after PD.
Methods: The clinical data of 360 patients who underwent PD were retrospectively collected from two centers between January 2019 and December 2023.
Cureus
November 2024
Department of Trauma and Orthopaedics, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, GBR.
Introduction Orthopaedic surgery frequently involves the use of intra-operative radiographs, commonly taken with surgeons standing in close proximity to the X-ray machine. Radiation training and appropriate radiation protection minimise the harm that surgeons can face from ionising radiation. This study evaluates the current state of radiation training and protective equipment available to orthopaedic surgeons in the East of England.
View Article and Find Full Text PDFFront Oncol
December 2024
Analysis of Circulating Tumor Cells, Laboratory of Analytical Chemistry, Department of Chemistry, University of Athens, Athens, Greece.
Introduction: Detection of mutations in primary tumors and liquid biopsy samples is of increasing importance for treatment decisions and therapy resistance in many types of cancer. The aim of the present study was to directly compare the efficacy of a relatively inexpensive ultrasensitive real-time PCR with the well-established and highly sensitive technology of ddPCR for the detection of the three most common hotspot mutations of , in exons 9 and 20, that are all of clinical importance in various types of cancer.
Patients And Methods: We analyzed 42 gDNAs from primary tumors (FFPEs), 29 plasma-cfDNA samples, and 29 paired CTC-derived gDNAs, all from patients with ER+ metastatic breast cancer, and plasma from 10 healthy donors.
Future Oncol
December 2024
Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, P.R. China.
Background: The global incidence of prostate cancer (PCa) is rising, necessitating improved diagnostic strategies. This study explores coagulation parameters' predictive value for clinically significant PCa (csPCa) and develops a nomogram.
Research Design And Methods: This study retrospectively analyzed data from 702 patients who underwent prostate biopsy at Shandong Provincial Hospital (SDPH) and 142 patients at Shandong Cancer Hospital and Institute (SDCHI).
Curr Med Imaging
December 2024
Department of Radiology, Affiliated Hospital of Chengde Medical College, Chengde, China.
Objective: This study aimed to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model to address the limitations of manual segmentation, which is known to be susceptible to inter-observer variability. Subsequently, a prediction model for gastric cancer (GC) differentiation was constructed alongside radiomics, and a nomogram was generated to investigate its clinical guiding significance.
Methods: This study enrolled 262 patients with pathologically confirmed GC.
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