Attachment to Caregivers and Type 1 Diabetes in Children

Attachment is a behavioral and physiological system, which enables individual’s dynamic adaptation to its environment. Attachment develops in close interaction between an infant and his/her mother, plays an important role in the development of the infant’s brain, and influences the quality of interpersonal relationships throughout life.Security of attachment is believed to influence individual response to stress, exposing insecurely organized individuals to deregulated autonomic nervous system and exaggerated hypothalamic-pituitary-adrenal activity, which, in turn, produces increased and prolonged exposure to stress-hormones. Such stress responses may have considerable implications for the development of diverse health-risk conditions, such as insulin resistance and hyperlipidemia, shown by numerous studies.Although the mechanisms are not yet fully understood, there is compelling evidence highlighting the role of psychological stress in the development of type 1 diabetes (T1D). One of the possible contributing factors for the development of T1D may be the influence of attachment security on individual stress reactivity. Thus, the suggestion is that insecurely attached individuals are more prone to experience increased and prolonged influence of stress hormones and other mechanisms causing pancreatic beta-cell destruction.The present paper opens with a short overview of the field of attachment in children, the principal attachment classifications and their historic development, describes the influence of attachment security on individual stress-reactivity and the role of the latter in the development of T1D. Following is a review of recent literature on the attachment in patients with T1D with a conclusion of a proposed role of attachment organization in the etiology of T1D.     

Secondary haemophagocytic lymphohistiocytosis: Experience from the Uppsala University Hospital

Background. Haemophagocytic lymphohistiocytosis (HLH) is a rare clinical syndrome characterized by fever, hepatosplenomegaly, cytopenia, and progressive multiple-organ failure. HLH in adults is often secondary to autoimmune diseases, cancer, or infections in contrast to familial HLH. Treatment of secondary HLH is directed against the triggering disease in addition to immunosuppressive therapy, the latter commonly according to the HLH-2004 protocol.Methods. We conducted a retrospective study to identify triggering diseases, disease-specific and immunosuppressive therapy administered, and prognosis in adult patients with secondary HLH. Patient data were collected from October 2010 to January 2015.Results. Ten adult patients with secondary HLH were identified. Seven were men, and the median age at diagnosis was 62 years. Five cases were triggered by malignant disease and five by infection. The median patient fulfilled five of the eight HLH-2004 diagnostic criteria. All patients fulfilled the criteria fever, cytopenia, and ferritin >500 µg/L. Median time from hospital admission to HLH diagnosis was 20 days. Four patients received immunosuppressive therapy according to the HLH-2004 protocol. The prognosis was dismal, especially for the patients with malignancy-associated HLH, of whom all died.Conclusion. HLH should be suspected in patients who present with fever, cytopenia, and ferritin >500 µg/L. Secondary HLH has a dismal prognosis. None of the patients with HLH triggered by malignancy survived. Achieving remission of the triggering disease seems to be important for a favourable outcome as, in all surviving patients, the haemophagocytic syndrome resolved after remission of the underlying infection.     

慢性心力衰竭护理结局分类评价表的构建研究

目的本研究以护理结局分类(NOC)为基础,筛选符合慢性心力衰竭患者的相关护理结局,由此构建具有专科专病特点的慢性心力衰竭患者护理结局评价表。方法成立研究核心小组,应用文献回顾法、专家函询法确定护理结局分类指标,并进行统计学分析,最终建立慢性心力衰竭护理结局分类评价表。结果通过研究,确定慢性心力衰竭护理结局中包含4个领域、8个一级指标、68个二级指标。4个领域分别是生理健康、功能健康、健康知识和行为、心理社会健康。一级指标中包含心脏泵血功能、活动耐力、社会支持、抑郁水平等。二级指标中包含心脏指数、血压、呼吸困难、情绪波动大、步行距离、步行速度等68个指标。统计学分析中:第一、二轮函询专家的积极系数分别为90%、100%,专家权威系数为0.895,专家意见协调程度(P<0.05)。结论本研究成功建立慢性心力衰竭护理结局分类评价表,有助于临床护士用于评价护理措施的有效性,也使其成为一种标准化语言,便于应用到护理电子信息系统中进行绩效测算等。但是本研究不足之处是未能将该研究进行临床实证,未能进一步确认其有效性。     

Prevalence and Predictors of Quality of Recovery at Home After Day Surgery

Traditionally, major complications and unanticipated admission/readmission rates were used to assess outcome after day surgery. However, in view of the relative absence of major complications the quality of recovery (QOR) should be considered one of the principal endpoints after day surgery. In our study, the level of QOR is defined by a combination of the Global Surgical Recovery (GSR) Index and the Quality of Life (QOL).The aim of this study was to analyze prevalence and predictors of QOR after day surgery on the fourth postoperative day.Elective patients scheduled for day surgery from November 2008 to April 2010 were enrolled in a prospective cohort study. Outcome parameters were measured by using questionnaire packages at 2 time points: 1 week preoperatively and 4 days postoperatively. Primary outcome parameter is the QOR and is defined as good if the GSR index >80% as well as the postoperative QOL is unchanged or improved as compared with baseline. QOR is defined as poor if both the GSR index ≤80% and if the postoperative QOL is decreased as compared with baseline. QOR is defined as intermediate in all other cases. Three logistic regression analyses were performed to determine predictors for poor QOR after day surgery.A total of 1118 patients were included. A good QOR was noted in 17.3% of patients, an intermediate QOR in 34.8%, and a poor QOR in 47.8% 4 days after day surgery. The best predictor for poor QOR after day surgery was type of surgery. Other predictors were younger age, work status, and longer duration of surgery. A history of previous surgery, expected pain (by the patient) and high long-term surgical fear were significant predictors of poor QOR in only 1 of 3 prediction models.The QOR at home 4 days after day surgery was poor in the majority of patients and showed a significant procedure-specific variation. Patients at risk for poor QOR can be identified during the preoperative period based on type of surgery, age, work status, and the duration of the surgery.