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Introduction <p>Acute appendicitis (AA) is the most common surgical emergency in pediatric patients, yet its diagnosis remains challenging due to variable clinical presentations and the overlap with other causes of abdominal pain. Predictive scores can enhance diagnostic accuracy, reduce unnecessary surgeries, and optimize resource utilization, especially in resource-limited settings. This study aimed to identify key predictive factors for acute appendicitis in children and to develop a combined clinical and biological scoring system to enhance diagnostic accuracy for this condition.</p> Patients and methods <p>We prospectively enrolled children aged 2 to 14 years presenting with abdominal pain to the pediatric surgery department at Fattouma Bourguiba University Hospital over a one-year period. Clinical, biological, and sonographic data were analyzed to identify key predictive factors and derive a predictive scoring model for acute appendicitis in this population. Model performance was assessed using the area under the curve (AUC) on the same dataset used for model derivation.</p> Results <p>Among 420 children presenting with abdominal pain, 91 (21.7%) were diagnosed with AA. The median age of the children was 7 years, with a male-to-female ratio of 1.48. Binary logistic regression identified the following predictive factors: right iliac fossa tenderness, right iliac fossa guarding, positive right single-leg hop, and neutrophil percentage ≥ 75%. The predictive model achieved an AUC of 0.901 (95% CI [0.85–0.93]) with a significance of P &lt; 0.0001. The optimal cut-off for the model was 5, yielding a sensitivity of 61.04%, specificity of 95.38%, positive predictive value (PPV) of 76.4%, and negative predictive value (NPV) of 90.5%. Stratified management strategies based on the score were proposed to guide clinical decision-making effectively.</p> Conclusion <p>The developed predictive score offers a simple, practical, and highly specific tool for diagnosing AA in pediatric emergencies. Its integration of functional signs, such as the right-sided single-leg hop test, enhances clinical utility, making it particularly valuable in resource-constrained settings. Further validations are warranted to confirm its generalizability and reliability.</p> Clinical trial number <p>Not applicable.</p> Level of evidence <p>II</p>

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Development of a new predictive clinico-biological score for acute appendicitis in the pediatric population

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月25日

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  • Sabrine Ben Youssef,
  • Afef Toumi,
  • Meriem Hassine,
  • Myriam Ben Fredj,
  • Radhouene Ben Salah,
  • Sami Sfar,
  • Meriem Kacem,
  • Sana Mosbahi,
  • Amine Ksia,
  • Mongi Mekki,
  • Mohsen Belghith,
  • Asma Sriha Belguith,
  • Sawssen Chakroun,
  • Lassaad Sahnoun

摘要

Introduction

Acute appendicitis (AA) is the most common surgical emergency in pediatric patients, yet its diagnosis remains challenging due to variable clinical presentations and the overlap with other causes of abdominal pain. Predictive scores can enhance diagnostic accuracy, reduce unnecessary surgeries, and optimize resource utilization, especially in resource-limited settings. This study aimed to identify key predictive factors for acute appendicitis in children and to develop a combined clinical and biological scoring system to enhance diagnostic accuracy for this condition.

Patients and methods

We prospectively enrolled children aged 2 to 14 years presenting with abdominal pain to the pediatric surgery department at Fattouma Bourguiba University Hospital over a one-year period. Clinical, biological, and sonographic data were analyzed to identify key predictive factors and derive a predictive scoring model for acute appendicitis in this population. Model performance was assessed using the area under the curve (AUC) on the same dataset used for model derivation.

Results

Among 420 children presenting with abdominal pain, 91 (21.7%) were diagnosed with AA. The median age of the children was 7 years, with a male-to-female ratio of 1.48. Binary logistic regression identified the following predictive factors: right iliac fossa tenderness, right iliac fossa guarding, positive right single-leg hop, and neutrophil percentage ≥ 75%. The predictive model achieved an AUC of 0.901 (95% CI [0.85–0.93]) with a significance of P < 0.0001. The optimal cut-off for the model was 5, yielding a sensitivity of 61.04%, specificity of 95.38%, positive predictive value (PPV) of 76.4%, and negative predictive value (NPV) of 90.5%. Stratified management strategies based on the score were proposed to guide clinical decision-making effectively.

Conclusion

The developed predictive score offers a simple, practical, and highly specific tool for diagnosing AA in pediatric emergencies. Its integration of functional signs, such as the right-sided single-leg hop test, enhances clinical utility, making it particularly valuable in resource-constrained settings. Further validations are warranted to confirm its generalizability and reliability.

Clinical trial number

Not applicable.

Level of evidence

II