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Introduction Physical inactivity is prevalent and associated with adverse outcomes among patients with chronic kidney disease (CKD). Most previous studies have relied on subjective questionnaires to assess levels of physical activity (PA) and mainly focused on patients undergoing dialysis. Therefore, the Physical Activity Elements and Adverse Outcomes in Patients with Chronic Kidney Disease in Guangdong study aims to investigate the levels and types of PA elements and their association with adverse outcomes in Chinese non-dialysis CKD (ND-CKD) patients.Methods and analysis In this prospective cohort study, 374 patients with ND-CKD will be recruited from Guangdong province, South of China. The primary exposure will be levels of PA assessed by ActiGraph GT3X+ accelerometer including the intensity, duration, frequency and type of PA. The traditional Chinese exercises such as tai chi and Baduanjin will also be assessed. The primary outcomes will be all-cause mortality. Other variables including demographics, comorbidities, medication and laboratory markers will be registered. All data will be updated annually for at least 5 years, or until the occurrence of death or initiation of renal replacement therapy. The Spearman correlation coefficient will be used to investigate the correlation between questionnaire-derived and accelerometry-derived PA. The Cox proportional hazards model will be used to investigate the association between level of PA and adverse outcomes. Non-linear associations between PA levels and outcomes, as well as the minimum desirable PA level, will be evaluated using restricted cubic splines.Ethics and dissemination The ethical permission for this study was obtained from the ethics committee of Guangdong Provincial Hospital of Chinese Medicine in Guangzhou, China (B2015-152-02). Written informed consent is obtained from all participants. The results will be disseminated by publication in a peer-reviewed journal and presented at relevant conferences.

Introduction Stroke is a leading cause of mortality and disability worldwide. Recurrent strokes result in prolonged hospitalisation and worsened functional outcomes compared with the initial stroke. Thus, it is critical to identify patients who are at high risk of stroke recurrence. This study is positioned to develop and validate a prediction model using radiomics data and machine learning methods to identify the risk of stroke recurrence in patients with acute ischaemic stroke (AIS).Methods and analysis A total of 1957 patients with AIS will be needed. Enrolment at participating hospitals will continue until the required sample size is reached, and we will recruit as many participants as possible. Multiple indicators including basic clinical data, image data, laboratory data, CYP2C19 genotype and follow-up data will be assessed at various time points during the registry, including baseline, 24 hours, 7 days, 1 month, 3 months, 6 months, 9 months and 12 months. The primary outcome was stroke recurrence. The secondary outcomes were death events, prognosis scores and adverse events. Imaging images were processed using deep learning algorithms to construct a programme capable of automatically labelling the lesion area and extracting radiomics features. The machine learning algorithms will be applied to integrate cross-scale, multidimensional data for exploratory analysis. Then, an ischaemic stroke recurrence prediction model of the best performance for patients with AIS will be established. Calibration, receiver operating characteristic and decision curve analyses will be evaluated.Ethics and dissemination This study has received ethical approval from the Medical Ethics Committee of the Second Affiliated Hospital of Nanchang University (medical research review No.34/2021), and informed consent will be obtained voluntarily. The research findings will be disseminated through publication in journals and presented at conferences.Trial registration number ChiCTR2200055209.

Introduction Hyperkalaemia (HK) is a potentially life-threatening electrolyte imbalance associated with several adverse clinical outcomes. The efficacy and negative effects of currently existing treatment options have made HK management questionable. Sodium zirconium cyclosilicate (SZC), a novel highly selective potassium binder, is approved for the treatment of HK. The present study will be aimed to assess the safety, effectiveness and treatment patterns of SZC in Chinese patients with HK in a real-world clinical setting as it is required by China’s drug review and approval process.Methods and analysis This is a multicentre, prospective cohort study which plans to enrol 1000 patients taking SZC or willing to take SZC from approximately 40 sites in China. Patients ≥18 years of age at the time of signing the written informed consent and with documented serum potassium levels ≥5.0 mmol/L within 1 year before study enrolment day will be included. Eligible patients will receive SZC treatment and will be followed up for 6 months from enrolment day. The primary objective will be to evaluate the safety of SZC for the management of HK in Chinese patients in terms of adverse events (AEs), serious AEs as well as discontinuation of SZC. The secondary objectives will include understanding the SZC dosage information in terms of its effectiveness and treatment patterns under real-world clinical practice and assessing effectiveness of SZC during the observational period.Ethics and dissemination This study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Dalian Medical University (approval number: YJ-JG-YW-2020). All the participating sites have received the ethics approval. Results will be disseminated through national and international presentations and peer-reviewed publications.Trial registration number NCT05271266.

Introduction Stroke is the most common cause of neurological disability in adults worldwide. Neural stem cell (NSC) transplantation has shown promising results as a treatment for stroke in animal experiments. The pilot investigation of stem cells in stroke phase 1 and phase 2 trials showed that transplantation of the highest dose (20 million cells) was well tolerated. Preliminary clinical benefits have also been observed. However, the trials were open-label and had a small sample size. Furthermore, human NSCs (hNSCs) were intracerebrally implanted, and some serious adverse events were considered to be related to the surgical procedure. Therefore, we plan to conduct a double-blinded, randomised controlled trial to test the safety and efficacy of intranasal injection of hNSCs.Methods and analysis This single-centre, randomised, double-blinded, parallel-controlled trial will be conducted in China. Sixty patients with ischaemic stroke who met the qualification criteria will be randomly divided into two groups: the NSCs and control groups. All participants will receive intranasal administration of hNSCs or placebo for 4 consecutive weeks. Patients will be followed up at baseline and at 4, 12, 24 and 48 weeks after intervention. The primary outcome is the National Institutes of Health Stroke Scale score (4, 12, 24 weeks after intervention). Secondary outcomes include the modified Rankin scale, Barthel index, Mini-Mental State Examination score (4, 12, 24 weeks after intervention) and cranial MRI changes (24 and 48 weeks after intervention). All adverse events will be recorded during the study period.Ethics and dissemination The study protocol was approved by the Ethics Committee of Ren Ji Hospital (2018-009). All subjects will provide informed consent. The results will be accessible in peer-reviewed publications and will be presented at academic conferences.Trial registration ChiCTR1900022741; Chinese Clinical Trial Registry.

Objective To identify the relationship between obesity indicators and hypertension–diabetes comorbidity (HDC) among adults in central China.Design and setting A cross-sectional study was conducted from 1 June 2015 to 30 September 2018 in 11 districts of Hubei Province, China.Participants A total of 29 396 participants aged 18 years or above were enrolled in the study. 2083 subjects with missing data were excluded. Eventually, 25 356 participants were available for the present analysis.Main outcome measures Data were subjected to univariable and multivariable logistic regression to examine the association between obesity indicators (body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR)) and HDC prevalence. Crude odds ratio and adjusted OR (AOR) with associated 95% CI were calculated.Results Overall, 2.8% of the respondents had HDC. The odds of HDC prevalence increased with the BMI of the participants (18.5≤BMI (kg/m2)≤23.9—1; 24≤BMI (kg/m2)≤26.9—AOR: 5.66, 95% CI: 4.25 to 7.55; BMI (kg/m2)≥27—AOR: 7.96, 95% CI: 5.83 to 10.87). The risk of HDC also increased with the WHtR of participants (WHtR≤P25—1; P25≤WHtR≤P50—AOR: 1.73, 95% CI: 1.10 to 2.71; P50 ≤WHtR≤P75—AOR: 2.51, 95% CI: 1.60 to 3.92; WHtR≥P75—AOR: 3.22, 95% CI: 2.01 to 5.16). Stratified analysis by gender showed that high BMI and WHtR were risk factors of HDC in males and females. However, the odds of HDC prevalence increased only when WHtR≥P75 in males, whereas the probability of HDC increased when WHtR≥ P25 in females.Conclusion High BMI and WHtR can increase the risk of HDC among Chinese adults. Reasonable control of BMI and WHtR may be beneficial in preventing HDC. Females should focus on maintaining an optimal WHtR earlier.

Objectives To develop and validate a nomogram model to predict chronic kidney disease (CKD) stages 3–5 prognosis.Design A retrospective cohort study. We used univariate and multivariate Cox regression analysis to select the relevant predictors. To select the best model, we evaluated the prediction models’ accuracy by concordance index (C-index), calibration curve, net reclassification index (NRI) and integrated discrimination improvement (IDI). We evaluated the clinical utility by decision curve analysis.Setting Chronic Disease Management (CDM) Clinic in the Nephrology Department at the Guangdong Provincial Hospital of Chinese Medicine.Participants Patients with CKD stages 3–5 in the derivation and validation cohorts were 459 and 326, respectively.Primary outcome measure Renal replacement therapy (haemodialysis, peritoneal dialysis, renal transplantation) or death.Results We built four models. Age, estimated glomerular filtration rate and urine protein constituted the most basic model A. Haemoglobin, serum uric acid, cardiovascular disease, primary disease, CDM adherence and predictors in model A constituted model B. Oral medications and predictors in model A constituted model C. All the predictors constituted model D. Model B performed well in both discrimination and calibration (C-index: derivation cohort: 0.881, validation cohort: 0.886). Compared with model A, model B showed significant improvement in the net reclassification and integrated discrimination (model A vs model B: NRI: 1 year: 0.339 (−0.011 to 0.672) and 2 years: 0.314 (0.079 to 0.574); IDI: 1 year: 0.066 (0.010 to 0.127), p

Objective This study aimed to develop and validate a new Learning Behaviour Questionnaire (LBQ) for the undergraduate nursing students.Study design This study was performed in two phases. Phase 1 of the study focused on questionnaire development to create a pool of items, while phase 2 focused on validity and reliability testing.Methods Semistructured interviews were used to explore nursing undergraduates’ perception of learning behaviour. A two-round modified Delphi method was used to test content validity and quantify the degree of consistency in questionnaire items. An item analysis, an exploratory factor analysis (EFA), a confirmatory factor analysis (CFA) and an internal consistency reliability check were conducted. Criterion-related validity was demonstrated through correlations with Self-Regulated Learning Scale for Undergraduates (SRLS-U). A sample of 114 nursing students was evaluated in test–retest reliability to confirm stability.Results The final LBQ consisted of four factors for the 19-item questionnaire with a 5-point rating from ‘1’ (Fully disagree) to ‘5’ (fully agree). The content validity was 0.890. EFA revealed the presence of four factors, including ‘strategy’, ‘attitude’, ‘motivation’ and ‘degree of satisfaction’. The CFA indicated good fit indexes for the proposed model (χ2/df=1.866, root mean square residual=0.037, comparative fit index =0.950, goodness-of-fit index =0.929, Tucker-Lewis index=0.941, adjusted goodness-of-fit index=0.907 and root mean square error of approximation=0.049). The LBQ correlated significantly with SRLS-U subscales (r=0.742–0.837, p