Plos One
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Outcome measurement is fundamental to assess needs and priority of care in palliative care settings. The Integrated Palliative care Outcome Scale (IPOS) was developed from earlier versions of this tool. Its use is encouraged to ameliorate the assessment of individual outcomes in palliative care settings. This study aimed to translate and culturally adapt IPOS into Italian, and explore its face and content validity. ⋯ The Italian IPOS, in its four versions directed to patients or staff and with a recall period of 3 or 7 days, has face and content validity for use in clinical settings and is ready for further psychometric and clinimetric validation.
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Previous studies have reported an association between family relationships and suicidal behavior, and found that people with high suicidal ideation are not likely to consult with others about their distress. An effective consulting service is therefore necessary for such individuals. Crisis hotlines are effective for reducing suicide risk, but their associated suicide ideation rate and odds ratio of family problems children remain unclear. ⋯ This result suggested that callers with family problems have a significantly lower rate and odds ratio for suicidal ideation compared with others. However, some associations with a high suicide ideation rate were found for individual items among callers with family problems such as abuse (20.4%), family breakdown (16.1%), and domestic violence (10.6%). Further studies are needed to understand the suicidal ideation of callers with family problems and develop more effective preventive strategies.
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Observational Study
Evaluation of antibiotic dispensing practice in community pharmacies in Jordan: A cross sectional study.
It is well known that the emergence of antibiotic resistance is linked to the misuse and overuse of antibiotics. Misuse includes self-medication and the inappropriate use of antibiotics because of improper dosage or improper duration than recommended. This study investigated three patterns of dispensing antibiotics in a sample of community pharmacies in Jordan. ⋯ In conclusion, a significant proportion of antibiotics are dispensed without prescription in Jordan. Moreover, a considerable proportion of prescribed antibiotics were inappropriate for the conditions concerned. This indicates the importance of enforcing the Jordanian regulations prohibiting the dispensing of nonprescription antibiotics and the implementation of continuous education to physicians and pharmacists to increase awareness about the emergence of antibiotic resistance.
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Detection of pulmonary nodules is an important aspect of an automatic detection system. Incomputer-aided diagnosis (CAD) systems, the ability to detect pulmonary nodules is highly important, which plays an important role in the diagnosis and early treatment of lung cancer. Currently, the detection of pulmonary nodules depends mainly on doctor experience, which varies. This paper aims to address the challenge of pulmonary nodule detection more effectively. ⋯ Our team trained A-CNN using the LUNA16 and Ali Tianchi datasets and evaluated its performance using the LUNA16 dataset. We discarded nodules less than 5mm in diameter. When the average number of false positives per scan was 0.125 and 0.25, the sensitivity of A-CNN reached as high as 81.7% and 85.1%, respectively.
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Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of information relating to disease presentation, imaging features, and patient characteristics to determine if a patient will benefit from surgery for DCM. We applied a supervised machine learning approach to develop a classification model to predict individual patient outcome after surgery for DCM. ⋯ Worse pre-operative disease severity, longer duration of DCM symptoms, older age, higher body weight, and current smoking status were associated with worse surgical outcomes. We developed a model that predicted positive surgical outcome for DCM with good accuracy at the individual patient level on an independent testing cohort. Our analysis demonstrates the applicability of machine-learning to predictive modeling in spine surgery.