الفهرس 
Acute kidney injuryOnly 14 pages are availabe for public view
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Abstract
What is already known on this subject? AND What does this study add? (Maximum 6 lines) “References are not needed” Acute kidney injury (AKI) is a common complication within critically ill patient . Recent studies have proposed many biomarkers for early detection of AKI , which may facilitate earlier diagnosis and proper management resulting in fewer complications and improved outcomes . This study aim to compare bet. Neutrophil Gelatenase-Associated lipocalin with traditional biomarkers to assess its accuracy in early prediction of AKI 1. INTRODUCTION/ REVIEW (Maximum 1000 words) “References are needed” Acute kidney injury (AKI) is defined as an absolute increase in serum creatinine (Scr)of more than or equal to 0.3 mg/dL , or a percentage increase in (Scr) of more than or equal to 50% (1.5-fold from baseline) , or a reduction in urine output to less than 0.5 mL/kg /hour for more than 6 hours, all within 48 hours after the completion of the procedure [1] . Acute kidney injury is a common complication within critically ill patients, affecting about 25% of all intensive care unit admissions . It is associated with significant morbidity, mortality, length of stay, and costs of care . [2] . Timely recognition of patients at risk for AKI, or with possible AKI , is essential to allow early intervention to minimize further renal injury, and may likely result in better outcomes than treating established AKI [3] .
Regarding the preoperative risk factors of AKI, advanced age is consistently associated with increased risk of AKI, regardless of the clinical setting [4] . Functional status of congestive heart failure, presence of peripheral vascular disease have all been associated with increased risk of AKI [2] . Other comorbid conditions such as diabetes, along with the extent of glycemic control are also independently associated with development of AKI after surgery [5] . The use of risk stratification indices should help in identification of high risk patients which is useful both for clinical practice and on-going research [6] . Future management in AKI will focus on detection and establishment of early biomarkers of kidney injury because the classical biomarkers, as serum creatinine and urinary output , have important limitations for detection of AKI as serum creatinine concentration is influenced by multiple factors including age and muscle mass . Also , serum creatinine level does not accurately reflect kidney function as an increase does not occur until 50% of the glomerular filtration rate (GFR) has been lost . What applies to serum creatinine also applies to urinary output , a clinically important but nevertheless non-specific marker of kidney function . Urinary output often persists until renal function ceases completely, and its interpretation is often confused by clinical conditions, such as hypovolemia, extended surgery, or the use of diuretics .
Thus, the fact that the classical biomarkers change late during the course of AKI development considerably restricts their suitability as a diagnostic tool [7] . Thus, A current challenge is that novel biomarkers are being compared to serum creatinine as the ‘gold standard’, and their implementation would allow for earlier prediction of AKI [8] . Biomarkers for ischemic injury could be monitored in the blood or urine . Most of the current interest has focused on a handful of promising biomarker : Neutrophil Gelatinase Associated Lipocalin (NGAL)[9] . It is a member of the lipocalin superfamily of carrier proteins, which are approximately 25 kDa in size . It is produced by activated neutrophils of proximal tubule it appears to be promising marker of AKI [10].
2. AIM/ OBJECTIVES (Maximum 300 words) The aim of this study is to evaluate the predictive capability of Neutrophil Gelatinase-Associated Lipocalin compared to traditional biomarkers in early prediction of acute kidney injury after abdominal surgery .
3. METHODOLOGY: Patients and Methods/ Subjects and Methods/ Material and Methods (Maximum 1000 words) “References may be needed”
Type of Study: Prospective Clinical Trial Study Setting : Ain- Shams University Hospitals and Tanta Cancer Institute
Study Period: September 2017- September 2018 Study Population: Patients undergo abdominal surgery who are at risk of acute kidney injury Inclusion Criteria: 1- Adult Patients ( > 18 years old ) . 2-Both sexes . 3-Patients with manifestations suggestive of acute kidney injury after abdominal surgery, which is defined as an absolute increase in Serum creatinine (Scr) of more than or equal to 0.3 mg/dL , or a percentage increase in SCr of more than or equal to 50% (1.5-fold from baseline) ,or a reduction in urine output to less than 0.5 mL/ kg / hour for more than 6 hours ; all within 48 hours after the completion of the procedure in intensive care unit . Exclusion Criteria: 1) Patient refusal . 2) Preexisting renal insufficiency; baseline serum creatinine >2 mg/dl , polycystic kidney, lupus nephritis or IgA nephropathy or any old history of renal disease . 3) Current use of known nephrotoxic drugs eg . Angiotensin – converting enzyme inhibitors , Aminoglycosides , NSAIDs . 4) Severe urinary tract infection ;diagnosed by the presence of pyuria > 50 pus cells/ high power field .
5) Pregnancy .
Sampling Method : Sample size was calculated using PASS 11.0 sample size calculation programe and based on a study carried out by ( Rafael et al , 2015 and Michael et al , 2011) who mentioned that accuracy of NAGL is 77.8 % to predict AKI ( sensitivity 80% and specificity 75% ), taken into consideration that incidence of AKI 32% . A total sample size of 62 ( which includes 20 subjects with disease ) achieves 80 % power to detect a change in sensitivity from 0.5 to 0.8 using a two sided binomial test and 92 % power to detect a change in specifity from 0.5 to 0.75 using a two sided binomial test . The target signifance level is 0.05 . The actual significance level achieved by the sensitivity test is 0.0414 and achieved by speficity test is 0.0436 . The prevelance of the disease is 0.32 .
Sample Size : 62 patients will enrolled in this study . Ethical Considerations : All patients will be consented after explaining the detailed study . moreover , their privacy will be maintained and no personal , medical data will be disclosed to third party . Study Tools : (1) Measurement of serum Neutrophil Gelatinase Associated – Lipocalin (NGAL) at preoperative and on admission of patient to intensive care unit post surgery , 2h , 6 h , 24h , 48h post ICU admission in comparison to traditional tools as serum creatinine , BUN , creatinine clearance which also will be recorded in the same manner .
(2) Full clinical evaluation including the medical history and the clinical examination , monitoring of vital signs , mean arterial pressure ,heart rate , urine output , temperature , conscious level from admission to ICU post operative and for 2 days . (3) Routine Laboratory Investigation ; including complete blood count (CBC) , urine analysis , liver functions and electrolytes . (4) Abdominal ultrasonography will be done preoperative , to rule out any preexisting kidney disease .
Study Procedures: Serial blood samples of NGAL will be analysed by ELISA . Specimen collection : 10 mL venous blood samples of selected patients and were collected in EDTA anticoagulant tubes . No special preparation is required . EDTA plasma will be stored at 2-8 °C if the assay is performed within 72 h . Otherwise, patient samples will be stored at -20 °C until measurement .
Study Interventions: This study includes measurement of serum Neutrophil Gelatinase Associated - Lipocalin by Elisa , at preoperative and on admission of patient to intensive care unit post surgery , 2h , 6 h , 24h , 48h post ICU admission , and record the pattern of rising of plasma neutrophil gelatinase - associated lipocalin ( pNGAL) , to asses to detect its accuracy in early prediction of acute kidney injury Statistical Analysis : All data will be collected and analyzed statically Statistical Package : Data will be analyzed using Statistical Program for Social Science (SPSS) version 20 .
4. REFERENCES (Maximum 20 references)
[1] -Kasiske BL, Wheeler DC. Kidney disease: improving global outcomes : and update. Nephrol Dial Transplant 2014;29 (4): 763e9.
[2] Thakar CV, Liangos O, Yared JP, et al. ARF after open-heart surgery: Influence of gender and race. Am J Kidney Dis. 2003;41:742–751. [3] Uchino S, Kellum JA, Bellomo R , et al. Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA 2005;294(7):813–8. [4] Waikar SS, Liu KD, Chertow GM . Diagnosis, epidemiology and outcomes of acute kidney injury. Clin J Am Soc Nephrol. 2008;3:844–861. [5] Thakar CV, Arrigain S, Worley S, et al. A clinical score to predict acute renal failure after cardiac surgery. J Am Soc Nephrol. 2005;16:162–168. [6] Waikar SS, BetenskyRA , Bonventre JV. Creatinine as the gold standard for kidney injury biomarker studies ?, Nephrol Dial Transplant, 2009, vol. 24 (3263- 3265) [7] Murray PT, Mehta RL, Shaw A et al , Potential use of biomarkers in acute kidney injury: report and summary of recommendations from the 10th Acute Dialysis Quality Initiative consensus conference. Kidney Int. (2014) 85:513– 521 [8] Vijayan A, Faubel S, Askenazi DJ et al , Clinical use of the urine biomarker for Acute kidney injury risk assessment . Am J Kidney Dis 2016 (68) :19–28 [9] Bagshaw SM, George C, Bellomo R. Changes in the incidence and outcome for early acute kidney injury in a cohort of Australian intensive Care Units. Crit Care 2007;11: R68 – 70 [10] Malyszko J: Biomarkers of acute kidney injury in different clinical settings .Kidney Blood Press Res 2010;33:368-382 .