RESUMEN
Identifying major depression in children and adolescents is more challenging than in adults. Questionnaires are often used for screening or guiding clinical assessment. Several instruments of different lengths are used as equivalent measures in diagnostic decisions. In this paper, we explore to what extent 18 commonly used depression scales for children and adolescents explore depression clinical symptoms as established by standard DSM-5 diagnosis criteria. We analyzed scale content adequacy by examining the overlap between scale contents and consensus clinical symptoms, the diagnostic time frame for active symptom assessment, and readability for the target age group. The 18 scales encompassed 52 distinct symptoms. These scales included just 50% of clinical symptoms required for diagnosis. The content overlap was low; on average, 29% of symptoms coincide across scales. Half of the scales did not use the standard period for active symptom appraisal, and some did not include a period for assessment. The reading levels on six scales were inappropriate for the scale's target population age group. The substantial heterogeneity in defining the depressive syndrome, the low overlap among scales, different periods of a positive diagnosis, and mismatch of reading competence for detecting may lead to heterogeneity in clinical diagnoses when using different scales. Improving the content of self-report in terms of homogeneity of diagnostic criteria would lead to better diagnostic decisions and patient management.
RESUMEN
AIMS: To identify the risk factors for lymphoedema following axillary lymph node dissection (ALND) in a European sample and to propose a lymphoedema prediction model for this population. DESIGN: Predictive retrospective cohort study comparing women who developed lymphoedema in 2 years of undergoing ALND with those who did not developed lymphoedema. METHODS: We reviewed the clinical records of 504 women who, between January 2008 and May 2018, underwent surgery for breast cancer that involved ALND. Logistic regression was used to identify significant risk factors for lymphoedema. The prediction accuracy of the model was assessed by calculating the area under the receiver operating characteristic curve. RESULTS: Of the 504 women whose records were analysed, 156 developed lymphoedema. Significant predictors identified in the regression model were level of lymph node dissection, lymph node status, post-operative complications, body mass index (BMI) and number of lymph nodes extracted. The prediction model showed good sensitivity (80%) in the study population. CONCLUSIONS: The factor contributing most to the risk of lymphoedema was the level of lymph node dissection, and the only patient-related factor in the prediction model was BMI. The model offers good predictive capacity in this population and it is a simple tool that breast care units could use to assess the risk of lymphoedema following ALND. Nurses with specialist knowledge of lymphoedema have a key role to play in ensuring that women receive holistic and individualized care. IMPACT: What problem did the study address? Secondary lymphoedema is one of the main complications in the treatment of breast cancer. What were the main findings? The prediction model included five factors associated with the risk of lymphoedema following ALND. The strongest predictor was the level of lymph node dissection, and the only patient-related factor was BMI. Where and on whom will the research have an impact? The prediction model offers breast care units a tool for assessing the risk of lymphoedema in women undergoing surgery involving ALND. The results highlight the importance of weight reduction as a preventive measure and support a more conservative surgical approach.
