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      Dynamic nomogram for predicting acute kidney injury in patients with acute ischemic stroke: A retrospective study

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          Abstract

          Background

          This study sought to develop and validate a dynamic nomogram chart to assess the risk of acute kidney injury (AKI) in patients with acute ischemic stroke (AIS).

          Methods

          These data were drawn from the Medical Information Mart for Intensive Care III (MIMIC-III) database, which collects 47 clinical indicators of patients after admission to the hospital. The primary outcome indicator was the occurrence of AKI within 48 h of intensive care unit (ICU) admission. Independent risk factors for AKI were screened from the training set using univariate and multifactorial logistic regression analyses. Multiple logistic regression models were developed, and nomograms were plotted and validated in an internal validation set. Based on the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) to estimate the performance of this nomogram.

          Results

          Nomogram indicators include blood urea nitrogen (BUN), creatinine, red blood cell distribution width (RDW), heart rate (HR), Oxford Acute Severity of Illness Score (OASIS), the history of congestive heart failure (CHF), the use of vancomycin, contrast agent, and mannitol. The predictive model displayed well discrimination with the area under the ROC curve values of 0.8529 and 0.8598 for the training set and the validator, respectively. Calibration curves revealed favorable concordance between the actual and predicted incidence of AKI ( p > 0.05). DCA indicates the excellent net clinical benefit of nomogram in predicting AKI.

          Conclusion

          In summary, we explored the incidence of AKI in patients with AIS during ICU stay and developed a predictive model to help clinical decision-making.

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          Most cited references47

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          Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

          Summary Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding Bill & Melinda Gates Foundation.
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            MIMIC-III, a freely accessible critical care database

            MIMIC-III (‘Medical Information Mart for Intensive Care’) is a large, single-center database comprising information relating to patients admitted to critical care units at a large tertiary care hospital. Data includes vital signs, medications, laboratory measurements, observations and notes charted by care providers, fluid balance, procedure codes, diagnostic codes, imaging reports, hospital length of stay, survival data, and more. The database supports applications including academic and industrial research, quality improvement initiatives, and higher education coursework.
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              World incidence of AKI: a meta-analysis.

              The burden of AKI around the globe has not been systematically examined. A systematic review (2004-2012) of large cohort studies was conducted to estimate the world incidence of AKI and its stages of severity and associated mortality, and to describe geographic variations according to countries, regions, and their economies. AKI definitions were reclassified according to the Kidney Disease Improving Global Outcomes (KDIGO) staging system. Random-effects model meta-analyses and meta-regressions were used to generate summary estimates and explore sources of heterogeneity. There were 312 studies identified (n=49,147,878) , primarily in hospital settings. Most studies originated from North America, Northern Europe, and Eastern Asia, from high-income countries, and from nations that spent ≥5% of the gross domestic product on total health expenditure. Among the 154 studies (n=3,585,911) that adopted a KDIGO-equivalent AKI definition, the pooled incidence rates of AKI were 21.6% in adults (95% confidence interval [95% CI], 19.3 to 24.1) and 33.7% in children (95% CI, 26.9 to 41.3). The pooled AKI-associated mortality rates were 23.9% in adults (95% CI, 22.1 to 25.7) and 13.8% in children (95% CI, 8.8 to 21.0). The AKI-associated mortality rate declined over time, and was inversely related to income of countries and percentage of gross domestic product spent on total health expenditure. Using the KDIGO definition, 1 in 5 adults and 1 in 3 children worldwide experience AKI during a hospital episode of care. This analysis provides a platform to raise awareness of AKI with the public, government officials, and health care professionals.
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                13 September 2022
                2022
                : 13
                : 987684
                Affiliations
                [1] 1Department of Neurosurgery, Hangzhou First People's Hospital, School of Medicine, Zhejiang University , Hangzhou, China
                [2] 2Department of Neurosurgery, The Second Affiliated Hospital, School of Medicine, Zhejiang University , Hangzhou, China
                [3] 3Department of Neurosurgery, The Fourth Affiliated Hospital, School of Medicine, Zhejiang University , Yiwu, China
                Author notes

                Edited by: Yujie Chen, Army Medical University, China

                Reviewed by: Chao Zhang, Army Medical University, China; Qiwen Deng, Nanjing Medical University, China

                *Correspondence: Wenhua Yu ywh699@ 123456126.com

                This article was submitted to Neurological Biomarkers, a section of the journal Frontiers in Neurology

                Article
                10.3389/fneur.2022.987684
                9513523
                a96ddd6b-7af0-4f4e-9c87-67128d28f446
                Copyright © 2022 Zhu, Fu, Jin, Xu, Wei, Cai and Yu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 July 2022
                : 22 August 2022
                Page count
                Figures: 5, Tables: 4, Equations: 0, References: 47, Pages: 13, Words: 7315
                Categories
                Neurology
                Original Research

                Neurology
                acute ischemic stroke,acute kidney injury,nomogram,mimic-iii database,retrospective study

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