Specific Pain Characteristics Research Articles

Awake and Sleep Oral Behaviours in Patients With Painful Temporomandibular Disorders

The aim of this research was to explore the oral behaviours exhibited by individuals with and without temporomandibular disorders (TMD) pain, and with various pain characteristics; and to determine which oral behaviour is correlated with painful TMD. 328 patients with TMD who visited Orofacial Pain Clinic were included in this retrospective cross-sectional study. The patients were categorised into 2 groups-painful TMD and non-painful TMD-based on pain status; their other pain characteristics were recorded. To evaluate oral behaviours, researchers utilised the Oral Behaviors Checklist (OBC) and categorised into 3 levels based on the Diagnostic criteria for TMD scoring manual. To investigate the associations amongst demographic information, oral behaviour levels, and TMD pain status and characteristics, logistic regression was employed, whilst t tests were used to analyse OBC scores. Logistic regression was also used to examine individual oral behaviours in relation to specific pain characteristics. Age and marital status were associated with TMD pain status. Significantly higher OBC scores were observed in chronic pain compared to acute pain group, but the scores were not significantly different for pain status and other pain characteristics. OBC score and level were associated solely with TMD pain chronicity. According to multivariate logistic regression, "clench or grind teeth when sleeping" was the strongest predictor of TMD pain and "place tongue forcibly against teeth" was the strongest predictor of chronic painful TMD. High oral behaviour level and OBC scores were associated with chronic painful TMD. Sleep bruxism was the strongest predictor of TMD pain. Age and marital status were correlated with TMD pain status. In the treatment of TMD, there can be potential benefits in addressing and managing oral parafunctional behaviours.

Determinants of Pain-Induced Disability in German Women with Endometriosis during the COVID-19 Pandemic.

(1) Background: The main aim of this research was to examine the factors leading to pain-induced disability by assessing the impact of demographic, endometriosis-specific, pandemic-specific, and mental health factors. (2) Methods: Women with endometriosis who attended online support groups were invited to respond to an online survey during the first wave of the COVID-19 pandemic in Germany. The Pain Disability Index (PDI) was employed to assess disability-related daily functioning. Independent predictors of pain-induced disability were determined using univariate and multivariate logistic regression analyses. (3) Results: The mean PDI score of the study population was 31.61 (SD = 15.82), which was significantly higher (p < 0.001) than that reported in a previously published normative study of the German population. In the present study, a high level of pain-induced disability, as defined by scores equal to or higher than the median of the study population, older age (OR 1.063, 95% CI 1.010–1.120, p = 0.020), dysmenorrhea (OR 1.015, 95% CI 1.005–1.026, p = 0.005), dysuria (OR 1.014; 95% CI 1.001–1.027, p = 0.029), lower back pain (OR 1.018, 95% CI 1.007–1.029, p = 0.001), and impaired mental health (OR 1.271, 95% CI 1.134–1.425, p < 0.001) were found to be independent risk factors. Pandemic-specific factors did not significantly influence the pain-induced disability of the participants in this study. (4) Conclusions: The level of pain-induced disability was significantly higher among the women with endometriosis than among women in the normative German validation study. Our findings identified risk factors for experiencing a high level of pain-induced disability, such as demographic and specific pain characteristics. Pandemic-specific factors did not significantly and independently influence the pain-induced disability during the first wave of the COVID-19 pandemic in Germany. Impaired mental health negatively influenced functioning during daily activities. Thus, women with endometriosis should be managed by a multidisciplinary team of healthcare professionals to prevent negative effects of pain-induced disability on their quality of life.

Do Patients Really Have Pain with Quadriceps Fat Pad Edema?

To determine the appropriate MRI criteria for the radiological diagnosis of significant quadriceps fat pad edema, to investigate the relationship between these criteria and anterior knee pain, and to evaluate possible structural and positional factors in the etiology. In this retrospective case-control study, individuals with and without quadriceps fat pad edema in the knee MRIs taken between May 2016 and December 2018 were determined as the case and control groups, respectively, in a ratio of 1:1. The MRI criteria for significant quadriceps fat pad edema were set as 10mm and above the anterior-posterior diameter of the quadriceps fat pad, posterior convexity, and an increased signal in the fat-suppressed proton density sequence. The groups were compared for anterior knee pain, pain characteristics, working positions (sitting and standing), and MRI findings of structural factors. P < 0.05 was considered statistically significant. A total of 108 individuals were evaluated. Anterior knee pain was more common in the case group (49/54, p < 0.001) and was highly correlated with signs of quadriceps fat pad edema (R = -0,657). Frequent pain at night (18/54, p = 0.013), increased pain when walking upstairs (40/54, p = 0.003), knees are flexed (43/54, p < 0.001), and decreased pain when knees are extended (42/54, p < 0.001) were significantly high in the case group. No significant differences were observed in working position and structural factors. Quadriceps fat pad edema is significantly associated with anterior knee pain and certain specific pain characteristics.

Pain Characteristics and Biomarkers in Treatment Approaches for Osteoarthritis Pain

Osteoarthritis (OA) is a progressive disease and OA pain intensity is related to ongoing pathophysiological changes. However, OA pain is complex and multimodal; its characteristics, including severity, localization and the stimuli that elicit it, can change as the disease progresses and differ greatly among patients. Understanding mechanisms underlying specific pain characteristics may help guide clinicians in choosing appropriate treatments, targeting treatments to those patients most likely to benefit. Associations have been demonstrated between biomarkers and some characteristics of OA pain, and to processes linked to the shift in pain characteristics over the course of OA. This article examines how understanding OA pain characteristics and their relation to the disease process could inform treatment choice when applying well-established treatment guidelines.

Identifying predictive factors for neuropathic pain after breast cancer surgery using machine learning

IntroductionNeuropathic pain (NP) remains a major debilitating condition affecting more than 26% of breast cancer survivors worldwide. NP is diagnosed using a validated 10-items Douleur Neuropathique - 4 screening questionnaire which is administered 3 months after surgery and requires patient-doctor interaction. To develop an effective prognosis model admissible soon after surgery, without the need for patient-doctor interaction, we sought to [1] identify specific pain characteristics that can help determine which patients may be susceptible to NP after BC surgery, and 2) assess the utility of machine learning models developed in objective [1] as a knowledge discovery tool for downstream analysis. MethodsThe dataset is from a prospective cohort study of female patients scheduled to undergo breast cancer surgery for the first time at the Jewish General Hospital, Montreal, Canada between November 2014 and March 2019. NP was assessed at 3 months after surgery using Douleur Neuropathique – 4 interview scores (in short, DN4-interview; range: 0–7). For the primary analysis, we constructed six ML algorithms (least square, ridge, elastic net, random forest, gradient boosting, and neural net) to identify the most relevant predictors for DN4-interview score; and compared model performance based on root mean square error (RMSE). For the secondary analysis, we built a logistic classification model for neuropathic pain (DN4-interview score ≥ 3 versus DN4-interview score < 3) using the relevant-consensus-predictors from the primary analysis. ResultsAnxiety, type of surgery, preoperative baseline pain and acute pain on movement were identified as the most relevant predictors for DN4 - interview score. The least square regression model (RMSE = 1.43) is comparable in performance with random forest (RMSE = 1.39) and neural network model (RMSE = 1.50). The Gradient boosting model (RMSE = 1.16) outperformed the models compared including the penalized regression models (ridge regressions, RMSE = 1.28; and elastic net, RMSE = 1.31). In the secondary analysis, the preferred logistic regression classier for NP had an area under the curve (AUC) of 0.68 (95% CI = 0.57 to 0.79). Anxiety was significantly associated with the likelihood of NP (odds ratio = 2.18; 95% CI = 1.05–4.49). In comparison to their counterparts, the odds of NP were higher in participants with acute pain on movement or with present preoperative baseline pain or participants who performed total mastectomy surgery, but the differences were not statistically significant. ConclusionsModern machine learning models show improvements over traditional least square regression in predicting of DN4-interview score. Penalized regression methods and the Gradient boosting model out-perform other models. As a predictor discovery tool, machine learning algorithms identify relevant predictors for DN4-interview score that remain statistically significant indicators of neuropathic pain in the classification model. Anxiety, type of surgery and acute pain on movement remain the most useful predictors for neuropathic pain.

Osteoarthritis Increases Paresthestic and Akathisic Pain, Anxiety Case-ness, and Depression Severity in Patients With Parkinson's Disease.

Objective: Parkinson's disease (PD) patients are known to suffer from pain, anxiety, and depression, but the exact degree of association between the two is unknown. As many PD patients also suffer from physical impairments, this cross-sectional case-control study sets out to compare and determine the case-ness of pain, anxiety and depression in PD patients that suffer with or without symptomatic osteoarthritis (OA). The goal of this study, therefore, was to observe if additional pain associated with comorbid OA in PD patients is correlated with greater depression and anxiety rates. The importance of understanding the burden of pain and increased depression severity of PD and OA patients is so that they may be screened appropriately based on the symptoms, which may increase their overall quality of life.Methods:This cross-sectional case-control study included 3 groups of 34 patients and 78 healthy age and gender-matched control participants. PD patients with symptomatic OA (PD+OA), PD patients without symptomatic OA (PD), patients with symptomatic OA but no PD (OA), and healthy control participants (Control). A PD patient group with Restless Legs Syndrome (PD+RLS) of 27 patients was also included. All participants completed questionnaires to assess for pain, depression, and anxiety.Results:PD+OA and PD patients had worsened depression severity and were more likely to report anxiety and depression case-ness than OA patients. PD+OA patients were more likely to complain about paresthestic and akasthisic pain, but less likely to complain about aching pain compared to PD patients and OA patients. PD+OA patients were more likely to have greater pain severity, and were more likely to report radiating and sharp pain than PD+RLS patients. PD+OA patients were also more likely to report higher depression case-ness than PD+RLS patients.Conclusion:PD with OA seems to be linked with specific pain characteristics (akathisia and paraesthesia) as well as heightened overall pain severity and pain interference in comparison to OA alone, PD alone and PD with RLS. PD is also correlated with depression severity and anxiety case-ness in OA when compared to the OA alone, PD alone and PD with RLS.

Increased likelihood of anxiety and poor sleep quality in Parkinson's disease patients with pain

BackgroundPain is a bothersome non-motor symptom in patients with Parkinson's disease (PD), but the relationships between PD, presence of pain, different pain characteristics, and other non-motor symptoms such as mood and sleep disturbances are unclear. ObjectiveTo investigate the relationship between PD and pain as well as specific subtypes of pain with anxiety, depression and sleep quality. MethodsThis cross-sectional case-control study included two groups of PD patients; one with (n=37) and one without pain (n=37). Healthy controls with (n=37) and without pain (n=37) were recruited and matched to the PD groups for age and gender. All participants completed questionnaires regarding pain, mood and sleep. ResultsPD patients with pain showed significantly higher anxiety severity and poorer sleep quality than PD patients without pain. Compared to controls with pain, PD patients with pain had more anxiety, depression and worsened sleep quality. PD patients with pain were more likely to report akathisic, tension and sharp pain compared to controls with pain, but these three pain characteristics did not correlate with each other. There were no differences in depression, anxiety, or sleep between PD patients with akathisic, tension and sharp pain and those without. ConclusionPain in PD seems to be linked with specific pain characteristics (akathisic, tension and sharp pain) as well as heightened anxiety and worsened sleep quality. Integrative approach treatments which address pain in PD may also improve anxiety and sleep quality.

Occurrence, Characteristics, and Predictors of Pain in Patients with Chronic Obstructive Pulmonary Disease

Few studies have provided a detailed characterization of pain in patients with chronic obstructive pulmonary disease (COPD). The aims of this cross-sectional study were to describe the occurrence, intensity, locations, and level of interference associated with pain, as well as pain relief; to identify differences in demographic, clinical, and symptom characteristics between COPD patients with and without pain; and to determine which demographic, clinical, and symptom characteristics were associated with average pain, worst pain, and pain interference. A total of 258 patients with COPD provided information on demographic characteristics; comorbidities; respiratory parameters including dyspnea; body mass index; and symptom characteristics (i.e., anxiety, depression, sleep disturbance, and fatigue). Pain was measured using the Brief Pain Inventory. Of these 258 COPD patients, 157 (61%) reported pain. Multiple linear regression analyses were performed to determine which demographic, clinical, and symptom characteristics were associated with average pain severity, worst pain severity, and mean pain interference. Lower stages of COPD were associated with higher worst pain and higher pain interference scores. Higher depression scores were associated with higher average pain and higher pain interference scores. In addition, higher number of pain locations was associated with higher average and higher worst pain severity scores. Findings from this study confirm that pain is a significant problem and highlights the need for specific pain management interventions for patients with COPD. More research is needed about specific pain characteristics and symptoms to gain an increased knowledge about the causes of pain in these patients.

Pain and the onset of depressive and anxiety disorders

Patients with pain may be at increased risk of developing a first episode of depressive or anxiety disorder. Insight into possible associations between specific pain characteristics and such a development could help clinicians to improve prevention and treatment strategies. The objectives of this study were to examine the impact of pain symptomatology on depression and anxiety onset and to determine whether these associations are independent of subthreshold depressive and anxiety symptoms. Data from the Netherlands Study of Depression and Anxiety, collected between 2004 and 2011, were used. A total of 614 participants with no previous history and no current depression or anxiety at baseline were followed up for 4years. Onset of depressive or anxiety disorder was assessed at 2- and 4-year follow-up by Composite International Diagnostic Interview. Baseline pain characteristics were location, duration, and severity, as assessed by chronic pain grade. Onset of depressive or anxiety disorder occurred in 15.5% of participants. Using Cox survival analyses, onset of depression and anxiety was associated with 6 pain locations (neck, back, head, orofacial area, abdomen, and joints; hazard ratio [HR]=1.96 to 4.02; P<.05), increasing number of pain locations (HR=1.29; P<.001), and higher severity of pain (HR=1.57; P<.001). By contrast, there was no association with duration of pain symptoms (HR=1.47; P=.12). Independent of subthreshold affective symptoms, only joint pain and increasing number of pain locations were still significantly associated with depression and anxiety onset. Clinicians should be aware that regardless of affective symptoms, pain, particularly at multiple locations, is a risk indicator for developing depressive and anxiety disorders.

Pain Characteristics of People with Chronic Fatigue Syndrome

ABSTRACTObjectives: Until now, there has been a lack of fundamental research into the pain experienced in chronic fatigue syndrome [CFS]. The aims of this study were to (1) investigate the pain experiences of people with CFS with a range of disability, and (2) identify specific pain characteristics of people with CFS.Methods: Fifty people were recruited, including 10 people who were severely disabled by CFS [25% Group]. Participants completed a structured interview and a series of pain assessments about their current pain, which included the McGill Pain Questionnaire [MPQ], the Pain Anxiety Symptoms Scale [PASS], and visual analog scales.Results: Muscle pain was the most reported painful symptom [68 percent]. The current pain intensity was 43.2 mm ± 20.8 mm measured on a visual analog scale. The MPQ pain rating index was 23.6 ± 10.8. The PASS total score was 37.9 ± 17.6. Thirty percent [N = 15] of participants reported the cervical spine the location of “most severe” pain, followed by the left and right s...

Exacerbation of Chronic Pain following Spinal Cord Injury

Because of the high prevalence and the refractory nature of pain following spinal cord injury (SCI), it is important to increase the understanding of what factors aggravate different types of pain. This information is related to pain generating mechanisms and may thus be useful in the diagnosis and management of these difficult pain conditions. The aims of the present study were to (1) identify variables (factors) that exacerbate chronic pain associated with SCI and (2) define the relationships among these patterns of pain exacerbation, specific pain characteristics, and psychological features. A sample out of 159 (75.5%) people with SCI and chronic pain, volunteered to participate in a mail survey. Over 50% of the sample indicated that prolonged sitting, infections, fatigue, muscle spasms, cold weather, and sudden movements exacerbated their pain. A principal components analysis detected five sets of factors that were reported to magnify pain: negative mood, prolonged afferent activity (bowel, bladder, somatic), weather, voluntary physical activity, and transient somatic afferent activity. Negative mood and prolonged afferent activity were frequently and significantly associated with both pain characteristics and psychosocial issues. A multiple regression analysis revealed that a combination of decreased activity levels due to pain (t = 3.54; p < 0.001), pain located in the frontal aspects of torso (including genitals) (t = 2.29; p < 0.05), "burning" (t = 2.26; p < 0.05), or "electric" (t = 2.09; p < 0.05) pain, and a limited perception of life control (t = -2.16; p < 0.05) was significantly associated with a high extent of pain aggravation (R2 = 0.39; p < 0.000).

Suggests More Tests for Chest Pain Diagnosis

Driscoll et al. (Pediatrics 57:648, May 1976) reported a series of 43 patients with chest pain evaluated by history and physical examination, psychiatric interview, screening laboratory studies, ECG, and chest x-ray film. No organic cause was identified in 45% of patients, and various psychiatric aspects of the pain were discussed. The history obtained from pediatric patients is often suboptimal, and specific pain characteristics and associations cannot be defined. We therefore propose that more vigorous diagnostic work-ups are necessary before chest pain can be classed as "idiopathic."