"Colorectal Leakage App" for Early Detection of Anastomotic Leakage After Colorectal Surgeries

Colorectal cancer ranks third among oncological diseases in Kazakhstan, both in men and women. Anastomotic leakage (AL) following colorectal surgeries is one of the most serious complications arising from colorectal surgical interventions. This condition is characterized by increased mortality and significant deterioration in the quality of life of patients. Additionally, the presence of AL after anterior resections for rectal cancer is associated with an increased risk of local disease recurrence. The frequency of AL varies between 2 and 19%, depending on risk factors, AL definition, and the level of anastomosis. Given the high likelihood and severe consequences of AL, a relevant task is its early detection and effective treatment.

Clinical signs of AL traditionally include fever, tachycardia, pain syndrome, purulent or fecal discharge through drainage, and dynamic bowel obstruction. These signs, combined with other clinical data, are integrated into a diagnostic-specific indicator known as the Dutch Leakage Score (DLS). This indicator is used as a standardized postoperative monitoring protocol for patients suspected of having AL, aiming to minimize delays in detecting this complication and, consequently, reduce early postoperative mortality.

In this prospective observational study, we aim to assess the effectiveness of the mobile application "Colorectal Leakage App" in the early detection of anastomotic leakage (AL) after colorectal surgeries. The study will be conducted at the National Research Oncology Center (NROC) in Astana, Kazakhstan, over one year. The primary goal is to evaluate the diagnostic effectiveness of the application in detecting AL after colorectal surgeries.

It is important to note that there is currently no up-to-date data on the number of colorectal cancer surgeries performed, and information on the frequency of AL after colorectal surgeries in the population of Kazakhstan is also lacking. Previous studies have shown that the effectiveness of the DLS algorithm is directly proportional to the frequency of AL. Therefore, it is assumed that the application of DLS may demonstrate different results in the conditions of Kazakhstan, which we also plan to measure through the "Colorectal Leakage App" mobile application.

1. Design of the study:

   Prospective observational study, where the "Colorectal Leakage App" mobile application will be implemented in daily postoperative monitoring. Additionally, an assessment of the diagnostic effectiveness of this application will be conducted.

2. Instruments and equipment:

The "Colorectal Leakage App" is a mobile application that, based on an algorithm, provides an assessment of the risk of Anastomotic Leakage (AL) in patients after colorectal surgeries. The algorithm is built on the standardized postoperative monitoring protocol called "Dutch Leakage Score". After calculating the scores, the application provides recommendations for further actions.

Primary endpoints:

1. Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value.
2. Frequency of AL after colorectal surgeries

Secondary endpoints:

1. Mortality within 30 days:.
2. Delay in the diagnosis of AL (number of days from the onset of the first signs of a leakage to the diagnosis of AL)
3. Duration of hospital stay.
4. Number of days in the ICU.
5. Number of days between surgery and detection of AL.

Postoperative monitoring with the "Colorectal Leakage App":

It is planned to implement standardized postoperative monitoring for patients who have undergone colorectal surgeries using the "Colorectal Leakage App." The application will include an algorithm based on the Dutch Leakage Score indicator. Each postoperative day, data entry at the patient's bedside will be carried out in the application.

1. Fever
2. Heart rate
3. Respiratory rate
4. Urinary production
5. Mental status
6. Clinical condition
7. Signs of ileus
8. Gastric retention
9. Fascial dehiscence
10. Abdominal pain, other than
11. wound pain
12. Increased leukocyte count, C-reactive protein (CRP), creatinine, and urea.
13. Nutritional status Based on the data analysis, the algorithm will provide recommendations regarding the necessity of conducting a computer tomography with rectal contrast.

The following information will also be collected: Preoperative risk factors for AL(age, gender, obesity, nutritional status, diabetes, cardiovascular diseases, renal insufficiency, inflammatory bowel diseases, ASAscore, bowel preparation); Surgery data (access, surgery type, anastomosis technique, duration of surgery, blood loss volume, formation of a preventive stoma, intraoperative and postoperative complications, pTNM).

Key points determining the conclusion of a patient's participation in the study will be: the detection of AL, patient discharge from the hospital, or patient death.