Objective:To construct advance care planning (ACP) interventions for end-stage cancer patients based on Watson care theory, so as to provide basis for ACP practice in end-stage cancer patients.Methods:Semi-structured interviews were conducted to establish items pool for "ACP interventions based on Watson care theory for end-stage cancer patients ". Delphi expert inquiry method was used to evaluate, revise and supplement the items, and the final version of "ACP interventions for end-stage cancer patients" was formed. The positive coefficient and authority coefficient of experts were calculated, and Kendall harmony coefficient and variation coefficient were used to evaluate the degree of expert consensus.Results:The "ACP interventions for end-stage cancer patients" was constructed with 19 items in 4 dimensions, including 7 items in the preparation phase, 6 items in the initiation phase, 4 items in the execution phase and 2 items in the follow-up phase. The effective recovery rates of the 2 rounds of questionnaire were both 100%. The authority coefficient of expert consultation was 0.835. The coefficient of variation of each item was 0 to 0.21. The Kendall harmony coefficients of the two rounds of consultation were 0.290 and 0.267, respectively.Conclusions:The ACP interventions for end-stage tumor patients constructed in this study has good authority and coordination, and reflects Watson care theory, which has certain reference significance for clinical ACP implementation.

Objective:To analyze the risk factors for hospital acquired pulmonary infections in elderly lung cancer patients during chemotherapy, and construct a prediction model to provide personalized guidance for clinical nursing work.Methods:Using convenience sampling, clinical case data of 405 elderly lung cancer patients who underwent chemotherapy at the First Affiliated Hospital of Zhengzhou University from January 2021 to December 2022 were collected. A total of 226 patients from January to December 2021 were selected as the modeling group, and 179 patients from January to December 2022 were selected as the validation group. In the modeling group, the patients were divided into two groups based on whether or not they had hospital acquired pulmonary infection, including the hospital acquired pulmonary infection group and the non-hospital acquired pulmonary infection group. Single factor analysis and multivariate Logistic regression analysis were used to determine the risk factors for hospital acquired pulmonary infection in elderly lung cancer patients during chemotherapy. A risk prediction model for hospital acquired pulmonary infection in elderly lung cancer patients during chemotherapy was constructed based on the results of multivariate analysis. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of the prediction model, and a calibration map was drawn for consistency testing. The prediction model was validated in the validation group to evaluate its predictive performance.Results:The incidence of hospital acquired pulmonary infection in the modeling group was 14.6% (33/226). The results of multivariate Logistic regression analysis showed that basic diseases, tumor-node-metastasis (TNM) staging, neutropenia, and invasive procedures were risk factors for hospital acquired pulmonary infections in elderly lung cancer patients undergoing chemotherapy ( P<0.05). Based on this result, a prediction model was constructed, with an area under the ROC curve of 0.832 [95% CI (0.764, 0.900) ] in the modeling group and 0.759 [95% CI (0.695, 0.824) ] in the validation group. The calibration curves of the modeling and validation groups showed a good coincidence between the predicted results and the actual results. Conclusions:Basic diseases, neutropenia, invasive procedures, and advanced stages of tumors are risk factors for hospital acquired pulmonary infections in elderly lung cancer patients undergoing chemotherapy. For high-risk patients, individualized intervention should be carried out as soon as possible to reduce the incidence of hospital acquired pulmonary infection.

Objective:To understand the attitudes of end-stage cancer patients to the adjunctive intervention program of the advance care planning, and analyze the influencing factors of their attitudes and choices.Methods:The purpose sampling was used to select 11 end-stage cancer patients hospitalized from January to December 2019. Face-to-face semi-structured in-depth interviews was conducted with the phenomenological research method in qualitative research. The Colaizzi 7-step method was used to organize, analyze data and refine themes.Results:A total of three themes were extracted, namely the attitude towards the advance care planning: mainly support or affirmation, not rejection; the acceptance of adjunctive intervention program: preference for basic supportive treatment, avoiding suffering and increasing family burdens due to invasive rescue; factors that affected patients' attitudes and choices of adjunctive intervention program: personal wishes, family members' attitudes, and information about disease and treatment methods.Conclusions:Patients with end-stage cancer do not reject advance care planning, and prefer basic supportive treatment based on the selection of adjunctive intervention programs, so as to avoid suffering and increasing family burdens due to invasive rescue. In the process of promotion and practice, the patient's personal wishes are important, but the key role of family members in medical decision-making cannot be ignored.

Objective:To explore the effect of case management cloud service based on smart hospital in patients with lung cancer undergoing chemotherapy.Methods:From March 2019 to June 2020, a total of 148 patients with lung cancer who received regular chemotherapy in the First Affiliated Hospital of Zhengzhou University were selected by convenience sampling method, and randomly divided into the control group and the observation group with 74 cases in each group. The control group received routine case management, and the observation group received case management cloud service based on smart hospital. Quality of life, treatment compliance and mortality were compared between the two groups.Results:Of the 148 patients, 17 cases died and did not complete the whole course of chemotherapy, including 4 cases in the observation group and 13 cases in the control group. The survival rates of the observation group and the control group during chemotherapy were 94.6% and 82.4%, respectively. There were statistically significant differences in physiological status, social and/or family status, function and total scores of quality of life of the control group before and after chemotherapy ( P<0.05) . There were statistically significant differences in physiological status, function and total score of quality of life of the observation group before and after chemotherapy ( P<0.05) . After chemotherapy, physiological status, emotional status, functional status, total score of quality of life and treatment compliance of the observation group were higher than those of the control group, and the differences were statistically significant ( P<0.05) . Conclusions:Compared with conventional case management, case management cloud service based on smart hospital has more advantages in maintaining quality of life, improving treatment compliance and survival prognosis of patients with lung cancer undergoing chemotherapy.