Longitudinal Trajectories of Depressive Symptoms Among Patients With Knee Osteoarthritis: The Role of Pain Intensity

Yan, Zeping; Wang, Zhiwei; Liang, Qian; Liu, Jian; Wu, Shiqian; Luan, Xiaorong

doi:10.1016/j.pmn.2022.10.005

Cited by 5 publications

(4 citation statements)

References 33 publications

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“…Importantly, anticipating a patient's specific postoperative outcome and clinical trajectory requires simultaneous consideration of several different patient-specific factors. Applications of AI in preoperative evaluation include determining candidacy for surgery and identification of factors associated with achieving meaningful, patient-specific postoperative outcomes 34-60 (Table I), which may currently be the most frequent application of AI within orthopaedics. Because the current value-driven health care system places importance on clinically significant outcome improvements, PROMs serve an important role in the quantification of patient-perceived improvement and therefore help determine the quality of care that patients receive 61-65 .…”

Section: Preoperative Evaluation For Operative Planning and Patient-s...mentioning

confidence: 99%

“…Many studies examining the use of AI applications for prediction of postoperative PROMs remain in the derivation phase 36,51,57 and validation phase 39,54,59 , with no studies analyzing the impact of these applications in a clinical setting to the best of our knowledge. With most studies failing to externally validate their AI models, model use is left at a proof-of-concept stage, preventing use of the models in clinical practice 27,28,68,69 .…”

Section: Preoperative Evaluation For Operative Planning and Patient-s...mentioning

confidence: 99%

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Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence

Huffman,

Pasqualini,

Khan

et al. 2024

JBJS Reviews

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» The application of artificial intelligence (AI) in the field of orthopaedic surgery holds potential for revolutionizing health care delivery across 3 crucial domains: (I) personalized prediction of clinical outcomes and adverse events, which may optimize patient selection, surgical planning, and enhance patient safety and outcomes; (II) diagnostic automated and semiautomated imaging analyses, which may reduce time burden and facilitate precise and timely diagnoses; and (III) forecasting of resource utilization, which may reduce health care costs and increase value for patients and institutions.» Computer vision is one of the most highly studied areas of AI within orthopaedics, with applications pertaining to fracture classification, identification of the manufacturer and model of prosthetic implants, and surveillance of prosthesis loosening and failure.» Prognostic applications of AI within orthopaedics include identifying patients who will likely benefit from a specified treatment, predicting prosthetic implant size, postoperative length of stay, discharge disposition, and surgical complications. Not only may these applications be beneficial to patients but also to institutions and payors because they may inform potential cost expenditure, improve overall hospital efficiency, and help anticipate resource utilization.» AI infrastructure development requires institutional financial commitment and a team of clinicians and data scientists with expertise in AI that can complement skill sets and knowledge. Once a team is established and a goal is determined, teams (1) obtain, curate, and label data; (2) establish a reference standard; (3) develop an AI model; (4) evaluate the performance of the AI model; (5) externally validate the model, and (6) reinforce, improve, and evaluate the model's performance until clinical implementation is possible.» Understanding the implications of AI in orthopaedics may eventually lead to wide-ranging improvements in patient care. However, AI, while holding tremendous promise, is not without methodological and ethical limitations that are essential to address. First, it is important to ensure external validity of programs before their use in a clinical setting. Investigators should maintain high quality data records and registry surveillance, exercise caution when evaluating others' reported AI applications, and increase transparency of the methodological conduct of current models to improve external validity and avoid propagating bias. By addressing these challenges and responsibly embracing the potential of AI, the medical field may eventually be able to harness its power to improve patient care and outcomes.

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Section: Preoperative Evaluation For Operative Planning and Patient-s...mentioning

confidence: 99%

Section: Preoperative Evaluation For Operative Planning and Patient-s...mentioning

confidence: 99%

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence

Huffman,

Pasqualini,

Khan

et al. 2024

JBJS Reviews

View full text Add to dashboard Cite

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“…While Yao et al [32] fail to explicitly mention depression as a possible osteoarthritis determinant or therapeutic target, Yan et al [33] concur that it is important to note that there is considerable heterogeneity in depressive symptoms and their trajectories among cases with knee osteoarthritis. Even though this does not include other forms of osteoarthritis, it is possible that pain intensity in this regard predicts the nature of these potentially differing depressive symptoms, regardless of disease site, and may be more successfully addressed than not by efforts to carefully incorporate strategies to address and reduce any modifiable degree of prevailing joint pain, and this topic should be carefully studied in its own right in the future.…”

Section: Journal Of Aging Research and Healthcarementioning

confidence: 99%

Osteoarthritis and Depression Update: 2023-Can the Stress and Coping Model Help?

Marks

2023

JARH

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Background Osteoarthritis and depression are both key barriers to healthy aging and greatly heighten the risk for many negative health issues that seriously impact life quality. When combined what are the implications? Aim This mini review examines 2023 data pertaining to osteoarthritis and depression and older adults and a possible theoretical framework of stress that may direct our approaches in the future. Methods and procedures Articles published between January 1 and August 15 2023 that addressed the current topic of interest and that were extracted from PUBMED, PubMed Central, Science Direct, and Google Scholar were carefully read and their key points arepresented in narrative form. Results As in the past, very few tangible theory-based prospective analyses that employ valid measures of depression and examine any association of any form of osteoarthritis longitudinally and in a consistent manner prevail. Several reports use the same or similar large cohort to draw upon, and find various degrees of clinical implications, but this may not embrace the need for more inclusivity, sampling strategies, control and diversity issues, as well as embracing the role of cognitions positive and negative. Conclusion Without efforts to develop sound research designs of diverse and carefully differentiated osteoarthritis substantive samples it is impossible to delineate the origin or implications of the osteoarthritis-depression linkage reported currently or arrive at a deep understanding of its relevance, to life quality and public health costs. What is needed to protect against or minimize either or both these clinically related disabling correlates in the aged population warrants timely study.

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“…[14][15][16] Musculoskeletal pain, myofascial pain, neuropathic pain, and visceral pain are the main types of pain that affect depression in patients. [17][18][19] Shoulder pain, [20,21] brain pain, [22] lumbar pain, [23] head pain, [24] lumbar pain, [25] neck pain, [26] and knee pain [27][28][29] are all highly correlated with depressive symptoms and are significant risk factors for depression in patients. From the perspective of different populations, the depressive symptoms of pain in women may not be more severe than those in men, [8] the depressive symptoms of lonely patients may be more severe than those of other patients, [30] and the depressive symptoms of patients with other complications may be more severe.…”

Section: Introductionmentioning

confidence: 99%

Association between pain intensity and depressive status in patients with hip fracture: An observational study

Jiang,

Sheng,

et al. 2024

Medicine

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Identifying depression symptoms in patients with hip fractures and studying the relationship between depression and pain intensity and pain location in hip fracture patients is of great significance for disease recovery in hip fracture patients. This cohort study analyzed 5 wave data from the China Health and Retirement Longitudinal Study in 2011, 2013, 2015, 2018, and 2020, focusing on 1222 patients with hip fractures. The study utilized the CESD-10 Depression Scale to assess depressive symptoms in hip fracture patients and conducted analyses to explore the relationship between depression symptoms, pain, and pain intensity, including binary logistic regression and examination of interaction terms between pain variables and pain intensity in key body parts. Depression symptoms are strongly associated with pain intensity in hip fracture patients, particularly in key body areas. Severe pain significantly increases the risk of depressive symptoms. Moreover, absence of pain in other key body parts is linked to depressive symptoms. Multivariate analysis reveals that higher education levels, marriage, urban residence, and self-rated good health serve as protective factors against depression, while diabetes and heart disease pose significant risks for depressive symptoms in hip fracture patients. Hip fracture pain can induce discomfort and trigger depressive symptoms, showing varied trajectories among patients. Pain intensity predicts the course of depressive symptoms, emphasizing the importance of tailored pain management strategies including medication, physical therapy, and nonpharmacological interventions. Personalized rehabilitation and mental health plans should be designed based on individual patient needs and differences.

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Longitudinal Trajectories of Depressive Symptoms Among Patients With Knee Osteoarthritis: The Role of Pain Intensity

Cited by 5 publications

References 33 publications

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence

Enabling Personalized Medicine in Orthopaedic Surgery Through Artificial Intelligence

Osteoarthritis and Depression Update: 2023-Can the Stress and Coping Model Help?

Association between pain intensity and depressive status in patients with hip fracture: An observational study

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