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. 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. 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. 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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
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.
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.
The XGBoost model provided better predictive performance for hyperkalemia than physicians at the outpatient clinic.
Methadone is a synthetic opioid used as maintenance treatment for patients addicted to heroin. Skin irritation is one of the adverse events caused by opioid use. 344 methadone maintenance treatment ...(MMT) patients were recruited with records and measurements on methadone dose, plasma methadone concentrations, and treatment emergent symptom scales (TESS). 15 patients reported with skin irritation. Five SNPs located within the NECTIN4 genetic region were genotyped. The NECTIN4 gene within the adherens junction interaction pathway was associated with methadone dose in pathway-based genome wide association analyses (P = 0.0008). Three highly-linked SNPs, rs11265549, rs3820097, and rs4656978, were significantly associated with methadone dose (P = 0.0003), plasma concentrations of R,S-methadone (P = 0.0004) and TNF-α (P = 0.010) in all 344 MMT patients, and with self-report skin irritation symptom scores (P = 0.010) in the 15 MMT patients who reported with skin irritation. To identify the possible roles of plasma level of Nectin-4 in the responses to MMT and opioid use, additional age- and gender-matched 51 controls and 83 methadone-free abstinent former heroin users were recruited. Plasma level of Nectin-4 was the highest in MMT patients among the three groups. The results suggest involvement of genetic variants on NECTIN4 in methadone dose. Plasma Nectin-4 level is likely an indicator for continued use of opioids.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
Recently, accumulating evidence has demonstrated that RDW independently predicts clinically important outcomes in many populations. However, the role of RDW has not been elucidated in chronic kidney ...disease (CKD) patients. We conducted the present study with the aim to evaluate the predictive value of RDW in CKD patients.
A retrospective observational cohort study of 1075 stage 3-5 CKD patients was conducted in a medical center. The patients' baseline information included demographic data, laboratory values, medications, and comorbid conditions. The upper limit of normal RDW value (14.9%) was used to divide the whole population. Multivariate Cox regression analysis was used to determine the independent predictors of mortality.
Of the 1075 participants, 158 patients (14.7%) died over a mean follow-up of approximately 2.35 years. The crude mortality rate was significantly higher in the high RDW group (high RDW group, 22.4%; low RDW group 11%, p <0.001). From the adjusted model, the high RDW group was correlated with a hazard ratio of 2.19 for overall mortality as compared with the low RDW group (95% CI = 1.53-3.09, p<0.001). In addition, the high RDW group was also associated with an increased risk for cardiovascular disease (HR = 2.28, 95% CI = 1.14-4.25, p = 0.019) and infection (HR = 1.9, 95% CI = 1.15-3.14, p = 0.012)) related mortality in comparison with the low RDW group.
In stage 3-5 CKD patients, RDW was associated with patient mortality of all-cause, cardiovascular disease and infection. RDW should be considered as a clinical predictor for mortality when providing healthcare to CKD patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
ABSTRACT
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.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Recently, both red cell distribution width (RDW) and mean corpuscular volume (MCV) have been associated with unfavorable outcomes in several medical conditions. Therefore, we conducted this ...retrospective study of 1075 patients with stage 3-5 chronic kidney disease to investigate whether interactions between RDW and MCV influence the risk of mortality. These patients were divided into four groups: group A (n = 415), RDW ≤ 14.9% and MCV ≤ 91.6 fL; group B (n = 232), RDW > 14.9% and MCV ≤ 91.6 fL; group C (n = 307), RDW ≤ 14.9% and MCV > 91.6 fL; and group D (n = 121), RDW > 14.9% and MCV > 91.6 fL. The adjusted hazard ratio (HR) of all-cause mortality for group B versus group A was 1.44 (95% confidence interval CI, 1.14-2.12, p = 0.02), group C versus group A 2.14 (95% CI, 1.31-3.48, p = 0.002), and group D versus group A 5.06 (95% CI, 3.06-8.37, p < 0.001). There was a multiplicative interaction between MCV and RDW in predicting patient mortality. The use of RDW in conjunction with MCV may improve healthcare by identifying those at an increased risk for mortality compared with the use of either RDW or MCV alone.
Aim
In Taiwan, Changhua County residents were exposed to high heavy metal pollution and exhibited high heavy metal levels in blood and urine. We examined associations between heavy metals in ...residential soil and renal outcomes of residents with chronic kidney disease (CKD).
Method
From 1 January 2003 to 30 June 2015, we retrospectively identified CKD patients with an estimated glomerular filtration rate of <60 mL/min per 1.73 m2 at one tertiary care centre. We linked data displaying heavy metal concentrations from farm soil adjacent to the patients' residences to clinical outcomes. We included 2343 CKD patients (533 with progression to end‐stage renal disease ESRD and 1810 without. We followed these patients for 3.49 ± 2.27 years, until death or initiation of maintenance dialysis.
Results
There were high correlations among the concentrations of the eight metals: arsenic, cadmium, chromium, mercury, copper, lead, nickel, and zinc. After factor analysis, chromium, copper, nickel, and zinc were grouped and labelled Factor 1. High Factor 1 concentration near the patients' residences was associated with diagnoses of hypertension, diabetes mellitus, and cerebral vascular accident. Patients living in areas with high Factor 1 concentrations were at higher risk of ESRD. After multivariate adjustment adjusted hazard ratio: 1.08, 95% Confidence interval: 1.01–1.14, P = 0.02, only zinc and nickel were risk factors for progression to ESRD.
Conclusion
Patients with CKD, with long‐term exposure to soil‐based heavy metals, had rapid progression to ESRD. Groups of minerals from the same source of contamination may accumulate and lead to additional harm.
Summary at a Glance
In this study, researchers from Taiwan examined associations between heavy metal concentrations in soil and the clinical outcomes in a cohort of patients with CKD. Higher heavy metal concentrations in farms nearby patients' residences were associated with a higher risk of progression to end‐stage kidney disease. However, the mechanisms underlying this association are unclear and further study is required.
Methadone is a synthetic opioid used for the maintenance treatment (MMT) of heroin dependence. It primarily binds to the μ-opioid receptor (MOR; with its gene, namely OPRM1). Methadone is also an ...N-methyl-D-aspartate (NMDA) receptor antagonist. The role of NMDA receptor in the regulatory mechanisms of methadone dosage in heroin dependent patients is so far not clear. D-amino acid oxidase (DAO) is an important enzyme that indirectly activates the NMDA receptor through its effect on the D-serine level. To test the hypothesis that genetic polymorphisms in the DAO gene are associated with methadone treatment dose and responses, we selected four single nucleotide polymorphisms (SNPs) in DAO from the literature reports of the Taiwanese population. SNPs were genotyped in 344 MMT patients. In this study, we identified a functional SNP rs55944529 in the DAO gene that reveals a modest but significant association with the methadone dosage in the recessive model of analysis (P = 0.003) and plasma concentrations (P = 0.003) in MMT patients. However, it did not show association with plasma methadone concentration in multiple linear regression analysis. It is also associated with the methadone adverse reactions of dry mouth (P = 0.002), difficulty with urination (P = 0.0003) in the dominant model, and the withdrawal symptoms of yawning (P = 0.005) and gooseflesh skin (P = 0.004) in the recessive model. Our results suggest a role of the indirect regulatory mechanisms of the NMDA reporter, possibly via the DAO genetic variants, in the methadone dose and some adverse reactions in MMT patients.
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