Aim: Pain is prevalent in geriatric patients and is not only a signal of physical diseases but also a symptom of mental health problems. This study aimed to explore the relationship between pain and depression in geriatric patients scheduled for orthopaedic surgery.
Methods: The study used a correlational and cross-sectional design. The study sample consisted of geriatric patients (n = 200) scheduled for orthopaedic surgery in a research and training hospital in northern Turkey. Data were collected by the researchers using the Geriatric Pain Measure and Geriatric Depression Scale. In the data analysis, descriptive statistics, Pearson's correlation, and hierarchical regression analysis were used.
Results: The patients' mean age was 73.16 ± 8.27 years. It was found that 5.5% (n = 11) of the participants had mild pain, 45.5% (n = 91) had moderate pain, and 49% (n = 98) had severe pain. There was a positive and moderate significant relationship between the mean Geriatric Pain Measure and Geriatric Depression Scale scores (r = 0.479, P < 0.01). Age (β = 0.133; P < 0.05) and education (β = 2.484; P < 0.05) were statistically significantly associated with depression. There was a significant and positive relationship between depression and being dependent in activities of daily living (β = 5.098; P < 0.05).
Conclusion: This study demonstrated that geriatric patients who were older, illiterate, dependent in activities of daily living, and with higher levels of pain had higher depression. A multidisciplinary team approach including nurses should be utilised in pain management and it should not be ignored that severe pain may be associated with depression in geriatric patients.
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http://dx.doi.org/10.1111/psyg.12892 | DOI Listing |
J Adv Nurs
January 2025
Nursing Science (INS), Department Public Health (DPH), Faculty of Medicine, University of Basel, Basel, Switzerland.
Aim: To implement and evaluate an Advanced Practice Nurse-led transitional care model (AdvantAGE) to reduce rehospitalisation rates in frail older adults discharged from a Swiss geriatric hospital.
Design: The study adopts an effectiveness-implementation hybrid design (Type 1) to simultaneously evaluate the effectiveness of the care model and explore the implementation process.
Methods: The primary outcome, the 90-day rehospitalisation rate, will be evaluated using a matched-cohort design with a prospective intervention group and a retrospective control group.
J Adv Nurs
January 2025
College of Nursing, SUNY Upstate Medical University, Syracuse, New York, USA.
Aim: To review older persons' lived experiences and perceptions of loneliness in residential care facilities and characterise mechanisms underlying their experiences through a comprehensive loneliness model.
Design: A systematic review synthesising qualitative research on the experiences of loneliness among older people living in residential care facilities.
Methods: This review followed Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines with quality appraisal conducted using the Critical Appraisal Skills Programme checklist.
BMC Anesthesiol
January 2025
Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA, 94612, USA.
Background: Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data.
Methods: Patients 65-years and older undergoing urgent or emergency non-cardiac surgery within 21 hospitals 2017-2021 were used to develop the model (randomly split: 80% training, 20% test).
BMC Health Serv Res
January 2025
Emergency Medicine, Vanderbilt University Medical Center and, Veterans Affairs Tennessee Valley Healthcare System, Geriatric Research, Education and Clinical Center (GRECC), Nashville, TN, USA.
Background: Heart failure is a major public health concern, affecting 6.7 million Americans. An estimated 16% of emergency department (ED) patients with acute heart failure (AHF) are discharged home.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China.
Purpose: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pelvic lymph node dissection (ePLND) by preoperative nomograms.
Methods: [Ga]Ga-PSMA-617 PET/CT scan of 116 eligible PCa patients (82 in the training cohort and 34 in the test cohort) who underwent radical prostatectomy with ePLND were analyzed in our study. The Med3D deep learning network was utilized to extract discriminative features from the entire prostate volume of interest on the PET/CT images.
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