Pancreas · 2023
Daily Pain Experiences in Chronic Pancreatitis: Identifying Pain Phenotypes.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Han Samuel, Li Rui, Palermo Tonya M
Аннотация
OBJECTIVES: Pain, the hallmark symptom of chronic pancreatitis (CP), remains difficult to assess. To capture the variability of pain that patients can experience day to day, this study used pain diaries to describe daily pain experiences and identify pain phenotypes.
METHODS: This study is a secondary data analysis from a pilot trial examining cognitive behavioral therapy for pain treatment in CP. Before treatment, patients completed an online daily pain diary using the Brief Pain Inventory for 7 days. Using indicators of pain magnitude, pain variability, pain synchrony along with least, worst, and average pain intensity levels, we identified pain patterns using K-means clustering.
RESULTS: Of 30 patients in the pilot trial, a total of 27 patients (mean age of 49.8 years, 80% women) had complete data to include in this report. Four clusters were identified: cluster 1, lowest pain magnitude (n = 3); cluster 2, moderate pain magnitude and high pain variability (n = 4); cluster 3, moderate pain magnitude and low pain variability (n = 9); and cluster 4, highest pain magnitude and lowest pain variability (n = 11).
CONCLUSIONS: Daily pain diaries offer a novel way of evaluating the dynamic pain experiences in CP. Although 4 distinct pain patterns were identified, further studies are needed to validate these findings.
METHODS: This study is a secondary data analysis from a pilot trial examining cognitive behavioral therapy for pain treatment in CP. Before treatment, patients completed an online daily pain diary using the Brief Pain Inventory for 7 days. Using indicators of pain magnitude, pain variability, pain synchrony along with least, worst, and average pain intensity levels, we identified pain patterns using K-means clustering.
RESULTS: Of 30 patients in the pilot trial, a total of 27 patients (mean age of 49.8 years, 80% women) had complete data to include in this report. Four clusters were identified: cluster 1, lowest pain magnitude (n = 3); cluster 2, moderate pain magnitude and high pain variability (n = 4); cluster 3, moderate pain magnitude and low pain variability (n = 9); and cluster 4, highest pain magnitude and lowest pain variability (n = 11).
CONCLUSIONS: Daily pain diaries offer a novel way of evaluating the dynamic pain experiences in CP. Although 4 distinct pain patterns were identified, further studies are needed to validate these findings.