Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
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Support Care Cancer · Jan 2010
Comparative StudyEvaluation and comparison of two prognostic scores and the physicians' estimate of survival in terminally ill patients.
Most terminally ill patients request information about their remaining life span. Professionals are not generally willing to provide prognosis on survival, even though they are expected to be able to do so from their clinical experience. This study aims to find out whether the standardized instruments Palliative Prognostic Index (PPI) and the Palliative Prognostic Score (PaP-S) are appropriate, specific, and sensitive to estimate survival time in patients receiving inpatient palliative care in Germany. ⋯ The prognostic scores are not able to produce a precise reliable prognosis for the individual patient. Nevertheless, they can be used for ethical decision making and team discussions. Estimating survival time from clinical experience seems to be easier for very bad or very good prognosis for physicians.
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Support Care Cancer · Jan 2010
Continuous non-invasive monitoring of the skin temperature of HSCT recipients.
Empirical antibiotic therapy usually started in patients who are neutropenic following treatment with cytostatic chemotherapy for a haematological malignancy as soon as fever develops to forestall fulminant sepsis. Hence, accurate and timely detection of fever is crucial to the successful management of infectious complications in these patients. We report an investigation of the feasibility and validity of continuous non-invasive body temperature measurement. ⋯ Continuous skin temperature measurements are feasible and valid compared to the conventional temperature measurement and may improve the management of infections by earlier detection of fever in neutropenic patients.
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Assessment of current practice with a valid set of indicators is the key to successfully improving the quality of patient-centred care. For improvement purposes, we developed indicators of patient-centred cancer care and tested them on a population of patients with non-small cell lung cancer (NSCLC). ⋯ Developing a valid set of patient-centred indicators is a first step towards improving the patient centredness of cancer care. Indicators can be based on recommendations from guidelines, but adding patient opinions leads to a more complete picture of patient centredness. The practice test on patients with NSCLC showed that the patient centredness of cancer care can be improved. Our set of indicators may also be useful for future quality assessments for other patients with cancers or chronic diseases.
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The survival of cancer patients who undergo cardiopulmonary resuscitation (CPR) after in-hospital cardiac arrest is poor. The survival of cancer patients who undergo CPR after out-of-hospital cardiac arrest is unknown. We sought to determine survival rates in such patients and to identify phrases in patient charts that might have prompted end-of-life discussions. ⋯ Survival of cancer patients who underwent CPR after out-of-hospital cardiac arrest was poor. Medical providers should consider discussing end-of-life issues, including out-of-hospital do-not-resuscitate orders, in the outpatient clinic setting with cancer patients nearing the end of life.
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Support Care Cancer · Jan 2010
Predictors of inpatient mortality in an acute palliative care unit at a comprehensive cancer center.
Predicting inpatient mortality has clinical and financial implications and helps improve the care of patients with advanced cancer and their families. Models with excellent validity and reliability are available for mortality prediction in intensive care units. The purpose of the current study was to determine factors associated with increased likelihood of mortality in an acute palliative care unit (APCU). ⋯ We observed a significant association of certain factors with increased likelihood of APCU death in patients with advanced cancer. These findings need to be validated in a larger prospective study to develop a model for predicting APCU mortality for patients with advanced cancer.