Pain in midlife women: a growing problem in need of further research

Pavlović, Jelena; Derby, Carol A.

doi:10.1186/s40695-022-00074-x

Cited by 5 publications

(4 citation statements)

References 47 publications

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“…We speculate that women may be more prone to chronic pain due to specific physiological and psychological gender-specific characteristics. 16,17 Pavlović et al 18 also showed differences in chronic pain predisposition between male and female patient. Female endocrine and nervous systems are more sensitive than males, and affected by various factors, which makes them more prone to chronic pain.…”

Section: Discussionmentioning

confidence: 95%

“…Female endocrine and nervous systems are more sensitive than males, and affected by various factors, which makes them more prone to chronic pain. 18 , 19 In addition, hormonal changes during childbirth and menopause can affect pain sensitivity. 20 Moreover, psychological and socioeconomic factors may also influence predisposition to chronic pain.…”

Section: Discussionmentioning

confidence: 99%

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Construction and validation of chronic pain prediction model after total knee arthroplasty

Qian,

Wang

2024

Pak J Med Sci

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Objective: To explore the risk factors of chronic pain after total knee arthroplasty (TKA) and to establish and verify a prediction model. Methods: As a retrospective observational study, medical records of 239 patients who underwent TKA in Affiliated Hospital of Jiangnan University from January 2020 to December 2022 were reviewed. Fifty four patients suffered from chronic pain after TKA surgery. Univariate and multivariate logistic regression were used to analyze factors associated with the occurrence of chronic pain after TKA. A nomogram prediction model was established based on the identified independent risk factors, and its predictive effectiveness was evaluated. Results: Gender, postoperative 24-hourss numerical rating scale (NRS) and postoperative three months Hospital for Special Surgery Knee-Rating (HSS) scores were independent risk factors for chronic pain after TKA (p<0.05). The area of the receiver operating characteristic (ROC) of the nomogram model based on these factors was 0.904 (95% confidence interval [CI): 0.861-0.947), which indicates a good predictive value for the postoperative chronic pain. When the optimal cut off value was selected, the sensitivity and specificity of the model were 92.6% and 74.1%, respectively, indicating that the predictive model is effective. Conclusions: Gender, postoperative 24-hours NRS and postoperative three months HSS score are independent risk factors for chronic pain after TKA. The nomogram prediction model based on these factors is effective and can provide auxiliary reference for patients with chronic pain after TKA. doi: https://doi.org/10.12669/pjms.40.4.8979 How to cite this: Qian J, Wang X. Construction and validation of chronic pain prediction model after total knee arthroplasty. Pak J Med Sci. 2024;40(4):657-662. doi: https://doi.org/10.12669/pjms.40.4.8979 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

Construction and validation of chronic pain prediction model after total knee arthroplasty

Qian,

Wang

2024

Pak J Med Sci

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“…One might assume more sensitive skin sensation in women because of lower skin thickness, softertexture of the skin and more superficial vascularization and innervation. In general, studies report a lower pain level in women [ 31 , 32 ]. An additional finding could be documented comparing shaved or not shaved skin area in men [ 30 ].…”

Section: Discussionmentioning

confidence: 99%

Somatosensory and Gustatory Profiling in the Orofacial Region

et al. 2022

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Quantitative sensory testing (QST) is a standard procedure in medicine to describe sensory patterns in various pathologies. The aim of this prospective clinical study was to define reference values of the trigeminal nerve (V3), including taste qualities, to create a compatibility for sensory loss or gain in pathologies. Fifty-one patients were included, and a standardized testing battery with 11 QST parameters according to the German Research Network on Neuropathic Pain (DFNS) was applied complemented by quantitative gustatory assessments. Significant somatosensory differences were found between the test sites (MDT at the chin, WDT at the lower lip) but no effect was detected for gender, age, and between body types. Taste sensitivity was dependent on concentration, gender (females being more sensitive) and increasing age (for bitter and sour taste). We provide reference values for somatosensory and gustatory testing of the facial area. Our data facilitate the detection of neurosensory abnormalities in the orofacial region. This might also serve as a control setting for COVID-19.

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“…Previous reviews of opioids have studied opioid use disorders and opioid misuse in primary care settings [39][40][41]. For example, younger age groups or female groups in primary care settings are often under-studied with poorly reported prevalence and risk factors [42][43][44][45]. To our best knowledge, a review of opioid prescriptions for chronic non-cancer pain patients in primary care providers based on large routinely collected electronic health records, claims, and observational datasets, which we term "big data", remains lacking.…”

Section: Introductionmentioning

confidence: 99%

Epidemiology of chronic pain and opioid use in primary care – a scoping review of big data research

Lin

Zhu

Murray

et al. 2023

Preprint

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Objective Recent research addressing the opioid use and misuse crisis in patients with chronic non-cancer pain in primary care has focused on traditional cohort studies underpinned by survey data. The advent of electronic health records creates a ′big data′ opportunity for improving our understanding of the epidemiology of chronic non-cancer pain in primary care and opioid use and misuse. This scoping review aimed to map the chronic non-cancer pain patient population in primary care using big data research, investigating the patient characteristics and opioid prescription patterns. Methods Searches of primary electronic databases and grey literature, including OVID, CINAHL, and Scopus, were performed from January 1, 2010 to December 2, 2022. The search strategy was restricted to the English language. Results A total of 1,057 records from databases and 515 records from grey literature were considered. Of these, only three articles met the eligibility criteria, and two articles of these reported an estimated chronic pain prevalence of 3.82% and 10.3% in the primary care setting. Chronic pain patients that presented to primary care providers were predominately female, and common comorbidities were anxiety and depression. An estimated 30% of chronic pain patients used opioids for treatment sourced from general practitioners and family practitioners. Conclusion The use of big data remains underutilized for investigating the epidemiology of chronic pain and opioid use in primary care. This review calls for a greater focus on pain informatics with big data to improve the accuracy of future clinical chronic pain epidemiology studies.

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Pain in midlife women: a growing problem in need of further research

Cited by 5 publications

References 47 publications

Construction and validation of chronic pain prediction model after total knee arthroplasty

Construction and validation of chronic pain prediction model after total knee arthroplasty

Somatosensory and Gustatory Profiling in the Orofacial Region

Epidemiology of chronic pain and opioid use in primary care – a scoping review of big data research

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