Objective Peritoneal dialysis can be done at home , however , its clinical follow-up quality is lower compared with hemodialysis due to the lack of detailed follow-up system and professional management team for post-discharge nursing care .The article aimed to explore the effect of a nurse-led integrated specialized disease management model in the follow-up of peritoneal dialysis patients . Methods Nurse-led integrated specialized disease management model was provided for 270 patients with peritoneal dialysis (PD) from January 2012 to May 2013.Self-designed questionnaire on diasease knowledge and self-care assement questionnaire were used for patients to evaluate their self-care ability and understanding of disease knowledge .Regular follow-up continued . Results The patients′understanding of disease knowledge was on the rise at 1st day before discharge, 1st month and 3rd months after discharge. After the application of nurse-led integrated specialized disease management model , the patients′regular clinical follow-up rate was in-creased from 78.3% to 88.6%.The patients′self-care ability improved gradually at 1st day before discharge , 1st month and 3rd months after discharge , which was of significant differences . Conclusion The nurse-led nurse-led integrated specialized disease management model can improve peritoneal dialysis patients′self-care ability and reduce their medical expense , which is of clinical sig-nificance .

Objective To investigate the current situation of disability acceptance and alexithymia among uremia patients,and to explore the effects of alexithymia on disability acceptance.Methods Totally 342 uremia patients were recruited by convenience sampling method.Patients were investigated with general information questionnaire,Acceptance of Disability Scale (ADS) and the Toronto Alexithymia Scale (TAS-20).Results The mean scores of disability acceptance and alexithymia were 180.45±26.93 and 52.35±8.24,respectively.The affective disorder of recognition,affective disorder of description and extroverted thinking were significantly negatively correlated with each dimension of disability acceptance(P＜0.05).Multiple linear regression analysis showed that alexithymia,gender and course of disease were influencing factors of disability acceptance for uremia patients(P＜0.05).Conclusion The level of disability acceptance was in the medium level among uremia patients,and alexithymia,gender and course of disease were its influencing factors.Nursing staff could take effective measures to ameliorate alexithymia and to improve the level of disability acceptance for uremia patients.

Objective Meta modelling was employed to develop a risk prediction model for intradialytic hypotension(IDH)and validate the model.Methods Literature on risk factors for IDH published up to March 31,2023 was retrieved from 8 databases,including Cochrane Library,PubMed,Web of Science,EBSCO,Scopus,CINAHL,CNKI and Wanfang Database.Random effects model was used to combine ORs,and factors with P＜0.05 were selected to establish the model based on their regression coefficients.286 maintenance hemodialysis patients were selected as a validation cohort to evaluate the model's discrimination,calibration and clinical utility.Results 39 studies were included,involving 25 546 patients.14 factors were identified to establish the risk prediction model.The risk score for IDH occurrence was calculated as-0.301 × male+0.015 × age+0.004 × dialysis vintage+0.988 × diabetes+0.730 × cardiovascular disease-0.042 × predialysis systolic blood pressure+0.666 × dialysis mode of hemodialysis filter+0.076 × temperature+0.159 × ultrafiltration rate+0.476 × ultrafiltration volume+1.024 × weight gain between dialysis+0.053 × serum phosphorus+0.023 × blood urea nitrogen+0.040 ×β2-microglobulin.Definition in the Kidney Disease Outcomes Quality Initiative guideline,nadir intradialytic systolic blood pressure＜90 mmHg(1 mmHg=0.133 kPa),falling intradialytic systolic blood pressure ≥20 mmHg,and definition in the United Kingdom Kidney Association guideline were selected as 4 outcomes.The areas under the curve for the prediction model with respect to these 4 outcomes were 0.830,0.648,0.647,and 0.763,respectively.Calibration curves showed that the model predictive outcomes were consistent with actual outcomes for the first 2 outcomes(x2=14.824,P=0.064;x2=12.016,P=0.149).Decision curve analysis indicated that the model had better net benefit compared to either intervention/no intervention for all definitions.Conclusion The IDH risk prediction model developed by meta-modeling in this study has good predictive performance and certain application value.