cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.27074107.v1
title: Predictors and prognostic significance of the volume load trajectory: a longitudinal study in patients on peritoneal dialysis

description: Volume overload in peritoneal dialysis patients is a common issue that can lead to poor prognosis. We employed a group trajectory model to categorize volume load trajectories and examined the factors associated with each trajectory class to explore the impact of different trajectory groups on clinical prognosis and residual renal function (RRF). This single-center prospective cohort study included 214 patients on maintenance peritoneal dialysis within a tertiary hospital. The ratio of extracellular water to total body water was measured using Bioimpedance analysis. The SAS 9.4 PROC Traj procedure was used to examine the group-based trajectory of the patients. A multivariate logistic regression model was used to calculate the adjusted odds ratios (aOR) of the associated factors to predict the trajectory class of participants. The average age of the included patients was 53.56 (SD: 11.77) years, with a male proportion of 46.7% and a median follow-up time of 6 months. The normal stable group accounted for 35.05% of the total population and maintained a normal and stable level, the moderate stable group accounted for 52.8% of the total population and showed a slightly higher and stable level, and the high fluctuation group accounted for 12.15% of the total population and showed a high and fluctuating level. A multivariate logistic regression analysis revealed that age, diabetes, and albumin levels are significant factors influencing the categorization of volume load trajectories. There were statistically significant differences in both the technical survival rate and the loss of residual renal function among the three trajectory groups.
DOI: 10.6084/m9.figshare.27948600
title: High neutrophil-to-lymphocyte ratio as a cost-effective marker of acute kidney injury and in-hospital mortality after cardiac surgery: a case-control study

description: Inflammation is one of the important pathophysiological characteristics of acute kidney injury (AKI) after cardiac surgery. The aim was to explore the relationship between preoperative neutrophil-to-lymphocyte ratio (NLR), a simple and cost-effective maker of inflammatory response, and AKI after cardiac surgery. Furthermore, whether the NLR affected in-hospital mortality was also investigated. The electronic medical records of patients from January 1, 2006 to December 31, 2018 undergoing cardiac surgery were utilized. The interest outcome was AKI, defined as the criteria of Kidney Disease Improving Global Outcomes (KDIGO), and other outcomes were severe AKI (KDIGO stage ≥2) and in-hospital mortality. Logistic regression was utilized to assess the association of preoperative NLR with outcomes while adjust for potential confounders. Totally, 23,638 patients were included. The incidence of AKI was 27.6%. The NLR was significantly greater in patients with AKI compared to those without. As the nonlinear relationship between NLR and AKI indicated by restricted cubic spline, NLR was analyzed as a categorical variable with the cutoff value of five. Multivariate analysis demonstrated that NLR &gt; 5 was significantly associated with an increased risk of AKI, with an odds ratio of 5.046 (95% confidence interval, 4.589 to 5.548), when compared to patients with NLR ≤ 5. Furthermore, high NLR was also an independent risk factor for severe AKI and in-hospital mortality. A higher preoperative NLR was increased the risk of AKI, severe AKI, and in-hospital mortality after cardiac surgery, which may be helpful for stratifying patients to develop individualized treatment.
DOI: 10.6084/m9.figshare.27948600.v1
title: High neutrophil-to-lymphocyte ratio as a cost-effective marker of acute kidney injury and in-hospital mortality after cardiac surgery: a case-control study

description: Inflammation is one of the important pathophysiological characteristics of acute kidney injury (AKI) after cardiac surgery. The aim was to explore the relationship between preoperative neutrophil-to-lymphocyte ratio (NLR), a simple and cost-effective maker of inflammatory response, and AKI after cardiac surgery. Furthermore, whether the NLR affected in-hospital mortality was also investigated. The electronic medical records of patients from January 1, 2006 to December 31, 2018 undergoing cardiac surgery were utilized. The interest outcome was AKI, defined as the criteria of Kidney Disease Improving Global Outcomes (KDIGO), and other outcomes were severe AKI (KDIGO stage ≥2) and in-hospital mortality. Logistic regression was utilized to assess the association of preoperative NLR with outcomes while adjust for potential confounders. Totally, 23,638 patients were included. The incidence of AKI was 27.6%. The NLR was significantly greater in patients with AKI compared to those without. As the nonlinear relationship between NLR and AKI indicated by restricted cubic spline, NLR was analyzed as a categorical variable with the cutoff value of five. Multivariate analysis demonstrated that NLR &gt; 5 was significantly associated with an increased risk of AKI, with an odds ratio of 5.046 (95% confidence interval, 4.589 to 5.548), when compared to patients with NLR ≤ 5. Furthermore, high NLR was also an independent risk factor for severe AKI and in-hospital mortality. A higher preoperative NLR was increased the risk of AKI, severe AKI, and in-hospital mortality after cardiac surgery, which may be helpful for stratifying patients to develop individualized treatment.
DOI: 10.6084/m9.figshare.26879639
title: Efficacy and safety of biologics, multitarget therapy, and standard therapy for lupus nephritis: a systematic review and network meta-analysis

description: This study aimed to compare the efficacy and safety of biologics, multitarget therapy, and standard therapy for the induction of lupus nephritis. A systematic search of electronic databases (EMBASE, Web of Science, PubMed, Cochrane Library, and ClinicalTrials.gov) was conducted from inception to 30 August 2023. Our study included randomized controlled trials enrolling adult lupus nephritis patients treated with biologics or multitarget therapy, in comparison with standard therapy. The primary outcomes were the rates of complete renal remission (CRR) and serious adverse events (SAE). Stata 15.0 was used to conduct the network meta-analysis. Ten randomized controlled trials with a total of 1989 patients met the inclusion criteria. The network meta-analysis indicated that compared with standard therapy, multitarget therapy, obinutuzumab, belimumab, and voclosporin therapy demonstrated superior efficacy in achieving complete renal remission. Among these options, multitarget therapy had the greatest effect (OR = 2.78, 95% CI = 1.81–4.26). Regarding safety, it was observed that there were no significant statistical differences among the various treatment options. Cluster analysis revealed that both obinutuzumab and belimumab exhibited good efficacy and safety. belimumab and obinutuzumab stood out as promising treatments due to their good performance in terms of efficacy and safety. Multitarget therapy may be the most effective approach for treating lupus nephritis. However, since the study population consists exclusively of Asian patients, further research is needed to verify the efficacy of multitarget therapy in lupus nephritis patients of non-Asian descent.
DOI: 10.6084/m9.figshare.26879639.v1
title: Efficacy and safety of biologics, multitarget therapy, and standard therapy for lupus nephritis: a systematic review and network meta-analysis

description: This study aimed to compare the efficacy and safety of biologics, multitarget therapy, and standard therapy for the induction of lupus nephritis. A systematic search of electronic databases (EMBASE, Web of Science, PubMed, Cochrane Library, and ClinicalTrials.gov) was conducted from inception to 30 August 2023. Our study included randomized controlled trials enrolling adult lupus nephritis patients treated with biologics or multitarget therapy, in comparison with standard therapy. The primary outcomes were the rates of complete renal remission (CRR) and serious adverse events (SAE). Stata 15.0 was used to conduct the network meta-analysis. Ten randomized controlled trials with a total of 1989 patients met the inclusion criteria. The network meta-analysis indicated that compared with standard therapy, multitarget therapy, obinutuzumab, belimumab, and voclosporin therapy demonstrated superior efficacy in achieving complete renal remission. Among these options, multitarget therapy had the greatest effect (OR = 2.78, 95% CI = 1.81–4.26). Regarding safety, it was observed that there were no significant statistical differences among the various treatment options. Cluster analysis revealed that both obinutuzumab and belimumab exhibited good efficacy and safety. belimumab and obinutuzumab stood out as promising treatments due to their good performance in terms of efficacy and safety. Multitarget therapy may be the most effective approach for treating lupus nephritis. However, since the study population consists exclusively of Asian patients, further research is needed to verify the efficacy of multitarget therapy in lupus nephritis patients of non-Asian descent.
DOI: 10.6084/m9.figshare.28013083
title: Artificial intelligence in predicting chronic kidney disease prognosis. A systematic review and meta-analysis

description: Chronic kidney disease (CKD) is a common condition that can lead to serious health complications. Artificial Intelligence (AI) has shown the potential to improve the prediction of CKD progression, offering increased accuracy over traditional methods. Therefore, this systematic review and meta-analysis examine the diagnostic performance of various AI models in predicting CKD. Search was performed in different databases for studies reporting the diagnostic accuracy of AI-based prediction models for the progression of CKD. Meanwhile, pre-defined eligibility criteria were used for the selection of studies. Pooled sensitivity, specificity, and area under curve (AUC) were calculated utilizing Meta-disc 1.4. Quality assessment was performed using the prediction model risk of bias assessment tool (PROBAST). A total of 33 studies were included. The pooled sensitivity of prediction tools was 0.43 (95% CI, 0.41–0.44, <i>I<sup>2</sup></i> = 99.3%, <i>p</i> &lt; 0.01). A significant difference (<i>p</i> &lt; 0.01) was also observed in the pooled specificity 0.92 (95% CI, 0.91–0.92, <i>I<sup>2</sup></i> = 99.5%). Positive likelihood ratio (PLP) and negative likelihood ratio (NLR) were 5.12 (95% CI: 3.60–7.27, <i>I<sup>2</sup></i> = 91.3%, <i>p</i> &lt; 0.01) and 0.28 (95% CI: 0.21–0.37, <i>I<sup>2</sup></i> = 99.3%, <i>p</i> &lt; 0.01), respectively and AUC was 0.89, suggesting a diagnostic accuracy of AI-based prediction models for the progression of CKD. This study demonstrates the promising potential of AI models in predicting CKD progression. However, further efforts are needed to optimize model performance, particularly in balancing sensitivity and specificity to ensure generalizability across diverse populations. Limitations of this study include the potential for overfitting in certain AI models due to imbalanced datasets. The high heterogeneity and the lack of standardized predictors limit the generalizability of findings across different populations.
DOI: 10.6084/m9.figshare.28013083.v1
title: Artificial intelligence in predicting chronic kidney disease prognosis. A systematic review and meta-analysis

description: Chronic kidney disease (CKD) is a common condition that can lead to serious health complications. Artificial Intelligence (AI) has shown the potential to improve the prediction of CKD progression, offering increased accuracy over traditional methods. Therefore, this systematic review and meta-analysis examine the diagnostic performance of various AI models in predicting CKD. Search was performed in different databases for studies reporting the diagnostic accuracy of AI-based prediction models for the progression of CKD. Meanwhile, pre-defined eligibility criteria were used for the selection of studies. Pooled sensitivity, specificity, and area under curve (AUC) were calculated utilizing Meta-disc 1.4. Quality assessment was performed using the prediction model risk of bias assessment tool (PROBAST). A total of 33 studies were included. The pooled sensitivity of prediction tools was 0.43 (95% CI, 0.41–0.44, <i>I<sup>2</sup></i> = 99.3%, <i>p</i> &lt; 0.01). A significant difference (<i>p</i> &lt; 0.01) was also observed in the pooled specificity 0.92 (95% CI, 0.91–0.92, <i>I<sup>2</sup></i> = 99.5%). Positive likelihood ratio (PLP) and negative likelihood ratio (NLR) were 5.12 (95% CI: 3.60–7.27, <i>I<sup>2</sup></i> = 91.3%, <i>p</i> &lt; 0.01) and 0.28 (95% CI: 0.21–0.37, <i>I<sup>2</sup></i> = 99.3%, <i>p</i> &lt; 0.01), respectively and AUC was 0.89, suggesting a diagnostic accuracy of AI-based prediction models for the progression of CKD. This study demonstrates the promising potential of AI models in predicting CKD progression. However, further efforts are needed to optimize model performance, particularly in balancing sensitivity and specificity to ensure generalizability across diverse populations. Limitations of this study include the potential for overfitting in certain AI models due to imbalanced datasets. The high heterogeneity and the lack of standardized predictors limit the generalizability of findings across different populations.
DOI: 10.6084/m9.figshare.26124117
title: Predictors, prevalence and prognostic role of pulmonary hypertension in patients with chronic kidney disease: a systematic review and meta-analysis

description: To estimate the predictors, prevalence and prognostic role of pulmonary hypertension (PH) in patients with chronic kidney disease (CKD) using meta-analysis. The PubMed, EmBase, and the Cochrane library were systematically searched for eligible studies from inception till May 2024. All of pooled analyses were performed using the random-effects model. Fifty observational studies involving 17,558 CKD patients were selected. The prevalence of PH in CKD patients was 38% (95% confidence interval [CI]: 33%–43%), and the prevalence according to CKD status were 31% (95% CI: 20%–42%) for CKD (I-V), 39% (95% CI: 25%–54%) for end stage kidney disease (ESKD) (predialysis), 42% (95% CI: 35%–50%) for ESKD (hemodialysis), and 26% (95% CI: 19%–34%) for renal transplant. We noted the risk factors for PH in CKD included Black individuals (relative risk [RR]: 1.39; 95% CI: 1.18–1.63; <i>p</i> &lt; 0.001), chronic obstructive pulmonary disease (RR: 1.48; 95% CI: 1.21-1.82; <i>p</i> &lt; 0.001), cardiovascular disease history (RR: 1.62; 95% CI: 1.05–2.51; <i>p</i> = 0.030), longer dialysis (RR: 1.70; 95% CI: 1.18–2.46; <i>p</i> = 0.005), diastolic dysfunction (RR: 1.88; 95% CI: 1.38–2.55; <i>p</i> &lt; 0.001), systolic dysfunction (RR: 3.75; 95% CI: 2.88–4.87; <i>p</i> &lt; 0.001), and grade 5 CKD (RR: 5.64; 95% CI: 3.18–9.98; <i>p</i> &lt; 0.001). Moreover, PH in CKD patients is also associated with poor prognosis, including all-cause mortality, major cardiovascular events, and cardiac death. This study systematically identified risk factors for PH in CKD patients, and PH were associated with poor prognosis. Therefore, patients with high prevalence of PH should be identified for treatment.
DOI: 10.6084/m9.figshare.26124117.v1
title: Predictors, prevalence and prognostic role of pulmonary hypertension in patients with chronic kidney disease: a systematic review and meta-analysis

description: To estimate the predictors, prevalence and prognostic role of pulmonary hypertension (PH) in patients with chronic kidney disease (CKD) using meta-analysis. The PubMed, EmBase, and the Cochrane library were systematically searched for eligible studies from inception till May 2024. All of pooled analyses were performed using the random-effects model. Fifty observational studies involving 17,558 CKD patients were selected. The prevalence of PH in CKD patients was 38% (95% confidence interval [CI]: 33%–43%), and the prevalence according to CKD status were 31% (95% CI: 20%–42%) for CKD (I-V), 39% (95% CI: 25%–54%) for end stage kidney disease (ESKD) (predialysis), 42% (95% CI: 35%–50%) for ESKD (hemodialysis), and 26% (95% CI: 19%–34%) for renal transplant. We noted the risk factors for PH in CKD included Black individuals (relative risk [RR]: 1.39; 95% CI: 1.18–1.63; <i>p</i> &lt; 0.001), chronic obstructive pulmonary disease (RR: 1.48; 95% CI: 1.21-1.82; <i>p</i> &lt; 0.001), cardiovascular disease history (RR: 1.62; 95% CI: 1.05–2.51; <i>p</i> = 0.030), longer dialysis (RR: 1.70; 95% CI: 1.18–2.46; <i>p</i> = 0.005), diastolic dysfunction (RR: 1.88; 95% CI: 1.38–2.55; <i>p</i> &lt; 0.001), systolic dysfunction (RR: 3.75; 95% CI: 2.88–4.87; <i>p</i> &lt; 0.001), and grade 5 CKD (RR: 5.64; 95% CI: 3.18–9.98; <i>p</i> &lt; 0.001). Moreover, PH in CKD patients is also associated with poor prognosis, including all-cause mortality, major cardiovascular events, and cardiac death. This study systematically identified risk factors for PH in CKD patients, and PH were associated with poor prognosis. Therefore, patients with high prevalence of PH should be identified for treatment.
DOI: 10.6084/m9.figshare.26879641
title: Association of peripheral eosinophil count with chronic kidney disease progression risk: a retrospective cohort study in Chinese population

description: The role of peripheral eosinophils in chronic kidney disease (CKD) requires further evaluation. We aimed to determine whether an eosinophil count increase is related to the occurrence of end-stage renal disease (ESRD). This single-center, observational, retrospective cohort study was conducted between January 2016 and December 2018 in Hangzhou, China, and included 3163 patients, categorized into four groups according to peripheral eosinophil count (PEC) quartile values. The main outcome was ESRD development during follow-up. We evaluated the relationship between the serum eosinophil count, demographic and clinical information, and ESRD incidence. Cox proportional hazards models and Kaplan–Meier survival curves were used. A total of 3163 patients with CKD were included in this cohort, of whom 1254 (39.6%) were females. The median (interquartile range [IQR]) age was 75 [64, 85] years, and the median (IQR) estimated glomerular filtration rate was 55.16 [45.19, 61.19] mL/min/1.73 m<sup>2</sup>. The median PEC was 0.1224 × 10<sup>9</sup>/L (IQR, 0.0625–0.212). Among the 3163 patients with CKD, 273 (8.6%) developed ESRD during a median follow-up time of 443.8 [238.8, 764.9] days. Individuals in the highest PEC quartile had a 66.2% higher ESRD risk than those in the lowest quartile (hazard ratio, 1.662; 95% confidence interval, 1.165–2.372). The results from the Kaplan–Meier survival curves confirmed the conclusion. Alongside traditional risk factors, patients with CKD and an elevated PEC are more likely to develop ESRD. Therefore, more attention should be paid to those patients with CKD who have a high PEC.
DOI: 10.6084/m9.figshare.26879641.v1
title: Association of peripheral eosinophil count with chronic kidney disease progression risk: a retrospective cohort study in Chinese population

description: The role of peripheral eosinophils in chronic kidney disease (CKD) requires further evaluation. We aimed to determine whether an eosinophil count increase is related to the occurrence of end-stage renal disease (ESRD). This single-center, observational, retrospective cohort study was conducted between January 2016 and December 2018 in Hangzhou, China, and included 3163 patients, categorized into four groups according to peripheral eosinophil count (PEC) quartile values. The main outcome was ESRD development during follow-up. We evaluated the relationship between the serum eosinophil count, demographic and clinical information, and ESRD incidence. Cox proportional hazards models and Kaplan–Meier survival curves were used. A total of 3163 patients with CKD were included in this cohort, of whom 1254 (39.6%) were females. The median (interquartile range [IQR]) age was 75 [64, 85] years, and the median (IQR) estimated glomerular filtration rate was 55.16 [45.19, 61.19] mL/min/1.73 m<sup>2</sup>. The median PEC was 0.1224 × 10<sup>9</sup>/L (IQR, 0.0625–0.212). Among the 3163 patients with CKD, 273 (8.6%) developed ESRD during a median follow-up time of 443.8 [238.8, 764.9] days. Individuals in the highest PEC quartile had a 66.2% higher ESRD risk than those in the lowest quartile (hazard ratio, 1.662; 95% confidence interval, 1.165–2.372). The results from the Kaplan–Meier survival curves confirmed the conclusion. Alongside traditional risk factors, patients with CKD and an elevated PEC are more likely to develop ESRD. Therefore, more attention should be paid to those patients with CKD who have a high PEC.
DOI: 10.6084/m9.figshare.28244223
title: Utilizing Raman spectroscopy for urinalysis to diagnose acute kidney injury stages in cardiac surgery patients

description: The successful treatment and improvement of acute kidney injury (AKI) depend on early-stage diagnosis. However, no study has differentiated between the three stages of AKI and non-AKI patients following heart surgery. This study will fill this gap in the literature and help to improve kidney disease management in the future. In this study, we applied Raman spectroscopy (RS) to uncover unique urine biomarkers distinguishing heart surgery patients with and without AKI. Given the amplified risk of renal complications post-cardiac surgery, this approach is of paramount importance. Further, we employed the partial least squares-support vector machine (PLS-SVM) model to distinguish between all three stages of AKI and non-AKI patients. We noted significant metabolic disparities among the groups. Each AKI stage presented a distinct metabolic profile: stage 1 had elevated uric acid and reduced creatinine levels; stage 2 demonstrated increased tryptophan and nitrogenous compounds with diminished uric acid; stage 3 displayed the highest neopterin and the lowest creatinine levels. We utilized the PLS-SVM model for discriminant analysis, achieving over 90% identification rate in distinguishing AKI patients, encompassing all stages, from non-AKI subjects. This study characterizes the incidence and risk factors for AKI after cardiac surgery. The unique spectral information garnered from this study can also pave the way for developing an <i>in vivo</i> RS method to detect and monitor AKI effectively.