Patient reporting pain intensity immediately after surgery can be associated with underlying depression in women with breast cancer.

OBJECTIVE: The aims of this study were to determine the prevalence of severe, definite depression symptoms, as measured using the Center for Epidemiological Studies Depression Scale (CES-D), and the association between high CES-D scores (i.e., ≥25) and sociodemographic and perioperative factors during perioperative period. METHODS: Among 1690 consecutive breast cancer patients who were admitted for definitive breast surgery during the study period, 1499 patients were included in this study. Patients with a past medical history of psychiatric medication or support, a plan for elective surgery due to locoregional recurrence, or any metastatic disease were excluded. The CES-D score was checked 1 day before definitive surgeries. The sociodemographic data and perioperative data were analyzed. RESULTS: The mean CES-D score was 18.5, with 24.1% (362/1499) and 56.7% (850/1499) having high CES-D scores of ≥25 and ≥16, respectively. Multivariate analysis revealed that the number of family members with any malignancy (≥2 vs. 0), sedative medication (yes vs. no), and postoperative numeric rating scale scores (persistent, severe pain vs. stably mild pain) were significantly associated factors for severe, definite depression symptoms [CES-D score of ≥25: adjusted odds ratio (OR) = 1.56, 95% confidence interval (CI) = 1.10-2.21, p = 0.013; adjusted OR = 1.65, 95% CI = 1.00-2.71, p = 0.048; and adjusted OR = 2.14, 95% CI = 1.15-3.95, p = 0.016, respectively]. CONCLUSION: Depression may increase the intensity of postoperative acute pain. Self-reporting of persistent postoperative pain intensity is potentially useful in detecting hidden depression symptoms in breast cancer patients during the perioperative period.

Availability of patient classification using clinical data.

OBJECTIVES: The aim of this study is examine the reliability and validity of the patient classification which is based on clinical data with comparing to nurse's check. METHOD: Nurse Experts estimated the content validity of extracting KPCS-1(Korea patient classification system for nurses Version 1) activities score from clinical data in storage of AMIS (Asan Medical Center information system). After verifying the content validity of extraction method from clinical data, two methods extracting KPCS-1 score (from clinical data vs. nurses' recording) were compared for 348 patients. RESULTS: This study demonstrated that extracting patient classification from clinical data is high value of validity (except 4 items excluded from this study), reliability between two methods extracting KPCS-1(from clinical data and nurses' recording) is high value (ICC=0.96, p<.001) and construct validity of two methods has similarity. CONCLUSIONS: It is believed that the patient classification system which is made from only clinical data without nurse's work burden is available. And 4 items which was excluded on KPCS-1 and examine area which had low level of reliability are needed to be amended.