Capillary Leak Index as a Prognostic Indicator for Post-Operative Abdominal Sepsis in Critically Ill Patients
Conditions: Intra-Abdominal Infections, Intestinal Obstruction, Appendicitis Acute, Perforated Viscus
Sponsor: Ain Shams University

 
 
Capillary leak Index as a Prognostic 
Indicator for Post-Operative Abdominal 
Sepsis in Critically ill Patients 
Protocol with Statistical Analysis Plan of Thesis 
NCT Number: NCT06901544 
Submitted For Fulfillment Of Master Degree In 
General Intensive Care. 
By 
Osama Ahmed Ahmed Salem Khalil 
(MBBCH) 
Faculty of Medicine, Ain Shams University 
 
Under supervision of 
Prof. Dr. HANAA ABD ALLAH ELGENDY 
Academic Position: Professor 
Department: Anesthesia, Intensive Care and Pain Management 
 
Ass.Prof.Dr. AMR MOHAMMED HILAL 
Academic Position: Assistant professor 
Department: Anesthesia, Intensive Care and Pain Management 
Dr. AHMED MONIER AHMED 
Academic Position: Lecturer 
Department: Anesthesia, Intensive Care and Pain Management 
 
Faculty of Medicine 
Ain Shams University 
11/8/2025 last update 
 

What is already known on this subject? AND 
What does this study add? 
Intra-abdominal infections are a major cause of morbidity and mortality in hospital 
settings worldwide. However, data from most published clinical trials under- estimate 
the true mortality risk for several reasons. (Meng et al., 2024). 
Major surgery may induce an inflammatory response, which results in an increased 
level of C-reactive protein (CRP) and represented in albumin loss to the extravascular 
area due to increased capillary permeability. Our study will be done to evaluate the 
association between capillary leak index (CLI) and intensive care unit related 
mortality in patients underwent major abdominal surgery (Susanti et al., 2021). 
1. INTRODUCTION 
Sepsis has been recognized as a life-threatening organ dysfunction caused by a 
dysregulated host response to infection (Clements, 2021). Considerable advances have 
since been made into the pathobiology (changes in organ function, morphology, cell 
biology, 
biochemistry, 
immunology, 
and 
circulation), 
management, 
and 
epidemiology of sepsis, suggesting the need for continuous research (JAMA, 2016). 
Peritonitis can be classified by the anatomical integrity of the abdominal cavity. 
Primary peritonitis is associated with undamaged intra-abdominal cavity organs. It is 
also known as spontaneous bacterial peritonitis and is treated without surgical 
intervention. The source of infection is often hard to establish and is usually found 
occurring in infants and cirrhotic patients (Mureșan et al., 2018). 
Secondary peritonitis is an infection of the peritoneal cavity after hollow viscus 
perforation, anastomotic leak, ischemic necrosis, or other injuries of the 
gastrointestinal tract (Montravers et al., 2015). Tertiary peritonitis is defined as a serious 
recurrent or persistent intra-abdominal infection after the successful control of 
secondary peritonitis. Irrespective of the cause, several measures are available and 
accepted as improving the survival rate, the most important being the early 
recognition of intra-abdominal infection. Efforts to achieve fluid balance should be 
initiated immediately to replace any intravascular insufficiency. Vasoactive agents 

may be necessary to augment and assist fluid restoration (Vincent JL and De Backer 2013).  
The treatment strategy for peritonitis primarily aims at the stabilization of possible 
organ dysfunction by routine intensive care medicine. Low risk secondary peritonitis 
(localized peritonitis), Ampicillin/Sulbactam or Carbapenem can be used as a 
monotherapy, however in combination therapy 2nd generation Cephalosporin + 
Metronidazole or 3rd generation Cephalosporin + Metronidazole can be used (Sartelli 
et al., 2016). High risk Secondary peritonitis Piperacillin/Tazobactam or Carbapenem or 
Tigecycline can be used as a monotherapy. A combination therapy 4th generation 
Cephalosporin + Metronidazole are usually used. Tertiary peritonitis antifungal 
therapy in high-risk patients and empirical therapy should cover the probable micro 
flora and should be changed according to the culture results (Morrissey et al., 2013). 
Capillary leak syndrome (CLS) refers to a syndrome of deranged fluid homeostasis, 
often observed in critically ill patients, CLS is frequently defined by excessive fluid 
shift from the intravascular to the extravascular space, resulting in intravascular 
hypovolemia, extravascular edema formation, and hypo perfusion necessitating 
further fluid resuscitation. In health, fluid exchange between intravascular and 
extravascular spaces is vital for maintaining the body’s homeostasis. However, 
disturbances in this delicate equilibrium, can lead to the clinical picture of CLS (Saravi 
et al., 2023).  
CLI is measured by dividing CRP level by albumin level. Systematic response to 
tissue injury, including major surgery, is marked by increased pro inflammatory 
cytokines, which promotes CRP production and capillary leakage. If the injury still 
exists, inflammatory process will continue (Susanti et al., 2021). 
Our study will be done to evaluate the association between capillary leak index (CLI) 
and intensive care unit (ICU) related mortality in patients underwent major abdominal 
surgery. 
2. AIM/OBJECTIVES 
In this study we are going to evaluate the “CLI” as an early prognostic indicator for 
post-operative abdominal sepsis in critically ill patients. 
 

3. METHODOLOGY:  
Patients and Methods 
➢ Type of Study: Prospective Cohort study.             
➢ Study Setting: Surgical intensive Care Unit, Ain Shams University Hospitals. 
➢ Study Period: 6 months. 
➢ Inclusion criteria:  
• Age: ≥18 years old presented with Post-operative intra-abdominal sepsis due 
to secondary peritonitis in the form of fever, increase TLC more than 12x10³ 
and increase procalcetonin > 0.5 microgram per liter. 
• Sex: Both sexes. 
• Post-Operative secondary peritonitis eg. Perforated viscus and abdominal 
abscess. 
• Estimated length of ICU stays ≥48 hrs. 
➢ Exclusion criteria: 
• Patient refusal. 
• Advanced Liver diseases According New MELD score ≥ 20 )Kamath et al.,2001) 
• Renal diseases (Moderate decrease in GFR 30-59 ml/min/1.73m²--Severe decrease 
in GFR 15-29 ml/min/1.73m²--Kidney failure less than 15 ml/min/1.73m² or on 
Hemodialysis). 
• Pregnancy. 
• Primary peritonitis. 
• Tertiary peritonitis 
• Mortality within first 48hrs of ICU admission. 
• Advanced malignancy ( Stage III localized malignancy with spreading lymph nodes Stage IV  
spreading to Other parts of the body such as to the liver, lungs and bones) 
Sampling Method: 
Simple randomization.  
Sample Size: Using the PASS 15 program for sample size calculation, reviewing 
results from the previous study (Susanti et al, 2021) showed that the mortality rate among 

the study group was 14.5%11/67) and, that the CLI a t day three is a good predictor 
for mortality with ROC-AUC=0.892, based on these findings and after 15% 
adjustment for dropout rate a sample size of at least 50 patient achieves 95% power 
to detect a difference of 0.3920 between t h e a r e a under t h e ROC curve (AUC) 
under the null hypothesis of 0.5000 and an AUC under the alternative hypothesis of 
0.8920 using a two-sided z-test at a significance level of 0.050. The data are 
continuous responses. 
Ethical considerations: 
➢ An informed consent according to rules of ethical committee in Ain Shams 
University will be obtained from the patients or guardians after being informed 
about the research procedure and any potential risks suspected. 
➢ All patients’ data are highly confidential. 
Study Tools: 
After an informed consent, the enrolled patients will be subjected to: 
➢ Full clinical assessment and history taking. 
➢ Laboratory investigations including random blood sugar, arterial blood gases 
(ABG), complete blood count (CBC), serum albumin and C re-active Protein 
“CRP”, liver function test, Kidney function test and procalcitonin. 
➢ Imaging studies including Pelvi-abdominal U/S and Pelvi-abdominal multi-
slice (CT) with or without contrast. 
➢ Other investigations include Electrocardiogram (ECG), Echocardiography. 
Study Procedures: 
All patients will be subjected to the following in the first post-operative day in the 
ICU: 
1. Full history taking including 
➢ Demographic Data: there include age, sex and BMI. 
➢ Medical history: this includes diabetes mellitus (DM), cardiopulmonary diseases, 
renal or hepatic diseases. 
➢ APACHE II Score. 

➢ SOFA Score. 
2. Patients will be divided into two groups according to CLI  
➢ Group I: Low CLI < 85.55 
➢ Group II: High CLI > 85.55 (PALACIOS et al., 2018). 
3. History of previous operations.  
4.   Drug history & special habits.  
5. Complain of the patient:  
•  Abdominal pain: This included onset, course, duration, site, radiation. 
6. Associated symptoms: e.g.: Vomiting, change in bowel habits (constipation or 
diarrhea), Fever, tachycardia and tachypnea. 
7. Investigations:  
➢ Laboratory investigations: Complete blood count (CBC). Liver function tests 
(LFT). Renal Function test (RFT). Coagulation profile. Daily assessment.  
➢ Specific laboratory investigations: CRP and Serum albumin Daily assessment.  
➢  Radiological investigations: Plain abdomen X-ray erect x-ray, Pelvi-abdominal 
ultrasonography, Computed Tomography (CT) abdomen as needed. 
8. Management of sepsis and septic shock and will be done according to surviving 
sepsis campaign guidelines 2021. 
9. Continuous monitoring of Temp, NIBP, IBP, HR, RR, intra-abdominal 
pressure, sPO2, UOP and GCS.  
Sampling: 
Blood sampling: About 5.0 ml venous blood sample was taken from each patient. 2.0 
ml blood was put into vacutainer Ethylene-diaminetetra-acetic acid (EDTA) tube for 
CBC. The reminder of blood sample was put into plain tube for serum separation and 
estimation of LFT, RFT, The CRP level was measured using ABX Pentra 400 
(HORIBA, Germany), whereas the albumin level was measured using HumaStar 80 
(HUMAN, Germany).Reference values for serum albumin is 35 to 55 g/l and for CRP 
is less than 6 mg/dl CLI will be calculated as CRP divided by serum albumin and 
multiplied by 100 in the first day post-operative and daily for 5 days with a cut-off 

point < 85.55 (PALACIOS et al., 2018). 
Measurements 
Primary outcome measure: 
Correlation between CLI and 28 days Mortality. 
Secondary outcomes measure: 
➢ Mechanical Ventilation days. 
➢ Incidence of organ failure. 
➢ Length of ICU stays. 
 Statistical Analysis: 
All data will be recorded, tabulated, analyzed and statistically compared between 
patients to identify any significant difference between them 
The finding will be discussed with regard to the achievement of the aim, their 
significance and their comparison with other available data in medical literature. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

4. REFERENCES 
1. Ade Susanti1,2 , Mayang Indah Lestari et al. High capillary leak index is associated with 
increased risk of ICU-related mortality after major abdominal surgery Crit Care Shock 2021) 
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2. Clements TW, Tolonen M, Ball CG, Kirkpatrick AW. Secondary peritonitis and intra-
abdominal sepsis: an increasingly global disease in search of better systemic therapies. 
Scandinavian Journal of Surgery. 2021 Jun;110(2):139-49. 
3. JAMA, The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) 
Feb 23;315(8):801–810. doi: 10.1001/jama.2016.0287 
4. Kamath PS, Wiesner RH, Malinchoc M, et al. A model to predict survival in patients with 
end stage liver disease. Hepatology (Baltimore, Md). 2001;33(2):464-470. 
5. Montravers P, Dufour G, Guglielminotti J, et al. Dynamic changes of microbial flora and 
therapeutic consequences in persistent peritonitis. Crit Care. 2015;19:7. 
6. Morrissey I, Hackel M, Badal R, Bouchillon S, Hawser S, Biedenbach D. A review of ten 
years of the Study for Monitoring Antimicrobial Resistance Trends (SMART) from 2002 to 
2011. Pharmaceuticals (Basel). 2013;6:1335–46. 
7. Mureșan MG, Balmoș IA, Badea I, Santini A. Abdominal sepsis: an update. The Journal of 
Critical Care Medicine. 2018 Oct 1;4(4):120-5. 
8. Meng R, Guan X, Sun L, Fei Z, Li Y, Luo M, et al The efficacy and safety of eravacycline 
compared with current clinically common antibiotics in the treatment of adults with complicated 
intra-abdominal infections: a bayesian network meta-analysis. Front Med (Lausanne). 
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shock Med. Crít. (Col. Mex. Med. Crít.) vol.32 no.3 Mexico City May/Jun. 2018. 
10. Saravi B, Goebel U, Hassenzahl LO, Jung C, David S, Feldheiser A, Stopfkuchen-Evans 
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Statistical analysis Plan 
NCT Number: NCT06901544 
Statistical analysis was done by SPSS v27 (IBM©, Armonk, NY, USA). Shapiro-Wilks 
test and histograms were used to evaluate the normality of the distribution of data. Quantitative 
parametric data were presented as mean and standard deviation (SD) and were analyzed by 
unpaired student t-test. Quantitative non-parametric data were presented as the median and 
interquartile range (IQR) and were analyzed by Mann Whitney-test. Qualitative variables were 
presented as frequency and percentage (%) and analyzed using the Chi-square test. A two-tailed 
P value < 0.05 was considered statistically significant. 
Evaluation of Diagnostic Performance: 
a) Diagnostic sensitivity: It measures the incidence of true positive results in patients’ groups. (TP 
)/(TP+FN )×100.Where: 
TP (true positive): number of diseased patients accurately classified by the test and FN (false 
negative): number of diseased patients accurately misclassified by the test. 
b) Diagnostic specificity: It measures the incidence of true negative results in a non-diseased group. 
(TN)/(TN+FP )×100. Where: 
TN (true negative): number of non-diseased subjects correctly classified by the test FP (false 
positive): number of non-diseased patients misclassified by the test. 
c) Positive Predictive value (PPV): It is the percentage of true positive results among total positive 
results. (TP)/(TP+FP )×100. 
d) Negative Predictive value (NPV): It is the percentage of true negative results among total negative 
results. (TN)/(TN+FN)×100. 
e) Receiver Operating Characteristic curve (ROC-curve) analysis:  
The overall diagnostic performance of each test was assessed by ROC curve analysis, a curve that 
extends from the lower left corner to the upper left corner then to the upper right corner is considered 
a perfect test. The area under the curve (AUC) evaluates the overall test performance (where the area 
under the curve >50% denotes acceptable performance and area about 100% is the best performance 

for the test). A value below 0.5 indicates a very poor model. A value of 0.5 means that the model is 
no better than predicting an outcome than random chance. Values over 0.7 indicate a good model. 
Values over 0.8 indicate a strong model. A value of 1 means that the model perfectly predicts those 
group members who will experience a certain outcome and those who will not.