Effect of Rosuvastatin on Acute Kidney Injury in Sepsis-Associated Acute Respiratory Distress Syndrome.

Background:Acute kidney injury (AKI) commonly occurs in patients with sepsis and acute respiratory distress syndrome (ARDS). Objective:To investigate whether statin treatment is protective against AKI in sepsis-associated ARDS. Design:Secondary analysis of data from Statins for Acutely Injured Lungs in Sepsis (SAILS), a randomized controlled trial that tested the impact of rosuvastatin therapy on mortality in patients with sepsis-associated ARDS. Setting:44 hospitals in the National Heart, Lung, and Blood Institute ARDS Clinical Trials Network. Patients:644 of 745 participants in SAILS who had available baseline serum creatinine data and who were not on chronic dialysis. Measurements:Our primary outcome was AKI defined using the Kidney Disease Improving Global Outcomes creatinine criteria. Randomization to rosuvastatin vs placebo was the primary predictor. Additional covariates include demographics, ARDS etiology, and severity of illness. Methods:We used multivariable logistic regression to analyze AKI outcomes in 511 individuals without AKI at randomization, and 93 with stage 1 AKI at randomization. Results:Among individuals without AKI at randomization, rosuvastatin treatment did not change the risk of AKI (adjusted odds ratio: 0.99, 95% confidence interval [CI]: 0.67-1.44). Among those with preexisting stage 1 AKI, rosuvastatin treatment was associated with an increased risk of worsening AKI (adjusted odds ratio: 3.06, 95% CI: 1.14-8.22). When serum creatinine was adjusted for cumulative fluid balance among those with preexisting stage 1 AKI, rosuvastatin was no longer associated worsening AKI (adjusted odds ratio: 1.85, 95% CI: 0.70-4.84). Limitations:Sample size, lack of urine output data, and prehospitalization baseline creatinine. Conclusion:Treatment with rosuvastatin in patients with sepsis-associated ARDS did not protect against de novo AKI or worsening of preexisting AKI

Magnitude of the Difference Between Clinic and Ambulatory Blood Pressures and Risk of Adverse Outcomes in Patients With Chronic Kidney Disease.

Background Obtaining 24-hour ambulatory blood pressure ( BP ) is recommended for the detection of masked or white-coat hypertension. Our objective was to determine whether the magnitude of the difference between ambulatory and clinic BP s has prognostic implications. Methods and Results We included 610 participants of the AASK (African American Study of Kidney Disease and Hypertension) Cohort Study who had clinic and ambulatory BPs performed in close proximity in time. We used Cox models to determine the association between the absolute systolic BP ( SBP ) difference between clinic and awake ambulatory BPs (primary predictor) and death and end-stage renal disease. Of 610 AASK Cohort Study participants, 200 (32.8%) died during a median follow-up of 9.9 years; 178 (29.2%) developed end-stage renal disease. There was a U-shaped association between the clinic and ambulatory SBP difference with risk of death, but not end-stage renal disease. A 5- to <10-mm Hg higher clinic versus awake SBP (white-coat effect) was associated with a trend toward higher (adjusted) mortality risk (adjusted hazard ratio, 1.84; 95% CI, 0.94-3.56) compared with a 0- to <5-mm Hg clinic-awake SBP difference (reference group). A ≥10-mm Hg clinic-awake SBP difference was associated with even higher mortality risk (adjusted hazard ratio, 2.31; 95% CI, 1.27-4.22). A ≥-5-mm Hg clinic-awake SBP difference was also associated with higher mortality (adjusted hazard ratio, 1.82; 95% CI, 1.05-3.15) compared with the reference group. Conclusions A U-shaped association exists between the magnitude of the difference between clinic and ambulatory SBP and mortality. Higher clinic versus ambulatory BPs (as in white-coat effect) may be associated with higher risk of death in black patients with chronic kidney disease

Research-based versus clinical serum creatinine measurements and the association of acute kidney injury with subsequent kidney function: findings from the Chronic Renal Insufficiency Cohort study.

Background:Observational studies relying on clinically obtained data have shown that acute kidney injury (AKI) is linked to accelerated chronic kidney disease (CKD) progression. However, prior reports lacked uniform collection of important confounders such as proteinuria and pre-AKI kidney function trajectory, and may be susceptible to ascertainment bias, as patients may be more likely to undergo kidney function testing after AKI. Methods:We studied 444 adults with CKD who participated in the prospective Chronic Renal Insufficiency Cohort (CRIC) Study and were concurrent members of a large integrated healthcare delivery system. We estimated glomerular filtration rate (eGFR) trajectories using serum creatinine measurements from (i) the CRIC research protocol (yearly) and (ii) routine clinical care. We used linear mixed effects models to evaluate the associations of AKI with acute absolute change in eGFR and post-AKI eGFR slope, and explored whether these varied by source of creatinine results. Models were adjusted for demographic characteristics, diabetes status and albuminuria. Results:During median follow-up of 8.5 years, mean rate of eGFR loss was -0.31 mL/min/1.73 m2/year overall, and 73 individuals experienced AKI (55% Stage 1). A significant interaction existed between AKI and source of serum creatinine for acute absolute change in eGFR level after discharge; in contrast, AKI was independently associated with a faster rate of eGFR decline (mean additional loss of -0.67 mL/min/1.73 m2/year), which was not impacted by source of serum creatinine. Conclusions:AKI is independently associated with subsequent steeper eGFR decline regardless of the serum creatinine source used, but the strength of association is smaller than observed in prior studies after taking into account key confounders such as pre-AKI eGFR slope and albuminuria

Fake News Detection with Heterogeneous Transformer

The dissemination of fake news on social networks has drawn public need for effective and efficient fake news detection methods. Generally, fake news on social networks is multi-modal and has various connections with other entities such as users and posts. The heterogeneity in both news content and the relationship with other entities in social networks brings challenges to designing a model that comprehensively captures the local multi-modal semantics of entities in social networks and the global structural representation of the propagation patterns, so as to classify fake news effectively and accurately. In this paper, we propose a novel Transformer-based model: HetTransformer to solve the fake news detection problem on social networks, which utilises the encoder-decoder structure of Transformer to capture the structural information of news propagation patterns. We first capture the local heterogeneous semantics of news, post, and user entities in social networks. Then, we apply Transformer to capture the global structural representation of the propagation patterns in social networks for fake news detection. Experiments on three real-world datasets demonstrate that our model is able to outperform the state-of-the-art baselines in fake news detection

Predicting adverse outcomes following catheter ablation treatment for atrial fibrillation

Objective: To develop prognostic survival models for predicting adverse outcomes after catheter ablation treatment for non-valvular atrial fibrillation (AF). Methods: We used a linked dataset including hospital administrative data, prescription medicine claims, emergency department presentations, and death registrations of patients in New South Wales, Australia. The cohort included patients who received catheter ablation for AF. Traditional and deep survival models were trained to predict major bleeding events and a composite of heart failure, stroke, cardiac arrest, and death. Results: Out of a total of 3285 patients in the cohort, 177 (5.3%) experienced the composite outcomeheart failure, stroke, cardiac arrest, deathand 167 (5.1%) experienced major bleeding events after catheter ablation treatment. Models predicting the composite outcome had high risk discrimination accuracy, with the best model having a concordance index > 0.79 at the evaluated time horizons. Models for predicting major bleeding events had poor risk discrimination performance, with all models having a concordance index < 0.66. The most impactful features for the models predicting higher risk were comorbidities indicative of poor health, older age, and therapies commonly used in sicker patients to treat heart failure and AF. Conclusions: Diagnosis and medication history did not contain sufficient information for precise risk prediction of experiencing major bleeding events. The models for predicting the composite outcome have the potential to enable clinicians to identify and manage high-risk patients following catheter ablation proactively. Future research is needed to validate the usefulness of these models in clinical practice.Comment: Under journal revie