Active clinical trials for "Acute Pain"

Persistent pain after breast cancer surgery (PPBCS) is a significant clinical problem, affecting between 25 and 50% of patients. Several factors are associated with the development of PPBCS, including acute postoperative pain. The analysis of pain trajectories through mixed model modeling is an alternative to static pain measures, improving precision and providing information on the time course of pain resolution. Our aim was to investigate if the characteristics of pain trajectories during the first postoperative week are correlated with the persistence of pain 3 months after breast cancer surgery.

The purpose of this study is to test the hypothesis that a preoperative test of pain modulation predicts persistent pain 4 months after breast cancer surgery. In addition, a risk score for the prediction of persistent pain will be developed from parameters available before surgery.

Despite advancement in perioperative pain management, more than half of the patients still report moderate-severe pain after surgery. Among several risk factors, pre-existing pain has consistently been shown to predict postoperative severe pain.If one can predict the patients who will experience more post-operative pain, then a more aggressive pain management strategy can be adopted perioperatively. This would improve patient satisfaction and prevent poor outcomes such as chronic pain after surgery. Therefore, our primary aim is to find out whether presence of pre-existing preoperative pain would predict moderate-severe acute pain after laparoscopic cholecystectomy. Moreover, we plan to use Patient Reported Outcomes Measurement Information System (PROMIS) scale to assess preoperative pain intensity and pain-related behaviors. Primary &Secondary Objectives: Primary objectives To investigate the association between preexisting preoperative pain (more than 3 months duration) and postoperative moderate-severe acute pain after laparoscopic cholecystectomy. Secondary objectives .1. To investigate the association between preoperative PROMIS(patient reported outcome measurement and information system) domain (PROMIS pain intensity score, PROMIS pain interference score, PROMIS pain behavioural score) and postoperative moderate-severe acute pain after LC. 2. To examine baseline demographic, clinical, psycho-behavioural features and intraoperative factors in relation to dynamic moderate to severe pain after LC. 3. To identify perioperative predictors for acute postsurgical pain. 4. To find out the incidence of shoulder tip pain after LC.

Patient reported pain, stress, and anxiety measures have been found to be inter-related, but it is not known if they are all associated with receiving opiate medications. The objective of this study is to determine if patients' degree of reported pain, stress, or anxiety is associated with receiving opiate pain medications in the emergency department or at discharge. Alert patients at least 18 years of age and who report pain greater than 3/10 are eligible to participate in the study. Consenting patients complete Visual Analog Scales describing their perceived pain, stress, and anxiety from enrollment until discharge. Demographic data and administration of pain medication is also recorded. Visual Analog Scale scores among patients who received an opioid pain medicine in the emergency department and at discharge will be compared to those who did not.

Pain in the emergency room is under documented and pain relief suboptimal. Data on nurse driven analgesia in emergency department waiting rooms is lacking. The primary objective of this study is to determine the proportion of patients in pain receiving pain therapy administered by the triage nurse (prevalence study). The secondary objectives are to 1) describe nursing practices in analgesia and adherence to the dedicated protocol; 2) to determine the factors associated with the non administration of painkillers and for these factors, to estimate the strength of the association

Between 40 to 70% of patients with critical illness experience moderate to severe pain. Diagnosing pain and assessing its severity is difficult in non-verbal patients both in an Intensive Care Unit and in Postoperative Unit after a major surgery such as cardiac surgery). In patients who are unable to self-report pain, we use behavioural pain scales, namely BPS - Behavioural Pain Scale. Aim: The aim of this study was to validate the Polish version of a behavioural pain assessment method - BPS in intubated, sedated patients after cardiac surgery versus self assessment of pain using Numeric rating scale (NRS) in both delirious and non-delirious patients (assessed using Confusion Assessment Method for ICU, CAM-ICU). Method: A prospective observational cohort study will include 60 patients. The patients will be observed by two trained observers during a nociceptive procedure (position change), both during analgosedation and analgesia. Patients will be observed 5 minutes before, during, and 15 min after the two sets of interventions (six assessments in total). Each BPS assessment will be carried out by two observers blinded to each other. To validate the Polish BPS translation we will use the following methods: calculations of interrater reliability, criterion validity and discriminant validity.

All patients admitted in Geneva University Hospitals (GUH) emergency department (ED) are triaged using the Swiss Emergency Triage Scale (SETS), a 4-level symptom-based triage scale. At the end of the triage process the triage nurse has to choose an emergency level and a main presenting complaint among a listing of 98 presenting complaints. The SETS recommends a pain evaluation for 44 out of the SETS 98 presenting complaint. The primary objective of the study is to determine whether pain is correctly evaluated when required by the SETS criteria. The secondary objectives are (1) to evaluate whether an appropriate treatment is delivered when pain is present, and (2) to identify predictors of pain evaluation and treatment.

The present study is a multicenter, explorative, qualitative study. The primary endpoint of this study is to evaluate to which extent the collection of data with regard to pain caused by illness or treatment can be optimized using health technology solutions. For this evaluation semi-structured qualitative interviews with 8-10 patients will be conducted. Secondary variables are the evaluation of the patients' pain experience and the general patients' willingness to collect data with regard to pain by using technological devices themselves or with support of healthcare professionals.

ultrasound guided bilateral erector spinae plane block will be used as adjuvant to general anaesthesia in cardiac surgery

Managing pain, which affects 20-50% of the population, is a major issue in daily clinical practice. Evaluation of pain intensity is essential to adapt treatment but as it mainly relies on self-report, this assessment is difficult or impossible in non-communicating patients. In these cases, pain can only be evaluated by medical staff by the observation of pain-related characteristics like facial expression of pain (FEP). However, recognition of FEP is subjective, time-consuming and subject to multiple biases frequently leading to underestimation of pain and consequently under-treatment. Some of these biases could be solved by the use of facial recognition technology, allowing objective, automated and time-saving pain assessment. DEF-I aims to address technical issues and achieve the development of facial expression recognition digital tool able to evaluate severe acute pain in clinical practice, with high validity and utility by improving the quality of the images to be analyzed, by studying larger samples of patients, data and images, in order to correlate more efficiently the pain intensity felt by a patient with the expression of his face. The main objective of this study is to verify whether it is possible to quantitatively correlate the intensity of acute postoperative pain felt by a patient with his facial expression. The secondary objective is to define a reliable computer algorithm that qualitatively correlates the type of acute postoperative pain experienced by a patient with his facial expression.