Literature DB >> 29926539

Body Mass Index as a Predictor of Acute Kidney Injury in Critically Ill Patients: A Retrospective Single-Center Study.

Sunmi Ju1, Tae Won Lee2, Jung Wan Yoo1, Seung Jun Lee1, Yu Ji Cho1, Yi Yeong Jeong1, Jong Deog Lee1, Ju Young Kim2, Gi Dong Lee2, Ho Cheol Kim3.   

Abstract

BACKGROUND: The aim of this study was to examine the influence of body mass index (BMI) on the development of acute kidney injury (AKI) in critically ill patients in intensive care unit (ICU).
METHODS: Data of patients admitted to medical ICU from December 2011 to May 2014 were retrospectively analyzed. Patients were classified into three groups according to their BMI: underweight (<18.5 kg/m²), normal (18.5-24.9 kg/m²), and overweight (≥25 kg/m²). The incidence of AKI was compared among these groups and factors associated with the development of AKI were analyzed. AKI was defined according to the Risk, Injury, Failure, Loss of kidney function, and End-stage (RIFLE) kidney disease criteria.
RESULTS: A total of 468 patients were analyzed. Their mean BMI was 21.5±3.9 kg/m², including 102 (21.8%) underweight, 286 (61.1%) normal-weight, and 80 (17.1%) overweight patients. Overall, AKI occurred in 82 (17.5%) patients. The overweight group had significantly (p<0.001) higher incidence of AKI (36.3%) than the underweight (9.8%) or normal group (15.0%). In addition, BMI was significantly higher in patients with AKI than that in those without AKI (23.4±4.2 vs. 21.1±3.7, p<0.001). Multivariate analysis showed that BMI was significantly associated with the development of AKI (odds ratio, 1.893; 95% confidence interval, 1.224-2.927).
CONCLUSION: BMI may be associated with the development of AKI in critically ill patients. Copyright©2018. The Korean Academy of Tuberculosis and Respiratory Diseases.

Entities:  

Keywords:  Acute Kidney Injury; Body Mass Index; Intensive Care Unit

Year:  2018        PMID: 29926539      PMCID: PMC6148097          DOI: 10.4046/trd.2017.0081

Source DB:  PubMed          Journal:  Tuberc Respir Dis (Seoul)        ISSN: 1738-3536


Introduction

Body mass index (BMI), calculated from the height and weight of a patient, is a simple and useful index for obesity1. BMI has been reported to be an important prognostic factor for many medical conditions. For example, in chronic obstructive pulmonary disease, chronic renal failure, and cancer, mortality is increased in underweight patients23, whereas in many metabolic diseases, including hypertension, diabetes mellitus, and dyslipidemia, mortality is commonly increased in overweight patients4. Moreover, the relationship between BMI and all-cause mortality in the general population is known to be ‘J’- or ‘U’-shaped5. Many studies have examined the usefulness of BMI as a prognostic factor in critically ill patients with differing results. Mortality appears to be increased in morbidly obese patients6, while no relationship between mortality and obesity was observed in another prospective study7. Moreover, recent studies have shown that mortality in the intensive care unit (ICU) is lower in obese patients than in those who are underweight789. The development of acute kidney injury (AKI) in ICU patients is a frequent complication that can affect the prognosis1011. Therefore, the development of AKI in these patients and the associated risk factors have been extensively studied11. However, only a few studies have assessed the relationship between BMI and AKI in critically ill patients12131415. Accordingly, the purpose of this study was to assess the influence of BMI on the development of AKI in critically ill patients.

Materials and Methods

1. Study design and settings

All critical-ill patients who were admitted to the medical intensive care unit (MICU) at Gyeongsang National University Hospital (hospital total, 890 beds; MICU, 13 to 15 beds) between December 2011 and May 2014 were retrospectively studied. The admission was decided by attending physician according to general criteria of ICU admission16. Before admission, consents were received from patients' family or caregiver. Patients were excluded if they were admitted for acute coronary syndrome, overdose, acute cerebrovascular disease, and chronic renal failure or were <18 years of age. This study was approved by the institutional review board of Gyeongsang National University Changwon Hospital (GNUCH-2018-05-014). Informed consent was waived due to the retrospective nature of the study.

2. Data collection and definitions

Demographic information, past medical history, and reason for ICU admission were collected for each patient on admission and discharge from the MICU according to the MICU registry at our institution. The Acute Physiology and Chronic Health Evaluation (APACHE) II score and Sequential Organ Failure Assessment (SOFA) score, measures of severity of illness and predictors of mortality17, were also calculated. Height was recorded based on previous medical records or the ICU admission measurement. Body weight was measured automatically using a calibrated bed scale (VersaCare Bed; Hill-Rom, Batesville, IN, USA) at ICU admission. BMI was calculated as body weight (kg)/height (m2). The patients were classified into three groups based on the degree of obesity as defined by the World Health Organization and the National Heart, Lung and Blood Institute of the National Institutes of Health as follows: underweight (BMI, <18.5 kg/m2), normal (BMI, 18.5–24.9 kg/m2), and overweight (BMI, ≥25.0 kg/m2) groups18. AKI was defined by the Risk, Injury, Failure, Loss of kidney function, and End-stage (RIFLE) kidney disease criteria using the creatinine level, glomerular filtration rate, and urine output19. The number of days the patient required mechanical ventilation, length of stay (LOS) in the ICU and hospital, and mortality in the ICU and hospital were assessed.

3. Statistical analysis

Continuous variables are reported as the mean±standard deviation. Categorical variables are described as number (%). Differences between groups were compared using analysis of variance, Student's t test, or chi-square test as appropriate. Univariate and multivariate logistic regression analysis was performed to examine the relation between BMI and the factors associated with the development of AKI. Statistical significance was defined as a p-value of <0.05. All data were analyzed using SPSS version 22.0 for Windows (IBM Corp., Armonk, NY, USA).

Results

1. Patient characteristics

A total of 468 patients were analyzed. The average age was 68.6±13.9 years, with a male-to-female ratio of 2:1. The mean BMI was 21.5±3.9 kg/m2 (range, 12.2–39.6 kg/m2). The mean APACHE II and SOFA scores were 18.8±8.8 and 7.9±4.4, respectively. The average LOS was 10.0±18.1 days in the ICU and 25.7±35.8 days in the hospital. The ICU morality rate was 35.8%, with an overall hospital mortality rate of 44.7%. AKI developed in 82 patients (17.1%).

2. Comparison of clinical characteristics according to the BMI groups

The baseline characteristics of the patients according to BMI group are summarized in Table 1. Of the 468 patients, 102 (21.8%) were underweight, 286 (61.1%) were normal-weight, and 80 (17.1%) were overweight. The mean age of the underweight group was 71.3±12.7 years, which was significantly older than that of the overweight patients (64.9±13.8 years, p=0.008). For the underweight, normal-weight, and overweight groups, the mean BMI values were 16.5±1.5, 21.6±1.8, and 27.7±2.5 kg/m2, respectively. The overweight group had a significantly higher incidence of AKI (36.3%) than the underweight (9.8%) and normal groups (15.0%) (p<0.001 for all). In addition, the overweight group had a higher incidence of hypertension, liver cirrhosis, and chronic kidney disease (p<0.05 for all). The diagnoses on admission included septic shock, acute respiratory distress syndrome (ARDS), gastrointestinal bleeding, with septic shock and ARDS being the main reasons for admission to the MICU. The established causes of septic shock and ARDS were described in the Table 1. Compared to the underweight (27.5%) and normal (33.9%) groups, the overweight group had a significantly higher incidence of septic shock (46.2%) as the reason for ICU admission (p=0.010). The APACHE II and SOFA scores of the overweight group were also significantly higher than those of the other two groups (p=0.002 and p<0.001, respectively). Regarding the clinical outcomes, the LOS in the ICU and hospital tended to be shorter when the BMI was increased. The highest mortality was found in the overweight group, and the lowest mortality was found in the normal weight group. However, there were no significant differences among the three BMI groups regarding the ICU LOS, hospital LOS, ICU death rate, and in-hospital death rate (p>0.05 for all).
Table 1

Baseline characteristics of patients by BMI groups

CharacteristicTotalUnderweight (BMI <18.5)Normal (BMI 18.5–24.9)Overweight (BMI ≥25.0)p-value
No. of patients48610228680
Sex (male/female)306/16262/40197/8947/330.132
Age, yr68.6±13.971.3±12.768.6±14.164.9±13.80.008
Age >80 yr31 (30.4)62 (21.7)13 (16.3)0.020
BMI, kg/m221.5±3.916.5±1.521.6±1.827.7±2.5<0.001
AKI82 (17.1)10 (9.8)29 (36.3)<0.001
Comorbidities
 DM155 (33.1)27 (26.5)94 (33.0)34 (42.5)0.074
 HTN192 (41.0)34 (33.3)44 (55.0)0.011
 CVD89 (19.0)25 (24.5)47 (16.4)17 (21.3)0.174
 LC45 (9.6)3 (2.9)29 (10.1)13 (16.3)0.009
 CKD69 (14.7)8 (7.8)42 (14.7)19 (23.8)0.011
 Malignancy59 (12.6)15 (14.7)32 (11.2)12 (15.0)0.510
 Heart failure23 (4.9)6 (5.9)15 (5.2)2 (2.5)0.530
 Alcoholism70 (15)10 (9.8)46 (16.1)14 (17.5)0.510
Reason for admission
 Severe sepsis/Septic shock162 (34.6)28 (27.5)97 (33.9)37 (46.2)0.010
  Lower respiratory tract infection84 (17.9)15 (14.7)56 (19.6)13 (16.3)
  Gastrointestinal tract infection10 (2.1)0 (0)5 (1.7)5 (6.3)
  Urinary tract infection8 (1.7)3 (2.9)4 (1.4)1 (1.3)
 Hepatobiliary tract infection5 (1.1)1 (1.0)2 (0.7)2 (2.5)
 Intra-abdominal infection0 (0)1 (0.3)1 (1.3)
 Wound infection2 (0.4)1 (1.0)1 (0.3)0 (0)
 Mediastinal infection1 (0.2)0 (0)0 (0)1 (1.3)
 Unknown8 (7.8)28 (9.8)14 (17.5)
 ARDS73 (15.6)12 (11.8)44 (15.4)17 (21.3)0.213
  Pulmonary cause60 (12.8)8 (7.8)39 (13.6)13 (16.3)
  Extrapulmonary cause4 (3.9)5 (1.7)4 (5.0)
APACHE II score18.8±8.816.7±7.518.8±8.821.4±10.00.002
SOFA score7.9±4.46.6±4.27.9±4.29.4±5.0<0.001
Extubation failure115 (24.6)34 (33.3)63 (22.0)18 (22.5)0.067
Transfusion requirement36 (35.3.7)104 (36.4)39 (48.8)0.103
Renal replacement therapy113 (24.1)19 (18.6)66 (23.1)28 (35)0.030
ECMO8 (1.7)0 (0)3 (1)5 (6.3)0.011
Use of systemic steroid before ICU admission87 (18.6)27 (26.5)50 (17.5)10 (12.5)0.041
MV duration, day9.6±16.910.7±11.89.8±19.87.4±10.50.412
ICU LOS, day10.0±18.111.7±13.410.3±21.06.9±9.80.184
Hospital LOS, day28.3±39.226.6±37.519.2±22.20.186
ICU death180 (38.5)41 (40.2)35 (43.8)0.448
Hospital death209 (44.7)48 (47.1)121 (42.3)40 (50.0)0.406

Values are presented as mean±SD or number (%).

AKI: acute kidney injury; BMI: body mass index; DM: diabetes mellitus; HTN: hypertension; CVD: cardiovascular disease; LC: liver cirrhosis; CKD: chronic kidney disease; ARDS: acute respiratory distress syndrome; APACHE: Acute Physiology and Chronic Health Evaluation; SOFA: Sequential Organ Failure Assessment; ECMO: extracorporeal membrane oxygenation; ICU: intensive care unit; MV: mechanical ventilation; LOS: length of stay.

3. Comparison of clinical characteristics according to development of AKI

The BMI was significantly higher in patients with AKI than in those without it (23.4±4.2 kg/m2 vs. 21.1±3.7 kg/m2, p<0.05). Patients with AKI had a higher incidence of liver cirrhosis, diabetes, chronic kidney disease, and alcoholism. Moreover, these patients showed a higher incidence of septic shock and ARDS than patients without AKI at the time of admission. Extubation failure, need for transfusion, use of renal replacement therapy, and application of extracorporeal membrane oxygenation were also more common in patients with AKI than in those without it. Regarding the clinical outcomes, the LOS in the ICU and hospital were significantly longer for patients with AKI than for those without AKI (p<0.05). The ICU and hospital mortality rates were also significantly higher in patients with AKI than in those without it (74.4% vs. 30.8% for ICU mortality; 74.4% vs. 38.3% for hospital mortality; p<0.05 for both) (Table 2).
Table 2

Baseline characteristics according to development of AKI

CharacteristicAKINo AKIp-value
No. of patients82386
Sex (male/female)54/28252/1340.105
Age, yr66.3±13.969.1±13.80.105
Age >80 yr14 (17.1)98 (23.8)0.185
BMI, kg/m223.4±4.221.1±3.7<0.001
Comorbidity
 DM36 (43.9)119 (30.8)0.028
 HTN38 (46.3)154 (39.9)0.323
 CVD7 (8.5)50 (13.0)0.352
 LC17 (20.7)28 (7.3)0.001
 CKD8 (7.8)42 (14.7)0.011
 Malignancy13 (15.9)46 (11.9)0.359
 Heart failure6 (7.3)17 (4.4)0.264
 Alcoholism21(25.6)49 (12.7)0.006
Reason for admission
 Septic shock43 (53.8)119 (31.2)<0.001
  Lower respiratory tract infection17 (20.7)67 (17.4)
  Gastrointestinal tract infection7 (8.5)3 (3.7)
  Urinary tract infection3 (3.7)5 (3.7)
 Hepatobiliary tract infection2 (2.4)3 (3.7)
 Intra-abdominal infection2 (2.4)0 (0)
 Wound infection0 (0)2 (0.5)
 Mediastinal infection0 (0)1 (0.3)
 Unknown12 (14.6)38 (9.8)
 ARDS20 (24.4)53 (13.7)0.019
  Pulmonary cause15 (18.3)45 (11.7)
  Extrapulmonary cause5 (6.1)8 (2.1)
RIFLE criteria
 Injury63 (76.8)
 Failure19 (23.2)
APACHE II score23.5±8.617.8±8.6<0.001
SOFA score10.5±4.47.3±4.2<0.001
Extubation failure33 (40.2)82 (21.2)0.001
Transfusion requirement58 (70.7)121 (31.3)0.000
Renal replacement therapy40 (48.8)73 (18.9)0.000
ECMO5 (6.1)3 (0.8)0.003
Use of systemic steroid before ICU admission14 (17.1)73 (18.9)0.750
MV duration, day6.9±7.010.2±18.40.009
ICU LOS, day7.7±8.510.5±19.50.040
Hospital LOS, day19.5±22.027.1±38.00.082
ICU death61 (74.4)119 (30.8)0.000
Hospital death61 (74.4)148 (38.3)0.000

BMI: body mass index; AKI: acute kidney injury; DM: diabetes mellitus; HTN: hypertension; CVD: cardiovascular disease; LC: liver cirrhosis; CKD: chronic kidney disease; ARDS: acute respiratory distress syndrome; RIFLE: Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease APACHE: Acute Physiology and Chronic Health Evaluation; SOFA: Sequential Organ Failure Assessment; ECMO: extracorporeal membrane oxygenation; ICU: intensive care unit; MV: mechanical ventilation; LOS: length of stay.

4. Risk factors for development of AKI

Finally, we assessed the risk factors for AKI in the ICU by logistic regression analyses. In univariate analysis, BMI, diabetes, chronic kidney disease, liver cirrhosis, alcoholism, septic shock, ARDS, SOFA score, and APACHE II score were found to be risk factors for AKI. However, BMI groups were found to be significantly associated with a risk of developing AKI in the multivariate analysis (odds ratio, 1.893; 95% confidence interval, 1.224–2.927; p=0.004) (Table 3).
Table 3

Univariate and multivariate logistic regression analysis for factor associated with development of AKI

Univariate analysisMultivariate analysis
β±SEtUnadjusted odds ratio (95% CI)p-valueβ±SEtUnadjusted odds ratio (95% CI)p-value
Age >80 yr−0.419±0.3171.7460.658 (0.354–1.224)0.186−0.086±0.3510.0600.917 (0.461–1.825)0.917
BMI, 3 groups0.911±0.20819.0972.486 (1.652–3.740)<0.0010.638±0.2228.2231.893 (1.224–2.927)0.004
 DM0.559±0.2485.0711.749 (1.075–2.846)0.0240.454±0.2752.7221.575 (0.918–2.701)0.099
 LC1.207±0.33612.9283.344 (1.732–6.457)0.0000.415±0.4160.9991.515 (0.671–3.421)0.317
 CKD0.752±0.2588.4532.210 (1.278–3.519)0.0040.223±0.2960.5671.250 (0.699–3.421)0.451
Alcoholism−0.086±0.2968.5010.422 (0.237–0.754)0.004−0.040±0.3731.1710.668 (0.321–1.387)0.279
Septic shock0.470±0.12613.9711.600 (1.250–2.047)0.0000.202±0.1441.9631.224 (0.337–1.431)0.161
 ARDS0.706±0.2975.6712.027 (1.133–3.625)0.0170.624±0.3253.6831.866 (0.987–3.350)0.055
 SOFA0.161±0.02931.6721.175 (1.111–1.242)0.0000.077±0.0471.6341.080 (0.985–1.183)0.201

p-values less than 0.05 were considered as significant.

AKI: acute kidney injury; SE: standard error; CI: confidence interval; BMI: body mass index; DM: diabetes mellitus; LC: liver cirrhosis; CKD: chronic kidney disease; ARDS: acute respiratory distress syndrome; SOFA: Sequential Organ Failure Assessment.

Discussion

This study revealed that BMI was an independent risk factor for the development of AKI in critically ill patients. Although BMI has been shown to be a useful prognostic marker in critically ill patients, the relationship between BMI and the development of AKI has not been extensively investigated in the literature12131415. However, several reports investigated the association between BMI and the development of AKI in critically ill patients. Soto et al.13 retrospectively analyzed risk factors for AKI in 751 patients with ARDS. The study showed that the prevalence of AKI increased significantly with increasing weight. In addition, there was a 2-fold increase in the risk of AKI in obese patients compared to those of normal weight. The study also reported that the risk could not be completely explained by the severity of illness. A study of 390 patients with sepsis also showed that BMI was higher in patients with AKI than in patients without AKI15. Another study showed the incidence of AKI in patients requiring renal replacement therapy went up as BMI increased12. Further, several studies have reported that AKI develops more frequently in patients with a high BMI after cardiac and abdominal surgery2021. These findings, along with our study, showed that a high BMI was a risk factor for the development of AKI in critically ill patients. The association between high BMI and risk of AKI development could be explained by several mechanisms. First, obesity causes some hemodynamic changes in the glomerulus such as glomerular hyperperfusion and hyperfiltration due to impaired natriuresis-associated activation of the renin and angiotensin system. Glomerular hyperperfusion and hyperfiltration may be result in glomerular injury. These changes have been demonstrated in an experimental animal model of obesity and in obese patients2223. Second, obesity can increase the hemodynamic and metabolic load on each individual glomerulus, which results in a low number of functional nephrons in obese patients24. In turn, a low number of functional nephrons was related to glomerular hypertrophy and glomerulosclerosis due to increased capillary pressure on the remaining functional nephrons24. Third, adipocytes may be as a production site for activated inflammatory cytokines and oxidative stress in obese patients25. Increased oxidative stress can contribute to detrimental changes in the glomeruli26. Taken together, in obese type II diabetes mellitus patients, reduction of body weight has been shown to be associated with significant decreases in proteinuria. This finding support that harmful influence of obesity to kidney injury27. Liver cirrhosis and diabetes were more common in patients with AKI than in patients without AKI in our study. In patients with liver cirrhosis, the development of AKI has been shown a relatively frequent problem, especially in critically ill patients, and it has a great impact on prognosis in these patients28. Although diabetes and the development of AKI was not studied in critically ill patients, a recent report showed that, in patients with sepsis, underlying diabetes was not associated with the development of AKI29. Further study is needed to evaluate diabetes as a risk factor for AKI in critically ill patients. Extubation failure was more common in patients with AKI than in patients without AKI in our study. Extubation failure is usually associated with a longer duration of mechanical ventilation and ICU stay30. It may increase the risk of several complications in the ICU. As a result, ICU patients with extubation failure may be more vulnerable to developing AKI. Previous reports have showed that the time to extubation may be associated with development of AKI in postcardiac surgery patients3132. These reports suggest that the duration of positive pressure ventilation in critically ill patients is an important risk factor for AKI development. In fact, mechanical ventilation itself has been shown to induce proinflammatory reactions and extrapulmonary end organ injury in animal models of mechanical ventilation3334. Conversely, AKI may be associated with a higher rate of extubation failure and delayed weaning. Although there are conflicting results between BMI and mortality in ICU patients. It is generally reported that patients with Low BMI have a higher mortality rate than those with normal BMI. A large-population prospective study conducted in Korea showed that low BMI patients has a higher mortality than in patient with normal and higher BMI35. In this study, the mortality rate of patients with low BMI was slightly higher (36% vs. 40%) than the patients with normal BMI although there was no statistically significant in two group. There are some limitations to this study. First, enrolled patients came from the medical ICU of a single tertiary hospital. The risk factors for AKI in the MICU may differ from those in surgical ICUs. For example, in surgical ICU patients, postoperative AKI due to decreased intravascular volume is a relatively common problem. By contrast, the risk factors for AKI in MICU patients usually include the presence of infection and medications (e.g., antibiotics, vasopressors). Second, the characteristics of the enrolled patients were heterogeneous. Hence, the risk for AKI may be quite different and it depend on the underlying disease and the reason for ICU admission. Therefore, the risk factors for AKI are assessed in a homogenous group of patients such as sepsis or acute lung injury. In conclusion, compared to low or normal BMI, a high BMI was found to be associated with a higher risk of developing AKI in critically ill patients treated in the MICU in this study. This result suggests that BMI may be associated with the development of AKI in critically ill patients.
  35 in total

1.  Body mass index. An additional prognostic factor in ICU patients.

Authors:  Maité Garrouste-Orgeas; Gilles Troché; Elie Azoulay; Antoine Caubel; Arnaud de Lassence; Christine Cheval; Laurent Montesino; Marie Thuong; François Vincent; Yves Cohen; Jean-François Timsit
Journal:  Intensive Care Med       Date:  2004-02-06       Impact factor: 17.440

2.  Obesity and oxidative stress predict AKI after cardiac surgery.

Authors:  Frederic T Billings; Mias Pretorius; Jonathan S Schildcrout; Nathaniel D Mercaldo; John G Byrne; T Alp Ikizler; Nancy J Brown
Journal:  J Am Soc Nephrol       Date:  2012-05-24       Impact factor: 10.121

3.  Body mass index and acute kidney injury in the acute respiratory distress syndrome.

Authors:  Graciela J Soto; Angela J Frank; David C Christiani; Michelle Ng Gong
Journal:  Crit Care Med       Date:  2012-09       Impact factor: 7.598

4.  Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults.

Authors:  Eugenia E Calle; Carmen Rodriguez; Kimberly Walker-Thurmond; Michael J Thun
Journal:  N Engl J Med       Date:  2003-04-24       Impact factor: 91.245

5.  Influence of overweight on ICU mortality: a prospective study.

Authors:  Cyril Goulenok; Mehran Monchi; Jean-Daniel Chiche; Jean-Paul Mira; Jean-François Dhainaut; Alain Cariou
Journal:  Chest       Date:  2004-04       Impact factor: 9.410

6.  Impact of obesity in mechanically ventilated patients: a prospective study.

Authors:  Jean-Pierre Frat; Valérie Gissot; Stéphanie Ragot; Arnaud Desachy; Isabelle Runge; Christine Lebert; René Robert
Journal:  Intensive Care Med       Date:  2008-08-01       Impact factor: 17.440

Review 7.  From big fat cells to high blood pressure: a pathway to obesity-associated hypertension.

Authors:  Zdenka Pausova
Journal:  Curr Opin Nephrol Hypertens       Date:  2006-03       Impact factor: 2.894

Review 8.  Obesity and perioperative acute kidney injury: a focused review.

Authors:  Manish Suneja; Avinash B Kumar
Journal:  J Crit Care       Date:  2014-03-05       Impact factor: 3.425

9.  Acute Kidney Injury in Severe Sepsis and Septic Shock in Patients with and without Diabetes Mellitus: A Multicenter Study.

Authors:  Marion Venot; Lise Weis; Christophe Clec'h; Michael Darmon; Bernard Allaouchiche; Dany Goldgran-Tolédano; Maité Garrouste-Orgeas; Christophe Adrie; Jean-François Timsit; Elie Azoulay
Journal:  PLoS One       Date:  2015-05-28       Impact factor: 3.240

10.  Body mass index and mortality in Korean intensive care units: a prospective multicenter cohort study.

Authors:  So Yeon Lim; Won-Il Choi; Kyeongman Jeon; Eliseo Guallar; Younsuck Koh; Chae-Man Lim; Shin Ok Koh; Sungwon Na; Young-Joo Lee; Seok Chan Kim; Ick Hee Kim; Je Hyeong Kim; Jae Yeol Kim; Jaemin Lim; Chin Kook Rhee; Sunghoon Park; Ho Cheol Kim; Jin Hwa Lee; Jisook Park; Gee Young Suh
Journal:  PLoS One       Date:  2014-04-18       Impact factor: 3.240

View more
  5 in total

1.  Machine learning for the prediction of acute kidney injury in patients with sepsis.

Authors:  Suru Yue; Shasha Li; Xueying Huang; Jie Liu; Xuefei Hou; Yumei Zhao; Dongdong Niu; Yufeng Wang; Wenkai Tan; Jiayuan Wu
Journal:  J Transl Med       Date:  2022-05-13       Impact factor: 8.440

2.  Higher body mass index is not a protective risk factor for 28-days mortality in critically ill patients with acute kidney injury undergoing continuous renal replacement therapy.

Authors:  Hai Wang; Yu Shi; Zheng-Hai Bai; Jun-Hua Lv; Jiang-Li Sun; Hong-Hong Pei; Zheng-Liang Zhang
Journal:  Ren Fail       Date:  2019-11       Impact factor: 2.606

3.  The effect of body mass index on the development of acute kidney injury and mortality in intensive care unit: is obesity paradox valid?

Authors:  Mehmet Süleyman Sabaz; Sinan Aşar; Gökhan Sertçakacılar; Nagihan Sabaz; Zafer Çukurova; Gülsüm Oya Hergünsel
Journal:  Ren Fail       Date:  2021-12       Impact factor: 2.606

4.  Characteristics of risk factors for acute kidney injury among inpatients administered sulfamethoxazole/trimethoprim: a retrospective observational study.

Authors:  Yuki Shimizu; Toshinori Hirai; Yukari Ogawa; Chihiro Yamada; Emiko Kobayashi
Journal:  J Pharm Health Care Sci       Date:  2022-08-01

5.  Risk factors for acute kidney injury after Stanford type A aortic dissection repair surgery: a systematic review and meta-analysis.

Authors:  Lei Wang; Guodong Zhong; Xiaochai Lv; Yi Dong; Yanting Hou; Xiaofu Dai; Liangwan Chen
Journal:  Ren Fail       Date:  2022-12       Impact factor: 3.222

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.