Incidence of Contrast Induced Acute Kidney Injury, Its Risk Factors and In-Hospital Outcomes in Patients Undergoing Coronary Angiography and Angioplasty

Introduction Contrast-induced acute kidney injury (CI-AKI) is a serious complication of angiographic procedures with significant morbidity and mortality. We aimed to find the incidence, risk factors and outcomes of CI-AKI in patients who have undergone coronary angiography/angioplasty in a referral hospital in Nepal. MethodsIt was a descriptive observational study of consenting consecutive patients above 18 years undergoing coronary angiography/angioplasty at Manmohan Cardiothoracic Vascular and Transplant Centre, Nepal from July 2015 to September 2017. CI AKI was defined as an elevation of serum creatinine of >25% or ≥0.5 mg/dl (44 μmol/L) from baseline within 48 hour of exposure to contrast. Statistical analysis was performed using SPSS 18 software. Statistical analysis was completed using Student’s t-test, chi-square test and multivariable logistic regression analysis. ResultsOut of 240 patients, 156 (65%) were male, mean age was 60.36±11.29 years. Eighteen patients (7.5%) developed CI-AKI. Incidence of CI-AKI was 20% in patients with chronic kidney disease (CKD), 5.4% in diabetics, 13.6% in patients >70 years, 12.79 % in patients with anaemia and 12.3% in patients with prior contrast exposure. Multivariate logistic regression analysis found smoking and history of prior contrast exposure to be independent predictors for development of CI-AKI. Among patients with CI-AKI, one (5.88%) required dialysis and one (5.88%) died. ConclusionIncidence of CI-AKI after coronary angiography/angioplasty was 7.5%. Patients with prior contrast exposure and smoking were at significantly increased risk of CI-AKI; higher trend of CI-AKI was seen in patients with CKD, diabetes, elderly and anaemia.

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Elevated De Ritis Ratio as a Predictor for Acute Kidney Injury after Radical Retropubic Prostatectomy

Journal of Personalized Medicine ◽

10.3390/jpm11090836 ◽

2021 ◽

Vol 11 (9) ◽

pp. 836

Author(s):

Jun-Young Park ◽

Jihion Yu ◽

Jun Hyuk Hong ◽

Bumjin Lim ◽

Youngdo Kim ◽

...

Keyword(s):

Risk Factors ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Roc Curve ◽

Kidney Injury ◽

Radical Retropubic Prostatectomy ◽

Multivariable Logistic Regression Analysis ◽

Retropubic Prostatectomy

Acute kidney injury (AKI) is related to mortality and morbidity. The De Ritis ratio, calculated by dividing the aspartate aminotransferase by the alanine aminotransferase, is used as a prognostic indicator. We evaluated risk factors for AKI after radical retropubic prostatectomy (RRP). This retrospective study included patients who performed RRP. Multivariable logistic regression analysis and a receiver operating characteristic (ROC) curve analysis were conducted. Other postoperative outcomes were also evaluated. Among the 1415 patients, 77 (5.4%) had AKI postoperatively. The multivariable logistic regression analysis showed that estimated glomerular filtration rate, albumin level, and the De Ritis ratio at postoperative day 1 were risk factors for AKI. The area under the ROC curve of the De Ritis ratio at postoperative day 1 was 0.801 (cutoff = 1.2). Multivariable-adjusted analysis revealed that the De Ritis ratio at ≥1.2 was significantly related to AKI (odds ratio = 8.637, p < 0.001). Postoperative AKI was associated with longer hospitalization duration (11 ± 5 days vs. 10 ± 4 days, p = 0.002). These results collectively show that an elevated De Ritis ratio at postoperative day 1 is associated with AKI after RRP in patients with prostate cancer.

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Effects of Anesthetic Technique on the Occurrence of Acute Kidney Injury after Spine Surgery: A Retrospective Cohort Study

Journal of Clinical Medicine ◽

10.3390/jcm10235653 ◽

2021 ◽

Vol 10 (23) ◽

pp. 5653

Author(s):

Jiwon Han ◽

Ah-Young Oh ◽

Chang-Hoon Koo ◽

Yu Kyung Bae ◽

Yong-Tae Jeon

Keyword(s):

Risk Factors ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Propensity Score ◽

Propensity Score Matching ◽

Spine Surgery ◽

Logistic Regression Analysis ◽

Kidney Injury ◽

Volatile Anesthetics

The effects of anesthetics on acute kidney injury (AKI) after spine surgery have not been evaluated fully. This study compared propofol-based total intravenous anesthesia (TIVA) and volatile anesthetics in the development of AKI after spine surgery. This retrospective study reviewed patients who underwent spine surgery between 2015 and 2019. A logistic regression analysis was performed to identify risk factors for AKI. Additionally, after propensity score matching, the incidence of AKI was compared between TIVA and volatile groups. Of the 4473 patients, 709 were excluded and 3764 were included in the logistic regression. After propensity score matching, 766 patients from each group were compared, and we found that the incidence of AKI was significantly lower in the TIVA group (1% vs. 4.2%, p < 0.001). In the multivariate logistic regression analysis, the risk factors for postoperative AKI were male sex (OR 1.85, 95% CI 1.18–3.06), hypertension (OR 2.48, 95% CI 1.56–3.94), anemia (OR 2.66, 95% CI 1.76–4.04), and volatile anesthetics (OR 4.69, 95% CI 2.24–9.84). Compared with volatile anesthetics, TIVA is associated with a reduced risk of AKI for patients who have undergone spine surgery.

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Clinical profile and factors determining outcome of intramural very low birth weight babies in a tertiary care centre: a retrospective study

International Journal of Research in Medical Sciences ◽

10.18203/2320-6012.ijrms20170143 ◽

2017 ◽

Vol 5 (2) ◽

pp. 520

Author(s):

Devi Meenakshi K. ◽

Arasar Seeralar A. T. ◽

Srinivasan Padmanaban

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Birth Weight ◽

Low Birth Weight ◽

Logistic Regression Analysis ◽

Very Low Birth Weight ◽

Tertiary Care ◽

P Value ◽

Increased Risk

Background: Very low birth weight (VLBW) babies are at increased risk of a number of complications both immediate and late. Worldwide it has been observed that these babies contribute to a significant extent to neonatal mortality and morbidity. Aim of the study was to study the risk factors contributing to mortality in VLBW babies and to evaluate the morbidity pattern in these infants.Methods: A retrospective analysis of data retrieved from the case records of VLBW babies admitted in the NICU of Kilpauk Medical College between January 2015 to December 2015. Out of the 2360 intramural babies admitted during the study period, 99 babies were less than 1500 gms. The risk factors for these babies were analyzed for their association with the outcome. Data were statistically analyzed.Results: In present study, we found that sex of the baby, gestational age, obstetric score, birth asphyxia, pulmonary haemorrhage, ROP and presence of shock were found to be associated with increased mortality. By logistic regression analysis it was observed that birth weight of the baby (p value 0.002), duration of stay (p value 0.0006), presence of shock (p<0.0001), were the risk factors significantly associated with poor outcome.Conclusions: Among the maternal and neonatal factors analyzed in the study using logistic regression analysis, birth weight, duration of hospital stay and presence of shock were significantly related to poor outcome. Of these presence of shock was the single most important factor that predicted increased mortality.

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Late Acute Kidney Injury is a Poor Prognosis Sign in Severe Burns: A Retrospective Cohort Study

10.21203/rs.3.rs-111856/v1 ◽

2020 ◽

Author(s):

Bo You ◽

Zi Chen Yang ◽

Yu Long Zhang ◽

Yu Chen ◽

Yun Long Shi ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Poor Prognosis ◽

Multiple Logistic Regression Analysis ◽

Kidney Injury ◽

Occurrence Rate ◽

Severe Burns ◽

Epidemiological Characteristics

Abstract BackgroundAcute kidney injury (AKI) is a morbid complication and the main cause of multiple organ failure and death in severely burned patients. The objective of this study was to explore the epidemiological characteristics, the risk factors, and impact of both early and late AKIs, respectively.MethodsThis retrospective study was performed with prospectively collected data of severely burned patients from the Institute of Burn Research in Southwest Hospital during 2011-2017. AKI was diagnosed according to Kidney Disease Improving Global Outcomes (KDIGO) criteria (2012), and it was divided into early and late AKIs depending on its onset time (within the first 3 days or >3 days post burn). The baseline characteristics, clinical data, and outcomes of the three groups (early AKI, late AKI and non-AKI) were compared using logistic regression analysis. Mortality predictors of patients with AKI were assessed.ResultsA total of 637 patients were included in analysis. The incidence of AKI was 36.9% (early AKI 29.4%, late AKI 10.0%). The mortality of patients with AKI was 32.3% (early AKI 25.7%, late AKI 56.3%), and that of patients without AKI was 2.5%. AKI was independently associated with obviously increased mortality of severely burned patients [early AKI, OR = 12.98 (6.08-27.72); late AKI, OR = 34.02 (15.69-73.75)]. Multiple logistic regression analysis revealed that age, gender, total burn surface area (TBSA), full-thickness burns of TBSA, chronic comorbidities (hypertension or/and diabetes), hypovolemic shock of early burn, and tracheotomy were independent risk factors for both early and late AKIs. However, sepsis was only a risk factor for late AKI. Decompression escharotomy was a protective factor for both AKIs. ConclusionsAKI remains prevalent and is associated with high mortality in severely burned patients. Compared with early AKI, late AKI has a lower occurrence rate, but greater severity and worse prognosis，is a devastating complication. Late AKI is a poor prognosis sign in severe burns.

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Prediction of Acute Kidney Injury after Liver Transplantation: Machine Learning Approaches vs. Logistic Regression Model

Journal of Clinical Medicine ◽

10.3390/jcm7110428 ◽

2018 ◽

Vol 7 (11) ◽

pp. 428 ◽

Cited By ~ 31

Author(s):

Hyung-Chul Lee ◽

Soo Yoon ◽

Seong-Mi Yang ◽

Won Kim ◽

Ho-Geol Ryu ◽

...

Keyword(s):

Machine Learning ◽

Liver Transplantation ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Kidney Injury ◽

Gradient Boosting ◽

Learning Approaches ◽

Gradient Boosting Machine

Acute kidney injury (AKI) after liver transplantation has been reported to be associated with increased mortality. Recently, machine learning approaches were reported to have better predictive ability than the classic statistical analysis. We compared the performance of machine learning approaches with that of logistic regression analysis to predict AKI after liver transplantation. We reviewed 1211 patients and preoperative and intraoperative anesthesia and surgery-related variables were obtained. The primary outcome was postoperative AKI defined by acute kidney injury network criteria. The following machine learning techniques were used: decision tree, random forest, gradient boosting machine, support vector machine, naïve Bayes, multilayer perceptron, and deep belief networks. These techniques were compared with logistic regression analysis regarding the area under the receiver-operating characteristic curve (AUROC). AKI developed in 365 patients (30.1%). The performance in terms of AUROC was best in gradient boosting machine among all analyses to predict AKI of all stages (0.90, 95% confidence interval [CI] 0.86–0.93) or stage 2 or 3 AKI. The AUROC of logistic regression analysis was 0.61 (95% CI 0.56–0.66). Decision tree and random forest techniques showed moderate performance (AUROC 0.86 and 0.85, respectively). The AUROC of support the vector machine, naïve Bayes, neural network, and deep belief network was smaller than that of the other models. In our comparison of seven machine learning approaches with logistic regression analysis, the gradient boosting machine showed the best performance with the highest AUROC. An internet-based risk estimator was developed based on our model of gradient boosting. However, prospective studies are required to validate our results.

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Decreased eGFR Is Associated With Ischemic Stroke in Patients With Dilated Cardiomyopathy

Clinical and Applied Thrombosis/Hemostasis ◽

10.1177/1076029619866909 ◽

2019 ◽

Vol 25 ◽

pp. 107602961986690 ◽

Cited By ~ 1

Author(s):

Yuqing Deng ◽

Zhiqing Chen ◽

Lili Hu ◽

Zhenyan Xu ◽

Jinzhu Hu ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Ischemic Stroke ◽

Dilated Cardiomyopathy ◽

Logistic Regression Analysis ◽

Multivariate Logistic Regression Analysis ◽

Analysis Model ◽

Multivariate Logistic Regression ◽

Increased Risk

Dilated cardiomyopathy (DCM) is increasingly indicated as a cause of cardioembolic syndrome, in particular, cardioembolic ischemia stroke. However, the potential risk factors for stroke among DCM patients remain under investigated. DCM patients hospitalized from June 2011 to June 2016 were included. The cases were defined as the group of DCM patients with stroke compared with those without stroke. Clinical characteristic data were collected and compared between the two groups including demographic data, complicated diseases, echocardiography index, and laboratory parameters and estimated glomerular filtration rate (eGFR). A multivariate logistic regression analysis model adjusted by sex and age was used to explore the related risk factors for stroke in DCM patients. A total of 779 hospitalized patients with DCM were included. Of these, 55 (7.1%) had experienced a stroke. Significantly lower eGFR levels (68.03 ± 26.22 vs 79.88 ± 24.25 mL/min/1.73 m2, P = .001) and larger left atrial diameters (45.32 ± 7.79 vs 43.25 ± 7.11 mm, P = .04) were found in the group of patients having DCM with stroke compared to those without stroke. When the eGFR was categorized as eGFR >60, 30<eGFR≤ 60 and eGFR ≤ 30, there were more patients with 30<eGFR≤ 60 (30.9% vs 17.7%) and eGFR≤ 30 (9.1% vs 3.3%) in the ischemic stroke group ( P = 0.003). A multivariate logistic regression analysis model adjusted by sex and age showed that 30 <eGFR≤60 (odds ratio [OR]: 2.07, 95% confidence interval [CI]: [1.05-4.07], P = .035) and eGFR≤30 (OR: 4.04, 95% CI: [1.41-11.62], P = .009) were statistically associated with ischemic stroke in patients with DCM. It is concluded that decreased eGFR is significantly associated with an increased risk of ischemic stroke in patients with DCM.

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How Reliable Is Automated Urinalysis in Acute Kidney Injury?

Laboratory Medicine ◽

10.1093/labmed/lmaa069 ◽

2020 ◽

Author(s):

Vani Chandrashekar ◽

Anil Tarigopula ◽

Vikram Prabhakar

Keyword(s):

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Epithelial Cells ◽

Logistic Regression Analysis ◽

Blood Cells ◽

White Blood Cells ◽

Kidney Injury ◽

Tubular Epithelial Cells ◽

Spearman Test

Abstract Objective Examination of urine sediment is crucial in acute kidney injury (AKI). In such renal injury, tubular epithelial cells, epithelial cell casts, and dysmorphic red cells may provide clues to etiology. The aim of this study was to compare automated urinalysis findings with manual microscopic analysis in AKI. Methods Samples from patients diagnosed with AKI and control patients were included in the study. Red blood cells, white blood cells, renal tubular epithelial cells/small round cells, casts, and pathologic (path) cast counts obtained microscopically and by a UF1000i cytometer were compared by Spearman test. Logistic regression analysis was used to assess the ability to predict AKI from parameters obtained from the UF1000i. Results There was poor correlation between manual and automated analysis in AKI. None of the parameters could predict AKI using logistic regression analysis. However, the increment in the automated path cast count increased the odds of AKI 93 times. Conclusion Automated urinalysis parameters are poor predictors of AKI, and there is no agreement with manual microscopy.

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Impaired T Lymphocyte Subsets Early Predict Acute Kidney Injury in Sepsis Patients

10.21203/rs.3.rs-612917/v1 ◽

2021 ◽

Author(s):

Guanglan Li ◽

Yu Zhang ◽

Ganyuan He ◽

Wenke Hao ◽

Wenxue Hu

Keyword(s):

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

T Lymphocyte ◽

Logistic Regression Analysis ◽

Lymphocyte Subsets ◽

Kidney Injury ◽

High Morbidity ◽

T Helper ◽

T Lymphocyte Subsets

Abstract Objective: Acute kidney injury (AKI) is a frequent complication of sepsis patients and is associated with high morbidity and mortality. Early recognition of sepsis-associated AKI (SA-AKI) is crucial to provide supportive treatment and improve prognosis. Thus, the objective is to analyze the early discriminative predictive information regarding T lymphocyte subsets of SA-AKI.Methods: We evaluated the relationships of T lymphocyte subsets and clinical parameters of sepsis patients, and assessed their potential roles in SA-AKI diagnosis. The following T lymphocyte subsets were studied: total T lymphocyte (CD3+), helper T lymphocyte (T helper, CD3+CD4+), cytotoxic T lymphocyte (CTL, CD3+CD8+), totally activated T lymphocyte (CD3+HLADR+), early activated T lymphocyte (CD4+CD69+, CD8+CD69+), regulatory T lymphocyte (Treg, CD4+CD25+, CD8+CD25+).Results: A total of 171 patients with sepsis were enrolled. The incidence of AKI was 80.1%. The percentages of total T lymphocyte, CTL, and totally activated T lymphocyte of SA-AKI patients were lower than those of sepsis patients without AKI (61.95±19.65 % vs 68.80±18.57 %, 19.95±17.22 % vs 26.48±18.31 %, 19.00±14.21 % vs 30.88±28.86 %, respectively, P<0.05). There were no significant differences in the percentages of T helper, early activated T lymphocyte, and Tregs between SA-AKI group and non-SA-AKI group. Univariate logistic regression analysis showed that percentages of total T lymphocyte, CTL, and totally activated T lymphocyte were protective factors for SA-AKI. Multivariate logistic regression analysis revealed that percentage of totally activated T lymphocyte had a negative association with SA-AKI independently (OR: 0.952, 95% CI: 0.926-0.978, P=0.000). Moreover, ROC analysis showed that total T lymphocyte, CTL, and totally activated T lymphocyte had discriminatory abilities, with areas under the curve (AUC) value of 0.638, 0.615, and 0.661, respectively (P<0.05). Conclusions: Impaired total T lymphocyte, CTL, and totally activated T lymphocyte could contribute to early diagnosis for SA-AKI.

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Risk factors for acute kidney injury and mortality in high risk patients undergoing cardiac surgery

PLoS ONE ◽

10.1371/journal.pone.0252209 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0252209

Author(s):

Giuseppe Filiberto Serraino ◽

Michele Provenzano ◽

Federica Jiritano ◽

Ashour Michael ◽

Nicola Ielapi ◽

...

Keyword(s):

Risk Factors ◽

Acute Kidney Injury ◽

Logistic Regression ◽

Regression Analysis ◽

Cardiac Surgery ◽

Blood Glucose ◽

Kidney Injury ◽

Glucose Levels ◽

Blood Glucose Levels ◽

Risk Patients

Background Acute Kidney Injury (AKI) represents a clinical condition with poor prognosis. The incidence of AKI in hospitalized patients was about 22–57%. Patients undergoing cardiac surgery (CS) are particularly exposed to AKI because of the related oxidative stress, inflammation and ischemia-reperfusion damage. Hence, the risk profile of patients undergoing CS who develop AKI and who are consequently at increased mortality risk deserves further investigation. Methods We designed a retrospective study examining consecutive patients undergoing any type of open-heart surgery from January to December 2018. Patients with a history of AKI were excluded. AKI was diagnosed according to KDIGO criteria. Univariate associations between clinical variables and AKI were tested using logistic regression analysis. Variable thresholds maximizing the association with AKI were measured with the Youden index. Multivariable logistic regression analysis was performed to assess predictors of AKI through backward selection. Mortality risk factors were assessed through the Cox proportional hazard model. Results We studied 158 patients (mean age 51.2±9.7 years) of which 74.7% were males. Types of procedures performed were: isolated coronary artery bypass (CABG, 50.6%), valve (28.5%), aortic (3.2%) and combined (17.7%) surgery. Overall, incidence of AKI was 34.2%. At multivariable analysis, young age (p = 0.016), low blood glucose levels (p = 0.028), estimated Glomerular Filtration Rate (p = 0.007), pH (p = 0.008), type of intervention (p = 0.031), prolonged extracorporeal circulation (ECC, p = 0.028) and cross-clamp (p = 0.021) times were associated with AKI. The threshold for detecting AKI were 91 and 51 minutes for ECC and cross-clamp times, respectively. At survival analysis, the presence of AKI, prolonged ECC and cross-clamp times, and low blood glucose levels forecasted mortality. Conclusions AKI is common among CS patients and associates with shortened life-expectancy. Several pre-operative and intra-operative predictors are associated with AKI and future mortality. Future studies, aiming at improving prognosis in high-risk patients, by a stricter control of these factors, are awaited.

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Abdominal obesity as a risk factor for stroke in Abuja, Nigeria

International Journal of Research in Medical Sciences ◽

10.18203/2320-6012.ijrms20213394 ◽

2021 ◽

Vol 9 (9) ◽

pp. 2573

Author(s):

Gerald A. Onwuegbuzie ◽

Peter Alabi ◽

Fatima Abdulai

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Risk Factor ◽

Abdominal Obesity ◽

Logistic Regression Analysis ◽

Statistical Significance ◽

Lifestyle Changes ◽

Health Concern ◽

Increased Risk

Background: Obesity in Africa has remained a public health concern, which is been fueled by urbanization and its attendant lifestyle changes which includes less energy demanding jobs, sedentary lifestyle and adopting detrimental western eating habits. There are well established risk factors for stroke, however the association of obesity with that of stroke is less clear.Methods: This study was designed to determine whether abdominal obesity is independently associated with an increased risk of ischaemic stroke. It is a case control study of 113 patients in which structured questionnaire was administered to consecutive patients admitted into the medical wards. The controls were matched for age and sex from a database with participants of the population-based cohort study. Statistical analysis of data was performed using SAS software (SAS Institute) 9.4.Results: In the study 85% of the patients had hypertension, 50.5% had hypercholesterolemia and 33.6% had diabetes. The BMI was normal for most of the cases (23.3% vs. 76.7% p<0.0001) while the WHR was increased for most of the cases (70.9% vs. 29.1% p<0.0001). The statistical significance shows that WHR was more sensitive in assessing obesity than BMI. The logistic regression analysis, in model 1 unadjusted and model 2 adjusted for sex and age, BMI showed a positive association with risk of stroke (OR 1.10; 95% CI, 1.04-1.17; p=0.002) this association lost its significance in model 3 after adjusting for diabetes, hypertension and hypercholesterolemia (OR 1.04; 95% CI, 0.96-1.13; p=0.3751). The results of logistic regression analysis for WHR for model 1, model 2 and model 3 did not show any significance before and after adjustment.Conclusions: Abdominal obesity may increase the risk of ischemic stroke through conventional vascular risk factors, but not as an independent risk factor.

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