Novel method for laparoscopic rectus sheath tunneling with Lin's tube in peritoneal dialysis catheter implantation.

Laparoscopic implantation of a catheter through rectus sheath tunnel minimizes the risks of catheter failure and reduces some complications like catheter migration, hernias, and leaks. We described a novel method for laparoscopic catheter rectus sheath tunneling using an aspiration tube and a silk tie (Lin's tube). This material is easily available and yields a small fascial defect with an equivalent cannula size to minimize tissue disruption. The technique is feasible, reproducible and it may reduce the risks of postoperative leakage and hemorrhage.

Predicting hyperkalemia in patients with advanced chronic kidney disease using the XGBoost model.

BACKGROUND: Hyperkalemia is a common complication of chronic kidney disease (CKD). Hyperkalemia is associated with mortality, CKD progression, hospitalization, and high healthcare costs in patients with CKD. We developed a machine learning model to predict hyperkalemia in patients with advanced CKD at an outpatient clinic. METHODS: This retrospective study included 1,965 advanced CKD patients between January 1, 2010, and December 31, 2020 in Taiwan. We randomly divided all patients into the training (75%) and testing (25%) datasets. The primary outcome was to predict hyperkalemia (K+ > 5.5 mEq/L) in the next clinic vist. Two nephrologists were enrolled in a human-machine competition. The area under the receiver operating characteristic curves (AUCs), sensitivity, specificity, and accuracy were used to evaluate the performance of XGBoost and conventional logistic regression models with that of these physicians. RESULTS: In a human-machine competition of hyperkalemia prediction, the AUC, PPV, and accuracy of the XGBoost model were 0.867 (95% confidence interval: 0.840-0.894), 0.700, and 0.933, which was significantly better than that of our clinicians. There were four variables that were chosen as high-ranking variables in XGBoost and logistic regression models, including hemoglobin, the serum potassium level in the previous visit, angiotensin receptor blocker use, and calcium polystyrene sulfonate use. CONCLUSIONS: The XGBoost model provided better predictive performance for hyperkalemia than physicians at the outpatient clinic.

Can chronic kidney disease staging early predict outcome of large-artery ischemic stroke with impaired renal function?

Background: Ischemic stroke poses a major threat to human beings, and a prompt intravenous thrombolytic management remains the gold standard protocol for stroke sufferers. Although the role of thrombolytic therapy (r-tPA) for ischemic stroke patients and those with underlying impaired renal function has been advocated as effective treating strategy, there is still a lack of investigation as to finding out baseline important variables that are capable of early outcome prediction. Objectives: In this project, we hypothesize that the change of clinical chronic kidney disease (CKD) staging (delta stage = CKD stage after 3-month follow-up - CKD stage at admission) could serve as a crucial predictor of the prognosis of patients. Design: This is a cohort longitudinal retrospective study. Sources and Methods: A total of 765 cerebral artery ischemic stroke patients with impaired renal function were recruited and followed up for 1 year. Among them, 116 had received the thrombolytic treatment (r-tPA) after being evaluated at the triage in the emergency department and the rest had not (non-r-tPA). Propensity-matching was applied to compare the mortality between the r-tPA and non-r-tPA groups. Multiple logistic regression (LR) and decision tree (DT) algorithm were used to identify important prediction factors for mortality as well as the improvement in neurological function. Results: The 1-year mortality rates for r-tPA and non-r-tPA groups were 32.8% and 44.4%, respectively. The propensity-matched odds ratio of mortality for the r-tPA group compared with the non-r-tPA group is 0.469, with p = 0.003. Logistic regressions suggest that age, Hct, diabetes mellitus type 2, coronary artery disease, and delta stage are important factors for mortality for the non-r-tPA group, whereas age, diabetes mellitus type 2, chronic heart failure, hospital day, and delta stage are important factors for the r-tPA group. On the usage of antihypertensive drugs, ACEI/ARB was not associated with mortality (p = 0.198), whereas the diuretic was, with odds ratio at 1.619 (p = 0.025), indicating higher mortality after administration. Both LR and DT analyses indicate that delta stage is the most important predictor. For the r-tPA group, patients with delta stage ⩽0 had a 24% mortality, while that for delta stage >0 the mortality is 75%. For non-r-tPA patients, the corresponding mortalities were 30.9 and 66.3, respectively. Delta stage is also useful for predicting patients' improvement of neurological function, assessed by NIHSS, mRS, and Barthel Index. The areas under the curve for the three assessments are 0.83, 0.835, and 0.663, respectively. Conclusion: Large-artery ischemic stroke patients who received thrombolytic treatment had significantly lower mortality, even when presenting underlying impaired renal function. The change of CKD staging (delta stage) is capable of acting as a powerful clinical baseline surrogate for both r-tPA and non-r-tPA patients in terms of early outcome prediction. Long-term use of diuretics could be potentially harmful to this group of patients. Moreover, delta stage correlates well with clinical long-term neurological functionality assessment (NIHSS, mRS, and Barthel index), which is helpful in aiding urgent clinical decision-making.

The impact of acute kidney injury with or without recovery on long-term kidney outcome in patients undergoing living liver transplantation.

BACKGROUND: Acute kidney injury (AKI) is associated with an increased incidence of poor liver graft and renal outcomes in patients who have undergone liver transplantation (LT). To date, no comprehensive study has compared patients with and without post-LT AKI and analyzed patients who recovered from AKI versus those who did not. METHODS: Patients who received living LT between January 2003 and January 2019 were enrolled. We diagnosed and classified AKI patients based on AKI-KDIGO guidelines by increment of creatinine after surgery when compared with serum creatinine on the day of surgery. The recovered AKI subgroup included recipients whose estimated glomerular filtration rate (eGFR) recovered more than 90% of baseline eGFR within 90 days after surgery. The risk of chronic kidney disease (CKD; eGFR <60 mL/min/1.73 m2) was investigated. RESULTS: A total of 392 patients, 77.3% men and mean ± standard deviation age 54.1 ± 8.4 years, met the eligible criteria and were divided into two groups (AKI vs non-AKI) and 243 (62%) patients developed AKI within 7 days after surgery. Compared with the non-AKI group, the AKI group was associated with an adjusted hazard ratio of 1.55 (95% CI 1.12-2.14) for the risk of incident CKD. Among AKI patients, 160 (65.8%) patients recovered renal function and 83 (34.2%) patients did not. Compared with the non-AKI group, the AKI non-recovery group was associated with an adjusted hazard ratio of 2.87 (95% CI 1.95-4.21) for the risk of incident CKD, while the AKI recovery group had no significant difference in the adjusted risk of incident CKD. CONCLUSIONS: Post-LT AKI is associated with subsequent risk of CKD development. Taking into account recovery status, AKI was no longer associated with a higher risk of CKD if renal function recovered within 90 days after surgery. Identification and implementation of targeted and individualized therapies for patients at risk for AKI, particularly non-recovery AKI, is of paramount importance to reduce incident CKD during follow-up.

Serum globulin is a novel predictor of mortality in patients undergoing peritoneal dialysis.

Serum globulin, which is composed mainly of immunoglobulins and acute phase proteins, can be considered as reflecting the inflammatory state. We conducted the present study to investigate the role of globulin in mortality risk in patients undergoing peritoneal dialysis (PD). The study participants were categorized by the median globulin value (2.8 g/dL) as the high globulin group (≥ 2.8 g/dL), and low globulin group (< 2.8 g/dL). Serum globulin is calculated by the equation: (serum total protein-serum albumin). The area under the curve (AUC) by the receiver operating characteristics curve analysis was calculated to compare the mortality prediction capacity of globulin with that of ferritin, and WBC counts. Among the 554 patients, 265 (47.83%) were men, the mean age was 52.91 ± 15.54 years and the body mass index was 23.44 ± 3.88 kg/m2. Multivariate Cox models showed the high globulin group had higher mortality risks of all-cause and cardiovascular disease (CVD), compared with the low globulin group with adjusted HRs of 2.06 (95% CI 1.39-3.05) and 1.94 (95% CI 1.18-3.16), respectively. The AUC of univariate and multivariate models for all-cause mortality resulted in higher AUC values for globulin than for ferritin and white blood cell (WBC) counts. In patients undergoing PD, the serum globulin can serve as a novel and independent determinant of predicting overall and CVD- associated mortality.

Infection in Living Donor Liver Transplantation Leads to Increased Risk of Adverse Renal Outcomes.

(1) Background: Little is known about the subsequent renal function change following incident infectious diseases in living-donor liver transplant (LT) recipients. (2) Methods: We studied patients who underwent living-donor LT from January 2003 to January 2019 to evaluate the association of incident hospitalization with major infections or pneumonia with adverse renal outcomes, including a sustained 40% reduction in estimated glomerular filtration rate (eGFR) and renal composite outcome (a 40% decline in eGFR, end-stage renal disease, or death.). Multivariable-adjusted time-dependent Cox models with infection as a time-varying exposure were used to estimate hazard ratio (HR) with 95% confidence interval (CI) for study outcomes. (3) Results: We identified 435 patients (mean age 54.6 ± 8.4 years and 76.3% men), of whom 102 had hospitalization with major infections during follow-up; the most common cause of infection was pneumonia (38.2%). In multiple Cox models, hospitalization with a major infection was associated with an increased risk of eGFR decline > 40% (HR, 3.32; 95% CI 2.13−5.16) and renal composite outcome (HR, 3.41; 95% CI 2.40−5.24). Likewise, pneumonia was also associated with an increased risk of eGFR decline > 40% (HR, 2.47; 95% CI 1.10−5.56) and renal composite outcome (HR, 4.37; 95% CI 2.39−8.02). (4) Conclusions: Our results illustrated the impact of a single infection episode on the future risk of adverse renal events in LT recipients. Whether preventive and prophylactic care bundles against infection and judicious modification of the immunosuppressive regimen benefit renal outcomes may deserve further study.

Predicting Mortality Using Machine Learning Algorithms in Patients Who Require Renal Replacement Therapy in the Critical Care Unit.

Background: General severity of illness scores are not well calibrated to predict mortality among patients receiving renal replacement therapy (RRT) for acute kidney injury (AKI). We developed machine learning models to make mortality prediction and compared their performance to that of the Sequential Organ Failure Assessment (SOFA) and HEpatic failure, LactatE, NorepInephrine, medical Condition, and Creatinine (HELENICC) scores. Methods: We extracted routinely collected clinical data for AKI patients requiring RRT in the MIMIC and eICU databases. The development models were trained in 80% of the pooled dataset and tested in the rest of the pooled dataset. We compared the area under the receiver operating characteristic curves (AUCs) of four machine learning models (multilayer perceptron [MLP], logistic regression, XGBoost, and random forest [RF]) to that of the SOFA, nonrenal SOFA, and HELENICC scores and assessed calibration, sensitivity, specificity, positive (PPV) and negative (NPV) predicted values, and accuracy. Results: The mortality AUC of machine learning models was highest for XGBoost (0.823; 95% confidence interval [CI], 0.791−0.854) in the testing dataset, and it had the highest accuracy (0.758). The XGBoost model showed no evidence of lack of fit with the Hosmer−Lemeshow test (p > 0.05). Conclusion: XGBoost provided the highest performance of mortality prediction for patients with AKI requiring RRT compared with previous scoring systems.

Association between predialysis creatinine and mortality in acute kidney injury patients requiring dialysis.

BACKGROUND: Creatinine is widely used to estimate renal function, but this is not practical in critical illness. Low creatinine has been associated with mortality in many clinical settings. However, the associations between predialysis creatinine level, Sepsis-related Organ Failure Assessment (SOFA) score, fluid overload, and mortality in acute kidney injury patients receiving dialysis therapy (AKI-D) has not been fully addressed. METHODS: We extracted data for AKI-D patients in the eICU and MIMIC databases. We conducted a retrospective observational cohort study using the eICU dataset. The study cohort was divided into the high-creatine group and the low-creatinine group by the median value (4 mg/dL). The baseline patient information included demographic data, laboratory tests, medications, and comorbid conditions. The independent association of creatinine level with 30-day mortality was examined using multivariate logistic regression analysis. In sensitivity analyses, the associations between creatinine, SOFA score, and mortality were analyzed in patients with or without fluid overload. We also carried out an external validity using the MIMIC dataset. RESULTS: In all 1,600 eICU participants, the 30-day mortality rate was 34.2%. The crude overall mortality rate in the low-creatinine group (44.9%) was significantly higher than that in the high-creatinine group (21.9%; P < 0.001). In the fully adjusted models, the low-creatinine group was associated with a higher risk of 30-day mortality (odds ratio, 1.77; 95% confidence interval, 1.29-2.42; P < 0.001) compared with the high-creatinine group. The low-creatinine group had higher SOFA and nonrenal SOFA scores. In sensitivity analyses, the low-creatinine group had a higher 30-day mortality rate with regard to the BMI or albumin level. Fluid overloaded patients were associated with a significantly worse survival in the low-creatinine group. The results were consistent when assessing the external validity using the MIMIC dataset. CONCLUSIONS: In patients with AKI-D, lower predialysis creatinine was associated with increased mortality risk. Moreover, the mortality rate was substantially higher in patients with lower predialysis creatinine with concomitant elevation of fluid overload status.

Association of Albumin and Globulin with Mortality Risk in Incident Peritoneal Dialysis Patients.

Background: Nutrition and inflammation have been implicated in predicting mortality in patients on peritoneal dialysis (PD). Serum albumin and globulin can be regarded for the nutritional and inflammatory status. However, there is lack of data to evaluate the synergistic effect of albumin and globulin on mortality prediction. Methods: In 554 patients initiating PD from January 2001 to July 2016, we divided them into four groups by the combination of two categories of low vs. high albumin and low vs. high globulin. The median values for albumin and globulin were chosen to classify them into low or high groups. Their associations with all-cause and cardiovascular (CV) mortality were examined in Cox regression models adjusted for confounding clinical and laboratory data. Results: Patients, 52.91 ± 15.2 years old and 47.8% men, had a median (interquartile range) value of 3.3 (2.9−3.8) g/dL for albumin and 2.8 (2.5−3.2) g/dL for globulin, respectively. Patients with low albumin and high globulin had the highest all-cause mortality and CV mortality, with adjusted hazard ratios of 3.87 (95% CI 1.83−8.20, p < 0.001) and 5.65 (95% CI 2.23−14.34, p < 0.001), respectively, compared with those with a high albumin and low globulin having the lowest mortality rate. Sensitivity analyses further confirmed this relationship. Conclusions: A patient profile of either low albumin or high globulin is linked to a higher risk for mortality, particularly for a profile of both low albumin and high globulin compared with one without either of them. Further studies are needed to explore the mechanisms underlying this phenomenon and how to improve clinical outcomes in those high-risk patients.

Micro-Elimination of Hepatitis C among Patients with Kidney Disease by Using Electronic Reminder System-A Hospital-Based Experience.

BACKGROUND: Little is known about the use of an electronic reminder system for HCV screening among patients with kidney disease. In this study, we tried to determine whether reminder systems could improve the HCV screening rate in patients with kidney disease. METHODS: Patients with kidney disease were enrolled from August 2019 to December 2020 to automatically screen and order HCV antibody and RNA testing in outpatient departments. RESULTS: A total of 19,316 outpatients with kidney disease were included, and the mean age was 66.5 years. The assessment rate of HCV antibody increased from 53.1% prior to the reminder system to 79.8% after the reminder system (p < 0.001), and the assessment rate of HCV RNA increased from 71% to 82.9%. The anti-HCV seropositivity rate decreased from 7.3% at baseline to 2.5% after the implementation of the reminder system (p < 0.001), and the percentage of patients with detectable HCV RNA among those with anti-HCV seropositivity decreased from 69.1% at baseline to 46.8% (p < 0.001). CONCLUSIONS: The feasibility of an electronic reminder system for HCV screening among patients with kidney disease in a hospital-based setting was demonstrated.

Lupus nephritis with corticosteroid responsiveness: molecular changes of CD46-mediated type 1 regulatory T cells.

BACKGROUND: The engagement of the complement regulatory proteins CD46 and CD3 in human CD4+ T cells induces the type 1 regulatory T cells (Tr1) and interleukin-10 (IL-10) secretion. This study aimed to elucidate the molecular changes of Tr1 cells through CD46 cytoplasmic Cyt1 tail in lupus nephritis (LN) respond to intravenous methylprednisolone (ivMP) therapy. METHODS: We enrolled 40 pediatric patients with LN and 30 healthy controls. Clinical characteristics and peripheral blood mononuclear cells were collected before and 3 days after the administration of ivMP. Kidney specimens were taken from five LN and five minimal-change nephrotic syndrome patients. RESULTS: We found that defective CD46-mediated T-helper type 1 contraction (IL-10 switching) is present in active LN patients. The ivMP therapy enhanced LN remission, restored the production of IL-10, increased the CD46-Cyt1/Cyt2 ratio, AKT, and cAMP-responsive element-binding protein phosphorylation, and induced migration with the expression of chemokine receptor molecules CCR4, CCR6, and CCR7 of CD3/CD46-activated Tr1 cells. CONCLUSIONS: Pharmacologic interventions that alter the patterns of CD46-Cyt1/Cyt2 expression and the secretion of IL-10 by CD3/CD46-activated Tr1 cells can be used in patients with active LN. IMPACT: In patients with LN, ivMP was associated with increased IL-10 production and increased CD46-Cyt1/Cyt2 ratio and AKT phosphorylation by Tr1 cells, with enhanced potential to migration in response to CCL17. These results suggest that expression levels of CD46 isoforms Cyt1 and Cyt2 in CD4 + CD46 + Tr1 cells differ in patients with active LN but can be corrected by corticosteroid treatment. Enhancing the expression of functional CD4 + CD46 + Tr1 cells may be a useful therapeutic approach for LN.

Association of Hematuria with Renal Progression and Survival in Patients Who Underwent Living Donor Liver Transplant.

BACKGROUND: This study aimed to determine the association between episodic or persistent hematuria after liver transplantation and long-term renal outcomes. METHODS: Patients who underwent living donor liver transplantation between July 2005 and June 2019 were recruited and divided into two groups based on the finding of microscopic or gross hematuria after transplantation. All patients were followed up from the index date until the end date in May 2020. The risks of chronic kidney disease, death, and 30% and 50% declines in estimated glomerular filtration rate (eGFR) were compared between groups. RESULTS: A total of 295 patients underwent urinalysis for various reasons after undergoing transplantation. Hematuria was detected in 100 patients (group A) but was not present in 195 patients (group B). Compared with group B, group A had a higher risk of renal progression, including eGFR decline >50% [aHR = 3.447 (95%CI: 2.24~5.30), p < 0.001] and worse survival. In addition, patients who took non-steroidal anti-inflammatory drugs (NSAIDs) continuously for over seven days within six months before transplant surgery had high risks of rapid renal progression, including a >30% decline in eGFR [aHR = 1.572 (95%CI: 1.12~2.21), p = 0.009)]. CONCLUSION: Development of hematuria after surgery in patients who underwent living donor liver transplant and were exposed to NSAIDs before surgery were associated with worse long-term renal dysfunction and survival.

Machine Learning Analysis of Time-Dependent Features for Predicting Adverse Events During Hemodialysis Therapy: Model Development and Validation Study.

BACKGROUND: Hemodialysis (HD) therapy is an indispensable tool used in critical care management. Patients undergoing HD are at risk for intradialytic adverse events, ranging from muscle cramps to cardiac arrest. So far, there is no effective HD device-integrated algorithm to assist medical staff in response to these adverse events a step earlier during HD. OBJECTIVE: We aimed to develop machine learning algorithms to predict intradialytic adverse events in an unbiased manner. METHODS: Three-month dialysis and physiological time-series data were collected from all patients who underwent maintenance HD therapy at a tertiary care referral center. Dialysis data were collected automatically by HD devices, and physiological data were recorded by medical staff. Intradialytic adverse events were documented by medical staff according to patient complaints. Features extracted from the time series data sets by linear and differential analyses were used for machine learning to predict adverse events during HD. RESULTS: Time series dialysis data were collected during the 4-hour HD session in 108 patients who underwent maintenance HD therapy. There were a total of 4221 HD sessions, 406 of which involved at least one intradialytic adverse event. Models were built by classification algorithms and evaluated by four-fold cross-validation. The developed algorithm predicted overall intradialytic adverse events, with an area under the curve (AUC) of 0.83, sensitivity of 0.53, and specificity of 0.96. The algorithm also predicted muscle cramps, with an AUC of 0.85, and blood pressure elevation, with an AUC of 0.93. In addition, the model built based on ultrafiltration-unrelated features predicted all types of adverse events, with an AUC of 0.81, indicating that ultrafiltration-unrelated factors also contribute to the onset of adverse events. CONCLUSIONS: Our results demonstrated that algorithms combining linear and differential analyses with two-class classification machine learning can predict intradialytic adverse events in quasi-real time with high AUCs. Such a methodology implemented with local cloud computation and real-time optimization by personalized HD data could warn clinicians to take timely actions in advance.

The tongue features associated with chronic kidney disease.

BACKGROUND: Traditional Chinese medicine (TCM) tongue diagnosis plays an important role in differentiation of symptoms because the tongue reflects the physiological and pathological condition of the body. The automatic tongue diagnosis system (ATDS), which noninvasively captures tongue images, can provide objective and reliable diagnostic information. Chronic kidney disease (CKD) currently is an important global public health problem and contributor to morbidity and mortality from non-communicable diseases. Thus, it is interesting to analyze and probe the relationship between tongue examination and CKD. METHODS: This protocol is a cross-sectional, case-controlled observational study investigating the usefulness of the ATDS in clinical practice by examining its efficacy as a diagnostic tool for CKD. Volunteers over 20 years old with and without CKD will be enrolled. Tongue images will be captured and the patients divided into 2 groups: CKD group and healthy group. Nine primary tongue features will be extracted and analyzed, including tongue shape, tongue color, tooth mark, tongue fissure, fur color, fur thickness, saliva, ecchymosis, and red dots. RESULT: The results of this study will systematically evaluate tongue manifestations of patients and examine its efficacy as an early detection and diagnosis of CKD. DISCUSSION: The aim of this protocol is to investigate discriminating tongue features to distinguish between CKD and normal people, and establish differentiating index to facilitate the noninvasive detection of CKD. TRIAL REGISTRIES: ClinicalTrials.gov; Identifier: NCT04708743.

Effect of electroacupuncture on restless legs syndrome (RLS) in hemodialysis patients: A protocol for systematic review and meta-analysis.

BACKGROUND: Restless legs syndrome (RLS) is frequent in dialysis patients and occurs predominantly in its most severe forms. The aim of the present study was to evaluate the effects of electroacupuncture (EA) in hemodialysis patients with RLS by heart rate variability (HRV) monitor. METHODS: One hundred twelve subjects who were hemodialysis patients with RLS will be divided into 2 groups: experimental and control. Each subject will receive the treatment relevant to their group 2 times a week for 4 weeks. After 4 weeks of treatment the subject will enter a 2-week washout period, after which the subjects will switch groups. Measurements will include HRV recordings, International Restless Legs Syndrome Rating Scale (IRLSRS) and Insomnia Severity Index (ISI). RESULT: The results of this study will systematically evaluate the effectiveness and safety of electoracupuncture intervention for hemodialysis patients with RLS. DISCUSSION: This study is the first investigation to analyze the relationship between EA and the change of HRV by an objective monitor. If the findings of the current trial are positive, this study will also help support an effective, safe and cheap approach to clinical treatment of this challenging disorder, help foster improved understanding the relationship between autonomic nervous system and RLS, and ultimately contribute to elucidate the mechanisms of EA. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04356794; registration date: April 22, 2020.

Superiority of albumin-globulin ratio over albumin to predict mortality in patients undergoing peritoneal dialysis.

There is increasing evidence showing that albumin-globulin ratio (AGR) can predict the survival of patients in many types of malignancies. However, no study was done to explore the value of AGR in peritoneal dialysis (PD) patients. A total of 554 incident patients undergoing PD from January 2001 through July 2016 were enrolled for this retrospective observational study. The outcomes of interest were all-cause mortality and cardiovascular disease (CVD) mortality. Baseline patient's socio-demographic data, pharmacotherapy, comorbidities, laboratory and PD-related parameters were collected and used in the multivariate Cox models. The predictive value of AGR on mortality risk was compared with other markers using area under the receiver operating characteristic curve (AUC) analysis. Among the study participants, there were 265 (47.83%) men and the mean follow-up time was 3.87 ± 3.15 years. Univariate Cox analysis showed that low AGR was significantly associated with worse outcomes in terms of all-cause and CVD mortality and it remained an independent predictor in the multivariate models. The fully adjusted hazard ratios for the low AGR group versus high AGR group were 2.12 (95% CI 1.34-3.35, p = 0.001) and 2.58 (95% CI 1.42-4.7, p = 0.002) for all-cause and CVD mortality, respectively. The predictive ability of AGR for mortality risk was superior to that of other biomarkers based on AUC calculations. In conclusion, low AGR was independently associated with higher all-cause and CVD mortality risks in patients undergoing PD.

A family with an MYH9-related disorder with different phenotypes masquerading as immune thrombocytopaenia: an underreported disorder in Taiwan.

A 66-year-old woman had experienced abnormal bleeding since the age of 7. Thrombocytopenia was not detected until she was 48, and immune thrombocytopenia was diagnosed at age 66. She also reported experiencing hearing disturbance since the age of 30 and acute renal failure since the age of 61 but reported no visual disturbance. Her younger son, who was 40 years old, also experienced abnormal bleeding since the age of 6, but immune thrombocytopenia was diagnosed as late as age 35. He had no other associated disorders. Laboratory examinations of both mother and son revealed a low platelet count (8000 and 29,000 µL, respectively), giant platelets and Döhle body-like granulocyte inclusion bodies. The mother had a high creatinine level (15.4 mg/dL) and normal liver enzyme levels. MYH9 genetic analysis identified a heterozygous mutation, c.101T>A, p.Val34Glu at exon 2 in both patients. These clinical and laboratory findings were consistent with a diagnosis of an MYH9-related disorder with different phenotypes observed in the same family. MYH9-related disorders were recognised in 2003, but were often misdiagnosed as immune thrombocytopenia, and hence, they have rarely been reported in Taiwan.

The CHA2DS2-VASc score predicts chronic kidney disease among patients with atrial fibrillation.

BACKGROUND: It is unclear how the CHA2DS2-VASc score can predict subsequent chronic kidney disease (CKD) and end-stage renal disease (ESRD) among atrial fibrillation (AF) patients. METHODS: We identified incident AF patients without CKD between 2000 and 2013 from the National Health Insurance Research Database (NHIRD) of Taiwan and calculated the CHA2DS2-VASc score for each patient. Adjusted hazard ratio (HR) with 95% confidence interval (CI) was estimated from multivariate cause-specific Cox models to assess the risk of CKD and ESRD associated with the CHA2DS2-VASc score. RESULTS: A total of 8764 participants with AF who did not have CKD were included in the analysis. The mean age was 69.63 ± 13.48 years and 4800 (54.8%) were males. The adjusted HR of CKD displayed a stepwise increase with the increase in the CHA2DS2-VASc score. When compared with those with a CHA2DS2-VASc score of 0, the adjusted HRs of CKD were 1.57 (95% CI 1.09-2.26), 2.04 (95% CI 1.42-2.94), 2.48 (95% CI 1.70-3.62), 2.88 (95% CI 1.95-4.26), 3.29 (95% CI 2.18-4.95) and 4.00 (95% CI 2.61-6.13) for the AF patients with a CHA2DS2-VASc score of 1, 2, 3, 4, 5 and ≥ 6, respectively. Similarly, as the CHA2DS2-VASc score increased, the adjusted HR of ESRD showed a gradual increase. CONCLUSIONS: Patients with a higher CHA2DS2-VASc score were linked to a higher risk of CKD and ESRD in a dose-dependent effect, i.e. the incidence of CKD/ESRD increased with the increasing CHA2DS2-VASc score.

Association between Albumin-Globulin Ratio and Mortality in Patients with Chronic Kidney Disease.

BACKGROUND: Malnutrition and inflammation are highly prevalent and tightly regulated with each other in chronic kidney disease (CKD) patients. Inflammation can lead to malnutrition in patients with sufficient nourishment, while malnutrition may also induce an inflammatory response. This study investigated whether the albumin-globulin ratio (AGR) can predict the mortality risk in CKD patients. METHODS: We enrolled 956 stage 3-5 CKD patients retrospectively at a medical center. Patients' baseline characteristics including demographics, laboratory data, pharmacotherapy, and comorbidities were collected for statistical adjustments. The study patients were stratified into three AGR groups according to similar magnitudes of hazards for mortality as follows: low AGR group, AGR ≤ 1.0; moderate AGR group, 1.1 ≤ AGR < 1.3; high AGR group, AGR ≥1.3. Multivariate Cox proportional hazard analysis was performed to evaluate the association of the AGR with the study outcomes, including overall and cardiovascular disease (CVD) mortality. RESULTS: During a median follow-up duration of 2.44 years, 108 (11.3%) deaths were recorded and 50 patients died from CVD. In adjusted model 1, the moderate AGR group was associated with hazard ratios (HR) of 0.57 (95% CI = 0.36-0.90, p = 0.016) and 0.52 (95% CI = 0.28-0.98, p = 0.043) for all-cause and CVD mortality compared with the low AGR group, respectively. The high AGR group was associated with HRs of 0.49 (95% CI = 0.27-0.90, p = 0.021) and 0.27 (95% CI = 0.1-0.74, p = 0.01) for all-cause and CVD mortality compared with the low AGR group, respectively. Similar results were obtained in the adjusted model 2 (inverse probability of the group weighted Cox model). In addition, the association between the AGR and mortality risk remained significant when the AGR was treated as a continuous variable. CONCLUSION: AGR is a significant biomarker predicting overall and cardiovascular mortality risk independent of various important factors amongst stage 3-5 CKD patients. We suggest that the AGR may be a simple and inexpensive measurement for detecting CKD patients at risk of mortality.

Urinary cell-free mitochondrial and nuclear deoxyribonucleic acid correlates with the prognosis of chronic kidney diseases.

INTRODUCTION: Cell-free deoxyribonucleic acid DNA (cf-DNA) in urine is promising due to the advantage of urine as an easily obtained and non-invasive sample source over tissue and blood. In clinical practice, it is important to identify non-invasive biomarkers of chronic kidney disease (CKD) in monitoring and surveillance of disease progression. Information is limited, however, regarding the relationship between urine and plasma cf-DNA and the renal outcome in CKD patients. METHODS: One hundred and thirty-one CKD patients were enrolled between January 2016 and September 2018. Baseline urine and plasma cell-free mitochondrial DNA (cf-mtDNA) and cell-free nuclear DNA (cf-nDNA) were isolated using quantitative real-time PCR. Estimated glomerular filtration rate (eGFR) measurement was performed at baseline and 6-month follow-up. Favorable renal outcome was defined as eGFR at 6 months minus baseline eGFR> = 0. Receiver operator characteristics (ROC) curve analysis was performed to assess different samples of cf-DNA to predict favorable renal outcomes at 6 months. A multivariate linear regression model was used to evaluate independent associations between possible predictors and different samples of cf-DNA. RESULTS: Patients with an advanced stage of CKD has significantly low plasma cf-nDNA and high plasma neutrophil gelatinase-associated lipocalin (NGAL) levels. Low urine cf-mtDNA, cf-nDNA levels and low plasma NGAL were significantly correlated with favorable renal outcomes at 6 months. The urine albumin-creatinine ratio (ACR) or urine protein-creatinine ratio (PCR) level is a robust predictor of cf-mtDNA and cf-nDNA in CKD patients. Baseline urine levels of cf-mtDNA and cf-nDNA could predict renal outcomes at 6 months. CONCLUSIONS: Urinary cf-mtDNA and cf-nDNA may provide novel prognostic biomarkers for renal outcome in CKD patients. The levels of plasma cf-nDNA and plasma NGAL are significantly correlated with the severity of CKD.