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Nursing effect of narrative nursing intervention on postoperative patients with severe lung cancer 被引量:1
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作者 Bin Wen Ying Liu +1 位作者 Xiao-Xia Min An-Qi Wang 《World Journal of Clinical Cases》 SCIE 2024年第1期76-85,共10页
BACKGROUND Lung cancer is a common disease with high mortality,and psychological support is very important in the diagnosis and treatment of postoperative patients with cancer pain.AIM To explore the application effec... BACKGROUND Lung cancer is a common disease with high mortality,and psychological support is very important in the diagnosis and treatment of postoperative patients with cancer pain.AIM To explore the application effect of the narrative nursing method in postoperative lung cancer patients in the intensive care unit.METHODS A total of 120 patients diagnosed with lung cancer and experiencing cancer-related pain were randomly allocated into two groups:an observation group and a control group,each consisting of 60 cases.The control group was given routine analgesic and psychological care,while the research group applied the five-step narrative nursing method based on routine care,comparing the visual analogue scale scores,sleep status,anxiety and depression status,and quality of life of the two groups of patients before and after the intervention.RESULTS The pain scores,anxiety scores,and depression scores of the study group were lower than those of the control group after the intervention using the narrative nursing method,and the difference was statistically significant(P<0.05).CONCLUSION Using narrative nursing methods to intervene in patients with lung cancer combined with cancerous pain can help patients to correctly recognize their disease,adjust their mentality,establish confidence,alleviate patients'subjective pain feelings,and improve their adverse emotions. 展开更多
关键词 Narrative care Lung cancer Care unit PAIN Quality of life
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Clinical characteristics and prognosis of non-small cell lung cancer patients with liver metastasis:A population-based study 被引量:1
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作者 Jun-Feng Wang Hong-Di Lu +3 位作者 Ying Wang Rui Zhang Xiang Li Sheng Wang 《World Journal of Clinical Cases》 SCIE 2022年第30期10882-10895,共14页
BACKGROUND The presence of liver metastasis(LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer(NSCLC) patients.The median overall survival of patients with involvement of the li... BACKGROUND The presence of liver metastasis(LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer(NSCLC) patients.The median overall survival of patients with involvement of the liver is less than 5 mo.At present,identifying prognostic factors and constructing survival prediction nomogram for NSCLC patients with LM(NSCLC-LM) are highly desirable.AIM To build a forecasting model to predict the survival time of NSCLC-LM patients.METHODS Data on NSCLC-LM patients were collected from the Surveillance,Epidemiology,and End Results database between 2010 and 2018.Joinpoint analysis was used to estimate the incidence trend of NSCLC-LM.Kaplan-Meier curves were constructed to assess survival time.Cox regression was applied to select the independent prognostic predictors of cancer-specific survival(CSS).A nomogram was established and its prognostic performance was evaluated.RESULTS The age-adjusted incidence of NSCLC-LM increased from 22.7 per 1000000 in 2010to 25.2 in 2013,and then declined to 22.1 in 2018.According to the multivariable Cox regression analysis of the training set,age,marital status,sex,race,histological type,T stage,metastatic pattern,and whether the patient received chemotherapy or not were identified as independent prognostic factors for CSS(P < 0.05) and were further used to construct a nomogram.The C-indices of the training and validation sets were 0.726 and 0.722,respectively.The results of decision curve analyses(DCAs) and calibration curves showed that the nomogram was well-discriminated and had great clinical utility.CONCLUSION We designed a nomogram model and further constructed a novel risk classification system based on easily accessible clinical factors which demonstrated excellent performance to predict the individual CSS of NSCLC-LM patients. 展开更多
关键词 Non-small cell lung cancer Liver metastasis NOMOGRAM Risk classification system
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