Cheungpasitporn, Wisit

Cardiac surgery-associated AKI (CSA-AKI) is common after cardiac surgery and has an adverse impact on short- and long-term mortality. Early identification of patients at high risk of CSA-AKI by applying risk prediction models allows clinicians to closely monitor these patients and initiate effective preventive and therapeutic approaches to lessen the incidence of AKI. Several risk prediction models and risk assessment scores have been developed for CSA-AKI. However, the definition of AKI and the variables utilized in these risk scores differ, making general utility complex. Recently, the utility of artificial intelligence coupled with machine learning, has generated much interest and many studies in clinical medicine, including CSA-AKI. In this article, we discussed the evolution of models established by machine learning approaches to predict CSA-AKI.

Background Abnormal circadian blood pressure ( BP ) variations during sleep, specifically the non‐dipping (<10% fall in nocturnal BP ) and reverse‐dipping patterns (rise in nocturnal BP ), have been associated with an increased risk of cardiovascular events and target organ damage. However, the relationship between abnormal sleep BP variations and cerebral small vessel disease markers is poorly established. This study aims to assess the association between non‐dipping and reverse‐dipping BP patterns with markers of silent cerebral small vessel disease. Methods and Results MEDLINE , Embase, and Cochrane Databases were searched from inception through November 2019. Studies that reported the odds ratios (ORs) for cerebral small vessel disease markers in patients with non‐dipping or reverse‐dipping BP patterns were included. Effect estimates from the individual studies were extracted and combined using the random‐effect, generic inverse variance method of DerSimonian and Laird. Twelve observational studies composed of 3497 patients were included in this analysis. The reverse‐dipping compared with normal dipping BP pattern was associated with a higher prevalence of white matter hyperintensity with a pooled adjusted OR of 2.00 (95% CI , 1.13–2.37; I 2 =36%). Non‐dipping BP pattern compared with normal dipping BP pattern was associated with higher prevalence of white matter hyperintensity and asymptomatic lacunar infarction, with pooled OR s of 1.38 (95% CI , 0.95–2.02; I 2 =52%) and 2.33 (95% CI , 1.30–4.18; I 2 =73%), respectively. Limiting to only studies with confounder‐adjusted analysis resulted in a pooled OR of 1.38 (95% CI , 0.95–2.02; I 2 =52%) for white matter hyperintensity and 1.44 (95% CI , 0.97–2.13; I 2 =0%) for asymptomatic lacunar infarction. Conclusions The non‐dipping and reverse‐dipping BP patterns are associated with neuroimaging cerebral small vessel disease markers.

Abstract Objective The objective of this meta‐analysis of observational studies was to evaluate the association between simple renal cysts (SRC) and presence of aortic pathology such as aortic aneurysms and dissection. Methods We conducted searches in Ovid MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials from January 1960 to August 2019 to identify observational studies that examined the association between SRCs and any aortic diseases, including aortic aneurysms and dissection. Two reviewers independently extracted the data and assessed the risk of bias. The meta‐analysis was performed by STATA 14.1. Results In total, 11 observational studies with 19 719 participants were included in this meta‐analysis. Compared to individuals without SRCs, patients with SRCs had higher odds of abdominal aortic aneurysm (AAA) (adjusted OR = 2.61, 95% CI 2.34‐2.91, P < 0.001, I 2 = 0%), ascending thoracic aortic aneurysm (TAA) (adjusted OR = 1.98, 95% CI 1.09‐3.63, P = 0.03, I 2 = 90.1%), descending TAA (adjusted OR = 3.44, 95% CI, 2.67‐4.43, P < 0.001, I 2 = 0%), type A aortic dissection (AD) (adjusted OR = 1.98, 95% CI 1.32‐2.96, P = 0.001, I 2 = 12.9%), and type B AD (adjusted OR = 2.55, 95% CI, 1.31‐4.96, P = 0.006, I 2 = 76.2%). There was a higher average in the sum of diameter of SRCs among AAA compared to patients without AAA (WMD = 19.80 mm, 95% CI 13.92‐25.67, P < 0.001, I 2 = 63.8%). Conclusion SRC is associated with higher odds of aortic diseases including AAA, ascending and descending TAA, type A and type B dissection even after adjusting for confounders.

This study aimed to assess the one-year mortality risk based on discharge serum chloride among the hospital survivors. We analyzed a cohort of adult hospital survivors at a tertiary referral hospital from 2011 through 2013. We categorized discharge serum chloride; ≤96, 97–99, 100–102, 103–105, 106–108, and ≥109 mmoL/L. We performed Cox proportional hazard analysis to assess the association of discharge serum chloride with one-year mortality after hospital discharge, using discharge serum chloride of 103–105 mmoL/L as the reference group. Of 56,907 eligible patients, 9%, 14%, 26%, 28%, 16%, and 7% of patients had discharge serum chloride of ≤96, 97–99, 100–102, 103–105, 106–108, and ≥109 mmoL/L, respectively. We observed a U-shaped association of discharge serum chloride with one-year mortality, with nadir mortality associated with discharge serum chloride of 103–105 mmoL/L. When adjusting for potential confounders, including discharge serum sodium, discharge serum bicarbonate, and admission serum chloride, one-year mortality was significantly higher in both discharge serum chloride ≤99 hazard ratio (HR): 1.45 and 1.94 for discharge serum chloride of 97–99 and ≤96 mmoL/L, respectively; p < 0.001) and ≥109 mmoL/L (HR: 1.41; p < 0.001), compared with discharge serum chloride of 103–105 mmoL/L. The mortality risk did not differ when discharge serum chloride ranged from 100 to 108 mmoL/L. Of note, there was a significant interaction between admission and discharge serum chloride on one-year mortality. Serum chloride at hospital discharge in the optimal range of 100–108 mmoL/L predicted the favorable survival outcome. Both hypochloremia and hyperchloremia at discharge were associated with increased risk of one-year mortality, independent of admission serum chloride, discharge serum sodium, and serum bicarbonate.

Background and Objectives: The optimal range of serum potassium at hospital discharge is unclear. The aim of this study was to assess the relationship between discharge serum potassium levels and one-year mortality in hospitalized patients. Materials and Methods: All adult hospital survivors between 2011 and 2013 at a tertiary referral hospital, who had available admission and discharge serum potassium data, were enrolled. End-stage kidney disease patients were excluded. Discharge serum potassium was defined as the last serum potassium level measured within 48 h prior to hospital discharge and categorized into ≤2.9, 3.0–3.4, 3.5–3.9, 4.0–4.4, 4.5–4.9, 5.0–5.4 and ≥5.5 mEq/L. A Cox proportional hazards analysis was performed to assess the independent association between discharge serum potassium and one-year mortality after hospital discharge, using the discharge potassium range of 4.0–4.4 mEq/L as the reference group. Results: Of 57,874 eligible patients, with a mean discharge serum potassium of 4.1 ± 0.4 mEq/L, the estimated one-year mortality rate after discharge was 13.2%. A U-shaped association was observed between discharge serum potassium and one-year mortality, with the nadir mortality in the discharge serum potassium range of 4.0–4.4 mEq/L. After adjusting for clinical characteristics, including admission serum potassium, both discharge serum potassium ≤3.9 mEq/L and ≥4.5 mEq/L were significantly associated with increased one-year mortality, compared with the discharge serum potassium of 4.0–4.4 mEq/L. Stratified analysis based on admission serum potassium showed similar results, except that there was no increased risk of one-year mortality when discharge serum potassium was ≤3.9 mEq/L in patients with an admission serum potassium of ≥5.0 mEq/L. Conclusion: The association between discharge serum potassium and one-year mortality after hospital discharge had a U-shaped distribution and was independent of admission serum potassium. Favorable survival outcomes occurred when discharge serum potassium was strictly within the range of 4.0–4.4 mEq/L.

Patient monitoring after kidney transplantation (KT) for early detection of allograft rejection remains key in preventing allograft loss. Serum creatinine has poor predictive value to detect ongoing active rejection as its increase is not sensitive, nor specific for acute renal allograft rejection. Diagnosis of acute rejection requires allograft biopsy and histological assessment, which can be logistically challenging in some cases and carries inherent risk for complications related to procedure. Donor-derived cell-free DNA (dd-cfDNA), DNA of donor origin in the blood of KT recipient arising from cells undergoing injury and death, has been examined as a potential surrogate marker for allograft rejection. A rise in dd-cfDNA levels precedes changes in serum creatinine allows early detections and use as a screening tool for allograft rejection. In addition, when used in conjunction with donor-specific antibodies (DSA), it increases the pre-biopsy probability of antibody-mediated rejection (ABMR) aiding the decision-making process. Advancements in noninvasive biomarker assays such as dd-cfDNA may offer the opportunity to improve and expand the spectrum of available diagnostic tools to monitor and detect risk for rejection and positively impact outcomes for KT recipients. In this this article, we discussed the evolution of dd-cfDNA assays and recent evidence of assessment of allograft rejection and injury status of KT by the use of dd-cfDNA.

Background: This study aimed to assess the association between the percentage of glomerulosclerosis (GS) in procurement allograft biopsies from high-risk deceased donor and graft outcomes in kidney transplant recipients. Methods: The UNOS database was used to identify deceased-donor kidneys with a kidney donor profile index (KDPI) score > 85% from 2005 to 2014. Deceased donor kidneys were categorized based on the percentage of GS: 0–10%, 11–20%, >20% and no biopsy performed. The outcome included death-censored graft survival, patient survival, rate of delayed graft function, and 1-year acute rejection. Results: Of 22,006 kidneys, 91.2% were biopsied showing 0–10% GS (58.0%), 11–20% GS (13.5%), >20% GS (19.7%); 8.8% were not biopsied. The rate of kidney discard was 48.5%; 33.6% in 0–10% GS, 68.9% in 11–20% GS, and 77.4% in >20% GS. 49.8% of kidneys were discarded in those that were not biopsied. Death-censored graft survival at 5 years was 75.8% for 0–10% GS, 70.9% for >10% GS, and 74.8% for the no biopsy group. Among kidneys with >10% GS, there was no significant difference in death-censored graft survival between 11–20% GS and >20% GS. Recipients with >10% GS had an increased risk of graft failure (HR = 1.27, p < 0.001), compared with 0–10% GS. There was no significant difference in patient survival, acute rejection at 1-year, and delayed graft function between 0% and 10% GS and >10% GS. Conclusion: In >85% KDPI kidneys, our study suggested that discard rates increased with higher percentages of GS, and GS >10% is an independent prognostic factor for graft failure. Due to organ shortage, future studies are needed to identify strategies to use these marginal kidneys safely and improve outcomes.

Background: This study aimed to assess the risk factors and impact of acute myocardial infarction on in-hospital treatments, complications, outcomes, and resource utilization in hospitalized patients for heat stroke in the United States. Methods: Hospitalized patients with a principal diagnosis of heat stroke were identified in the National Inpatient Sample dataset from the years 2003 to 2014. Acute myocardial infarction was identified using the hospital International Classification of Diseases, Ninth Revision (ICD-9), diagnosis of 410.xx. Clinical characteristics, in-hospital treatment, complications, outcomes, and resource utilization between patients with and without acute myocardial infarction were compared. Results: A total of 3372 heat stroke patients were included in the analysis. Of these, acute myocardial infarction occurred in 225 (7%) admissions. Acute myocardial infarction occurred more commonly in obese female patients with a history of chronic kidney disease, but less often in male patients aged <20 years with a history of hypothyroidism. The need for mechanical ventilation, blood transfusion, and renal replacement therapy were higher in patients with acute myocardial infarction. Acute myocardial infarction was associated with rhabdomyolysis, metabolic acidosis, sepsis, gastrointestinal bleeding, ventricular arrhythmia or cardiac arrest, renal failure, respiratory failure, circulatory failure, liver failure, neurological failure, and hematologic failure. Patients with acute myocardial infarction had 5.2-times greater odds of in-hospital mortality than those without myocardial infarction. The length of hospital stay and hospitalization cost were also higher when an acute myocardial infarction occurred while hospitalized. Conclusion: Acute myocardial infarction was associated with worse outcomes and higher economic burden among patients hospitalized for heat stroke. Obesity and chronic kidney disease were associated with increased risk of acute myocardial infarction, while young male patients and hypothyroidism were associated with decreased risk.