AI-enabled electrocardiography alert intervention and all-cause mortality: a pragmatic randomized clinical trial.

The early identification of vulnerable patients has the potential to improve outcomes but poses a substantial challenge in clinical practice. This study evaluated the ability of an artificial intelligence (AI)-enabled electrocardiogram (ECG) to identify hospitalized patients with a high risk of mortality in a multisite randomized controlled trial involving 39 physicians and 15,965 patients. The AI-ECG alert intervention included an AI report and warning messages delivered to the physicians, flagging patients predicted to be at high risk of mortality. The trial met its primary outcome, finding that implementation of the AI-ECG alert was associated with a significant reduction in all-cause mortality within 90 days: 3.6% patients in the intervention group died within 90 days, compared to 4.3% in the control group (4.3%) (hazard ratio (HR) = 0.83, 95% confidence interval (CI) = 0.70-0.99). A prespecified analysis showed that reduction in all-cause mortality associated with the AI-ECG alert was observed primarily in patients with high-risk ECGs (HR = 0.69, 95% CI = 0.53-0.90). In analyses of secondary outcomes, patients in the intervention group with high-risk ECGs received increased levels of intensive care compared to the control group; for the high-risk ECG group of patients, implementation of the AI-ECG alert was associated with a significant reduction in the risk of cardiac death (0.2% in the intervention arm versus 2.4% in the control arm, HR = 0.07, 95% CI = 0.01-0.56). While the precise means by which implementation of the AI-ECG alert led to decreased mortality are to be fully elucidated, these results indicate that such implementation assists in the detection of high-risk patients, prompting timely clinical care and reducing mortality. ClinicalTrials.gov registration: NCT05118035 .

Artificial intelligence-enabled electrocardiography contributes to hyperthyroidism detection and outcome prediction.

BACKGROUND: Hyperthyroidism is frequently under-recognized and leads to heart failure and mortality. Timely identification of high-risk patients is a prerequisite to effective antithyroid therapy. Since the heart is very sensitive to hyperthyroidism and its electrical signature can be demonstrated by electrocardiography, we developed an artificial intelligence model to detect hyperthyroidism by electrocardiography and examined its potential for outcome prediction. METHODS: The deep learning model was trained using a large dataset of 47,245 electrocardiograms from 33,246 patients at an academic medical center. Patients were included if electrocardiograms and measurements of serum thyroid-stimulating hormone were available that had been obtained within a three day period. Serum thyroid-stimulating hormone and free thyroxine were used to define overt and subclinical hyperthyroidism. We tested the model internally using 14,420 patients and externally using two additional test sets comprising 11,498 and 596 patients, respectively. RESULTS: The performance of the deep learning model achieves areas under the receiver operating characteristic curves (AUCs) of 0.725-0.761 for hyperthyroidism detection, AUCs of 0.867-0.876 for overt hyperthyroidism, and AUC of 0.631-0.701 for subclinical hyperthyroidism, superior to a traditional features-based machine learning model. Patients identified as hyperthyroidism-positive by the deep learning model have a significantly higher risk (1.97-2.94 fold) of all-cause mortality and new-onset heart failure compared to hyperthyroidism-negative patients. This cardiovascular disease stratification is particularly pronounced in subclinical hyperthyroidism, surpassing that observed in overt hyperthyroidism. CONCLUSIONS: An innovative algorithm effectively identifies overt and subclinical hyperthyroidism and contributes to cardiovascular risk assessment.

Hyperthyroidism occurs when the thyroid gland produces too much hormone and can cause various symptoms including faster heartbeat, weight loss, and nervousness. Diagnosis is often missed, which can lead to heart problems and even death. Measurements of the heart's electrical activity can be obtained using Electrocardiograms (ECGs). We made a computational model that can detect hyperthyroidism from ECGs. Our model was better able to identify people with hyperthyroidism than currently available methods, especially the more severe forms of the condition. If future work demonstrates our model is safe and accurate, it could potentially be used to detect hyperthyroidism sooner, enabling faster treatment and improved health of people with hyperthyroidism.

Identification and characterization of a novel CASR mutation causing familial hypocalciuric hypercalcemia.

Context: Although a monoallelic mutation in the calcium-sensing receptor (CASR) gene causes familial hypocalciuric hypercalcemia (FHH), the functional characterization of the identified CASR mutation linked to the clinical response to calcimimetics therapy is still limited. Objective: A 45-year-old male presenting with moderate hypercalcemia, hypocalciuria, and inappropriately high parathyroid hormone (PTH) had a good response to cinacalcet (total serum calcium (Ca2+) from 12.5 to 10.1 mg/dl). We identified the genetic mutation and characterized the functional and pathophysiological mechanisms, and then linked the mutation to calcimimetics treatment in vitro. Design: Sanger sequencing of the CASR, GNA11, and AP2S1 genes was performed in his family. The simulation model was used to predict the function of the identified mutant. In vitro studies, including immunoblotting, immunofluorescence, a cycloheximide chase study, Calbryte™ 520 Ca2+ detection, and half-maximal effective concentration (EC50), were examined. Results: This proband was found to carry a de novo heterozygous missense I554N in the cysteine-rich domain of CASR, which was pathogenic based on the different software prediction models and ACGME criteria. The simulation model showed that CASR I554N mutation decreased its binding energy with Ca2+. Human CASR I554N mutation attenuated the stability of CASR protein, reduced the expression of p-ERK 1/2, and blunted the intracellular Ca2+ response to gradient extracellular Ca2+ (eCa2+) concentration. The EC50 study also demonstrated the correctable effect of calcimimetics on the function of the CASR I554N mutation. Conclusion: This novel CASR I554N mutation causing FHH attenuates CASR stability, its binding affinity with Ca2+, and the response to eCa2+ corrected by therapeutic calcimimetics.

The screening, diagnosis, and management of patients with autosomal dominant polycystic kidney disease: A national consensus statement from Taiwan.

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited cause of end-stage kidney disease (ESKD) worldwide. Guidelines for the diagnosis and management of ADPKD in Taiwan remains unavailable. In this consensus statement, we summarize updated information on clinical features of international and domestic patients with ADPKD, followed by suggestions for optimal diagnosis and care in Taiwan. Specifically, counselling for at-risk minors and reproductive issues can be important, including ethical dilemmas surrounding prenatal diagnosis and pre-implantation genetic diagnosis. Studies reveal that ADPKD typically remains asymptomatic until the fourth decade of life, with symptoms resulting from cystic expansion with visceral compression, or rupture. The diagnosis can be made based on a detailed family history, followed by imaging studies (ultrasound, computed tomography, or magnetic resonance imaging). Genetic testing is reserved for atypical cases mostly. Common tools for prognosis prediction include total kidney volume, Mayo classification and PROPKD/genetic score. Screening and management of complications such as hypertension, proteinuria, urological infections, intracranial aneurysms, are also crucial for improving outcome. We suggest that the optimal management strategies of patients with ADPKD include general medical care, dietary recommendations and ADPKD-specific treatments. Key points include rigorous blood pressure control, dietary sodium restriction and Tolvaptan use, whereas the evidence for somatostatin analogues and mammalian target of rapamycin (mTOR) inhibitors remains limited. In summary, we outline an individualized care plan emphasizing careful monitoring of disease progression and highlight the need for shared decision-making among these patients.

Novel Prediction Score for Arterial-Esophageal Fistula in Patients with Esophageal Cancer Bleeding: A Multicenter Study.

PURPOSE: To develop and internally validate a novel prediction score to predict the occurrence of arterial-esophageal fistula (AEF) in esophageal cancer bleeding. METHODS: This retrospective cohort study enrolled patients with esophageal cancer bleeding in the emergency department. The primary outcome was the diagnosis of AEF. The patients were randomly divided into a derivation group and a validation group. In the derivation stage, a predictive model was developed using logistic regression analysis. Subsequently, internal validation of the model was conducted in the validation cohort during the validation stage to assess its discrimination ability. RESULTS: A total of 257 patients were enrolled in this study. All participants were randomized to a derivation cohort (n = 155) and a validation cohort (n = 102). AEF occurred in 22 patients (14.2%) in the derivation group and 14 patients (13.7%) in the validation group. A predictive model (HEARTS-Score) comprising five variables (hematemesis, active bleeding, serum creatinine level >1.2 mg/dL, prothrombin time >13 s, and previous stent implantation) was established. The HEARTS-Score demonstrated a high discriminative ability in both the derivation and validation cohorts, with c-statistics of 0.90 (95% CI 0.82-0.98) and 0.82 (95% CI 0.72-0.92), respectively. CONCLUSIONS: By employing this novel prediction score, clinicians can make more objective risk assessments, optimizing diagnostic strategies and tailoring treatment approaches.

A novel prognostic model to predict mortality in patients with acute-on-chronic liver failure in intensive care unit.

Acute-on-chronic liver failure (ACLF) implies high short-term mortality rates and usually requires intensive care unit (ICU) admission. Proper prognosis for these patients is crucial for early referral for liver transplantation. The superiority of CLIF-C ACLF score in Asian patients with ACLF admitted to an ICU remains inconclusive when compared to other scoring systems. The purpose of the study is (i) to compare the predictive performance of original MELD, MELD-Lactate, CLIF-C ACLF, CLIF-C ACLF-Lactate, and APACHE-II scores for short-term mortality assessment. (ii) to build and validate a novel scoring system and to compare its predictive performance to that of the original five scores. Two hundred sixty-five consecutive cirrhotic patients with ACLF who were admitted to our ICU were enrolled. The prognostic values for mortality were assessed by ROC analysis. A novel model was developed and internally validated using fivefold cross-validation. Alcohol abuse was identified as the primary etiology of cirrhosis. The AUROC of the five prognostic scores were not significantly superior to each other in predicting 1-month and 3-month mortality. The newly developed prognostic model, incorporating age, alveolar-arterial gradient (A-a gradient), BUN, total bilirubin level, INR, and HE grades, exhibited significantly improved performance in predicting 1-month and 3-month mortality with AUROC of 0.863 and 0.829, respectively, as compared to the original five prognostic scores. The novel ACLF model seems to be superior to the original five scores in predicting short-term mortality in ACLF patients admitted to an ICU. Further rigorous validation is required.

Prognostic Factors in Children with Acute Kidney Injury Requiring Continuous Renal Replacement Therapy.

INTRODUCTION: This study aims to evaluate prognostic factors and outcomes in a single-center PICU cohort that received continuous renal replacement therapy (CRRT). METHODS: This retrospective study analyzed clinical characteristics, laboratory data, and outcomes. Ninety-day mortality and advanced chronic kidney disease (CKD) (eGFR <60 ml/min/1.73m2) were defined as primary and secondary outcomes, respectively. RESULTS: Seventy-five patients were enrolled, all of whom received CRRT for indications including acute kidney injury with complicated refractory metabolic acidosis, electrolyte derangement, and existed or impending fluid overload. The 90-day mortality and advanced CKD were 53% and 29%, respectively. Multivariate Cox regression analysis demonstrated that only underlying bone marrow transplantation (BMT) (HR 4.58; 95% CI 2.04-10.27) and a high pSOFA score (HR 1.12; 95% CI 1.01-1.23) were independent risk factors for 90-day mortality. Among survivors, ten developed advanced CKD on the 90th day, and this group had a higher serum fibrinogen level (OR 1.01; 95% CI 1.01-1.03) at the start of CRRT. CONCLUSION: In critically ill children with AKI requiring CRRT, post-BMT and high pSOFA scores are independent risk factors for 90-day mortality. Additionally, a high serum fibrinogen level at the initiation of CRRT is associated with the development of advanced CKD.

Excess Salt Intake Activates IL-21-Dominant Autoimmune Diabetogenesis via a Salt-Regulated Ste20-Related Proline/Alanine-Rich Kinase in CD4 T Cells.

The fundamental mechanisms by which a diet affects susceptibility to or modifies autoimmune diseases are poorly understood. Excess dietary salt intake acts as a risk factor for autoimmune diseases; however, little information exists on the impact of salt intake on type 1 diabetes. To elucidate the potential effect of high salt intake on autoimmune diabetes, nonobese diabetic (NOD) mice were fed a high-salt diet (HSD) or a normal-salt diet (NSD) from 6 to 12 weeks of age and monitored for diabetes development. Our results revealed that the HSD accelerated diabetes progression with more severe insulitis in NOD mice in a CD4+ T-cell-autonomous manner when compared with the NSD group. Moreover, expression of IL-21 and SPAK in splenic CD4+ T cells from HSD-fed mice was significantly upregulated. Accordingly, we generated T-cell-specific SPAK knockout (CKO) NOD mice and demonstrated that SPAK deficiency in T cells significantly attenuated diabetes development in NOD mice by downregulating IL-21 expression in CD4+ T cells. Furthermore, HSD-triggered diabetes acceleration was abolished in HSD-fed SPAK CKO mice when compared with HSD-fed NOD mice, suggesting an essential role of SPAK in salt-exacerbated T-cell pathogenicity. Finally, pharmacological inhibition of SPAK activity using a specific SPAK inhibitor (closantel) in NOD mice ameliorated diabetogenesis, further illuminating the potential of a SPAK-targeting immunotherapeutic approach for autoimmune diabetes. Here, we illustrate that a substantial association between salt sensitivity and the functional impact of SPAK on T-cell pathogenicity is a central player linking high-salt-intake influences to immunopathophysiology of diabetogenesis in NOD mice.

Phenotype, genotype, and clinical outcome of Taiwanese with congenital nephrotic syndrome.

BACKGROUND/PURPOSE: Congenital nephrotic syndrome (CNS) is one of the important causes of end-stage kidney disease in children. Studies on the genotype, phenotype, and clinical outcome in infants with CNS caused by genetic mutations are scarce. METHODS: We analyzed the genetic background, clinical manifestations, treatment response, and prognosis of pediatric patients with CNS in Taiwan. RESULTS: Fifteen infants with CNS were enrolled, and 11 patients of median age 21 (interquartile range 3∼44) days caused by genetic mutations from 10 unrelated families were included in the study. Of the eleven patients, 9 had extra-renal manifestations including microcephaly, facial dysmorphism, and skeletal anomalies. More than two-thirds of the patients had disease onset before 1 month of age. Diffuse meningeal sclerosis was the most common histological characteristic. Whole exome sequencing followed by direct Sanger sequence revealed mutations in OSGEP (R247Q), WT1 (R366H and R467Q), LAMB2 (Q1209∗ and c. 5432-5451 19 bp deletion), NUP93 (D302V), and LAGE3 (c.188+1G > A). Three of the variants were novel. Corticosteroids and/or immunosuppressants were administered in 2 patients, but both were refractory to treatment. During the mean 3.5 years of follow-up, all but two died of uremia and sepsis. The two survivors reached end-stage kidney disease and required peritoneal dialysis, and one of them underwent uneventful renal transplantation. CONCLUSIONS: The majority of patients with CNS in Taiwan were caused by OSGEP followed by WT1 mutation. R247Q is the hotspot mutation of OSGEP in Taiwan. CNS patients in Taiwan suffer from significant morbidity and mortality.

Comparing Three Profoundly Influential Prognostic Scores in Cirrhotic Patients with Acute-on-Chronic-Liver Failure Admitted to the ICU: Prediction of One-Month Mortality-A Retrospective Cohort Study.

BACKGROUND: Acute-on-chronic-liver failure (ACLF) demonstrates high short-term mortality rates and usually requires intensive care unit (ICU) admission. Accurate prognostication of these patients is pivotal for timely referral for liver transplantation. The superiority of CLIF-C ACLF, CLIF-C ACLF lactate, and NACSELD-ACLF scores in Asian patients with ACLF admitted to an ICU remains inconclusive. AIMS: To compare the predictive performance of CLIF-C ACLF, CLIF-C ACLF lactate, and NACSELD-ACLF scores for one-month mortality. METHODS: 276 consecutive cirrhotic patients with ACLF admitted to ICU were enrolled. The prognostic values for one-month mortality were assessed by AUROC analysis. RESULTS: The primary cause of cirrhosis in this cohort was alcohol abuse (56.5%). AUROC analysis (95% confidence intervals) demonstrated that CLIF-C ACLF lactate [0.802 (0.747-0.856)] outperformed both CLIF-C ACLF [0.791 (0.733-0.848)] and NACSELD-ACLF [0.673 (0.606-0.740)] in predicting one-month mortality. However, no statistically significant difference was observed between the predictive abilities of CLIF-C ACLF and CLIF-C ACLF lactate. CONCLUSIONS: In critically ill cirrhotic patients with ACLF admitted to the hepatology ICU, CLIF ACLF-lactate outperformed CLIF-C ACLF and NACSELD-ACLF in predicting one-month mortality. Nevertheless, no statistically significant difference was observed between CLIF-C ACLF and CLIF-C ACLF lactate. Larger-scale multi-center prospective studies are warranted to validate these results.

Acute kidney disease following COVID-19 vaccination: a single-center retrospective study.

Background: Rare cases of de novo or relapsed kidney diseases associated with vaccination against coronavirus disease 2019 (COVID-19) have been increasingly reported. The aim of this study was to report the incidence, etiologies, and outcomes of acute kidney disease (AKD) following COVID-19 vaccination. Methods: This retrospective study extracted cases from renal registry of a single medical center from 1 March 2021 to 30 April 2022, prior to the significant surge in cases of the Omicron variant of COVID-19 infection in Taiwan. Adult patients who developed AKD after COVID-19 vaccination were included. We utilized the Naranjo score as a causality assessment tool for adverse vaccination reactions and charts review by peer nephrologists to exclude other causes. The etiologies, characteristics, and outcomes of AKD were examined. Results: Twenty-seven patients (aged 23 to 80 years) with AKD were identified from 1,897 vaccines (estimated rate of 13.6 per 1000 patient-years within the renal registry). A majority (77.8%) of vaccine received messenger RNA-based regimens. Their median (IQR) Naranjo score was 8 (6-9) points, while 14 of them (51.9%) had a definite probability (Naranjo score ≥ 9). The etiologies of AKD included glomerular disease (n = 16) consisting of seven IgA nephropathy, four anti-neutrophil cytoplasmic antibodies-associated glomerulonephritis (AAN), three membranous glomerulonephritis, two minimal change diseases, and chronic kidney disease (CKD) with acute deterioration (n = 11). Extra-renal manifestations were found in four patients. Over a median (IQR) follow-up period of 42 (36.5-49.5) weeks, six patients progressed to end-stage kidney disease (ESKD). Conclusion: Besides glomerulonephritis (GN), the occurrence of AKD following COVID-19 vaccination may be more concerning in high-risk CKD patients receiving multiple doses. Patients with the development of de novo AAN, concurrent extra-renal manifestations, or pre-existing moderate to severe CKD may exhibit poorer kidney prognosis.

Machine Learning to Identify Genetic Salt-Losing Tubulopathies in Hypokalemic Patients.

Introduction: Clinically distinguishing patients with the inherited salt-losing tubulopathies (SLTs), Gitelman or Bartter syndrome (GS or BS) from other causes of hypokalemia (LK) patients is difficult, and genotyping is costly. We decided to identify clinical characteristics that differentiate SLTs from LK. Methods: A total of 66 hypokalemic patients with possible SLTs were recruited to a prospective observational cohort study at the University College London Renal Tubular Clinic, London. All patients were genotyped for pathogenic variants in genes which cause SLTs; 39 patients had pathogenic variants in genes causing SLTs. We obtained similar data sets from cohorts in Taipei and Kobe, as follows: the combined data set comprised 419 patients; 291 had genetically confirmed SLT. London and Taipei data sets were combined to train machine learning (ML) algorithms, which were then tested on the Kobe data set. Results: Single biochemical variables (e.g., plasma renin) were significantly, but inconsistently, different between SLTs and LK in all cohorts. A decision table algorithm using serum bicarbonate and urinary sodium excretion (FENa) achieved a classification accuracy of 74%. This was superior to all the single biochemical variables identified previously. Conclusion: ML algorithms can differentiate true SLT in the context of a specialist clinic with some accuracy. However, based on routine biochemistry, the accuracy is insufficient to make genotyping redundant.

ER ribosomal-binding protein 1 regulates blood pressure and potassium homeostasis by modulating intracellular renin trafficking.

BACKGROUND: Genome-wide association studies (GWASs) have linked RRBP1 (ribosomal-binding protein 1) genetic variants to atherosclerotic cardiovascular diseases and serum lipoprotein levels. However, how RRBP1 regulates blood pressure is unknown. METHODS: To identify genetic variants associated with blood pressure, we performed a genome-wide linkage analysis with regional fine mapping in the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) cohort. We further investigated the role of the RRBP1 gene using a transgenic mouse model and a human cell model. RESULTS: In the SAPPHIRe cohort, we discovered that genetic variants of the RRBP1 gene were associated with blood pressure variation, which was confirmed by other GWASs for blood pressure. Rrbp1- knockout (KO) mice had lower blood pressure and were more likely to die suddenly from severe hyperkalemia caused by phenotypically hyporeninemic hypoaldosteronism than wild-type controls. The survival of Rrbp1-KO mice significantly decreased under high potassium intake due to lethal hyperkalemia-induced arrhythmia and persistent hypoaldosteronism, which could be rescued by fludrocortisone. An immunohistochemical study revealed renin accumulation in the juxtaglomerular cells of Rrbp1-KO mice. In the RRBP1-knockdown Calu-6 cells, a human renin-producing cell line, transmission electron and confocal microscopy revealed that renin was primarily retained in the endoplasmic reticulum and was unable to efficiently target the Golgi apparatus for secretion. CONCLUSIONS: RRBP1 deficiency in mice caused hyporeninemic hypoaldosteronism, resulting in lower blood pressure, severe hyperkalemia, and sudden cardiac death. In juxtaglomerular cells, deficiency of RRBP1 reduced renin intracellular trafficking from ER to Golgi apparatus. RRBP1 is a brand-new regulator of blood pressure and potassium homeostasis discovered in this study.

Atypical hemolytic uremic syndrome: Consensus of diagnosis and treatment in Taiwan.

Atypical hemolytic uremic syndrome (aHUS), characterized by microangiopathic hemolytic anemia, thrombocytopenia, and acute kidney injury, is a rare but life-threatening systemic disorder caused by the dysregulation of the complement pathway. Current advances in molecular analysis and pathogenesis have facilitated the establishment of diagnosis and development of effective complement blockade. Based on this recent consensus, we provide suggestions regarding the diagnosis and management of aHUS in Taiwan. The diagnosis of aHUS is made by the presence of TMA with normal ADAMTS13 activity without known secondary causes. Although only 60% of patients with aHUS have mutations in genes involving the compliment and coagulation systems, molecular analysis is suggestive for helping establish diagnosis, clarifying the underlying pathophysiology, guiding the treatment decision-making, predicting the prognosis, and deciding renal transplantation. Complement blockade, anti-C5 monoclonal antibody, is the first-line therapy for patients with aHUS. Plasma therapy should be considered for removing autoantibody in patients with atypical HUS caused by anti-CFH or complement inhibitor is unavailable.

Reversible cefazolin-induced status epilepticus in a peritoneal dialysis patient.

Cefazolin-induced neurotoxicity with the documented toxic concentration has not been reported in uremic patients on continuous ambulatory peritoneal dialysis (CAPD). We described an elderly female on CAPD for years presented with newly-onset status epilepticus. Her body weight was 60 kg. And she had received intraperitoneal ceftazidime and cefazolin 1.5 g once daily for her CAPD peritonitis 5 days earlier. She was disoriented but afebrile with normal blood pressure. Laboratory data showed WBC 18,480/uL, pH 6.93, HCO3 - 8.5 mmol/L, free Ca2+ 3.5 mmol/L, and albumin 2.8 g/dL. Although antiepileptic drugs and hypocalcemia correction ceased the seizure, her consciousness remained semi-coma. Image studies of brain were unremarkable. Despite undetectable serum ceftazidime, her cefazolin trough level was 149.5 µg/mL. Emergent hemodialysis rapidly resolved her neurological features accompanied by a markedly declined serum cefazolin concentration (28.6 µg/mL). Higher intraperitoneal cefazolin dosing in patients on CAPD may cause drug-induced neurotoxicity with status epilepticus which could be rapidly corrected by hemodialysis.

Case report: Rhabdomyolysis and kidney injury in a statin-treated hypothyroid patient-kill two birds with one stone.

Statin treatment for hypercholesterolemia may cause reversible rhabdomyolysis and acute kidney injury in susceptible patients. However, persistent rhabdomyolysis and acute kidney injury following discontinuation of statins require careful evaluation of the underlying causes to avoid missing a curable disease. We describe a 50-year-old woman with hypercholesterolemia [total cholesterol 345 mg/dl, low-density lipoprotein cholesterol (LDL-C) 266 mg/dL] on atorvastatin therapy (40 mg daily) for 1 month that presented with myalgia and muscle weakness. Relevant laboratory studies revealed persistent higher hypercholesterolemia with total cholesterol (312 mg/dL), high creatine kinase (CK) (5,178 U/L), and high creatinine levels (1.5 mg/dL) without dysmorphic red blood cells and proteinuria. Despite the cessation of statin therapy, serum CK level increased to 9,594 U/L, and creatinine remained at 1.5 mg/dL. A thorough work-up to assess potential underlying causes indicated low T3 and free T4 and high thyroid-stimulating hormone (TSH) levels, consistent with hypothyroidism. With aggressive thyroxine replacement for 1 month, all of the clinical features, along with elevated serum CK and creatinine levels, were completely resolved. This case highlights the fact that hypothyroidism must be kept in mind as a potential cause of concomitant myopathy and kidney injury, especially in patients with statin-resistant hypercholesterolemia.

Mycophenolate-Induced Hepatotoxicity Precipitates Tacrolimus Nephrotoxicity in a Kidney Transplant Recipient: A Case Report.

Mycophenolate (mycophenolate mofetil [MMF]; mycophenolate sodium [MPS]) and tacrolimus (FK-506) are commonly and concomitantly used to prevent rejection in organ transplant. Mycophenolate-induced hepatotoxicity causing the reduced FK-506 metabolism with nephrotoxicity may be less appreciated, leading to inappropriate management. We describe a new living donor kidney recipient receiving pretransplant and post-transplant immunosuppressants including oral mycophenolate (MMF 1 g daily) and tacrolimus (FK-506 4-8 mg daily) who developed progressive liver dysfunction (up to 10-fold increase) despite the reduced FK-506 dosage (6 mg daily). A thorough investigation including infection, inflammation, and autoimmune hepatitis were unremarkable. With a withdrawal of MMF, his liver function improved, but persistently higher trough serum FK-506 level (12-15 ng/mL) and increased serum creatinine were notable. Moreover, the reintroduction of MPS with the reduced FK-506 dosage (4 mg daily) worsened liver function along with FK-506 nephrotoxicity (serum creatinine from 1.4-2.4 mg/dL). The replacement of MPS with mammalian target of rapamycin inhibitor not only resolved liver injury but also normalized serum FK-506 level and kidney function. Mycophenolate should be kept in mind as a cause of drug-induced hepatotoxicity that can reduce tacrolimus metabolism, leading to FK-506 nephrotoxicity and acute kidney injury in organ transplant.

Peritoneal effluent MicroRNA profile for detection of encapsulating peritoneal sclerosis.

BACKGROUND: Encapsulating peritoneal sclerosis (EPS) is a catastrophic complication of peritoneal dialysis (PD) with high mortality. Our aim is to develop a novel noninvasive microRNA (miRNA) test for EPS. METHODS: We collected 142 PD effluents (EPS: 62 and non-EPS:80). MiRNA profiles of PD effluents were examined by a high-throughput real-time polymerase chain reaction (PCR) array to first screen. Candidate miRNAs were verified by single real-time PCR. The model for EPS prediction was evaluated by multiple logistic regression and machine learning. RESULTS: Seven candidate miRNAs were identified from the screening of PCR-array of 377 miRNAs. The top five area under the curve (AUC) values with 5 miRNA-ratios were selected using 127 samples (EPS: 56 vs non-EPS: 71) to produce a receiver operating characteristic curve. After considering clinical characteristics and 5 miRNA-ratios, the accuracies of the machine learning model of Random Forest and multiple logistic regression were boosted to AUC 0.97 and 0.99, respectively. Furthermore, the pathway analysis of miRNA associated targeting genes and miRNA-compound interaction network revealed that these five miRNAs played the roles in TGF-ß signaling pathway. CONCLUSION: The model-based miRNA expressions in PD effluents may help determine the probability of EPS and provide further therapeutic opinion for EPS.