Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model
Group A Streptococcus (GAS) infections, caused by Streptococcus pyogenes, are a major health concern among children under 12 years, leading to conditions such as tonsillitis, rheumatic fever, and post-streptococcal glomerulonephritis. Accurate diagnosis is essential for effective treatment and preve...
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| Language: | English |
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Elsevier
2024-12-01
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| Series: | The Microbe |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950194624001353 |
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| author | F.C. Ihenetu C.I. Okoro M.M. Ozoude K.E. Dunga C. Nwaoha |
| author_facet | F.C. Ihenetu C.I. Okoro M.M. Ozoude K.E. Dunga C. Nwaoha |
| author_sort | F.C. Ihenetu |
| collection | DOAJ |
| description | Group A Streptococcus (GAS) infections, caused by Streptococcus pyogenes, are a major health concern among children under 12 years, leading to conditions such as tonsillitis, rheumatic fever, and post-streptococcal glomerulonephritis. Accurate diagnosis is essential for effective treatment and prevention. This study aimed to develop and validate a Clinical Prediction Rule (CPR) for predicting the presence of S. pyogenes in throat swabs from children under 12. We analyzed clinical and laboratory data from 1015 pediatric patients presenting with symptoms suggestive of GAS infection at Federal University Teaching Hospital, Owerri, Imo State, between January 2019 and December 2022. S. pyogenes was first isolated from throat swabs cultured on blood agar, and 233 positive isolates were further identified using Polymerase Chain Reaction (PCR) targeting the Spy 1258 gene, with DNA extracted via boiling and confirmed through phenotypic methods. Data from these 233 identified cases were used to develop and validate the CPR. Variables examined included gender, age, ward of admission, clinical diagnosis, and antibiotic susceptibility. Logistic regression modeling identified significant predictors of S. pyogenes presence, with potential biases minimized through systematic case review, standardized data extraction and cross-checking by multiple reviewers. Among the 233 cases analyzed, the mean age was 4 ± 0.25 years, with 62.7 % under age 3. Tonsillitis was the predominant diagnosis, with GAS prevalence ranging from 56.7 % to 69.3 %. Antibiotic susceptibility test result varied, with significant predictors including Sepsis/Tonsillitis and ear discharge/tonsillitis (p < 0.001). The CPR model demonstrated a sensitivity of 95.4 % and a specificity of 36.8 %, highlighting its potential to enhance clinical diagnosis and management of GAS infections. This study offers valuable insights into predictors of S. pyogenes infection in pediatric patients and highlights the CPR’s potential for improving clinical diagnosis and management. |
| format | Article |
| id | doaj-art-5cfadbe2d9e144fba2c087caee93a75f |
| institution | Kabale University |
| issn | 2950-1946 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Microbe |
| spelling | doaj-art-5cfadbe2d9e144fba2c087caee93a75f2024-12-18T08:55:40ZengElsevierThe Microbe2950-19462024-12-015100168Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction modelF.C. Ihenetu0C.I. Okoro1M.M. Ozoude2K.E. Dunga3C. Nwaoha4Deapartment of Microbiology, Imo State University, Owerri, NigeriaDepartment of Microbiology, Federal University Teaching Hospital Owerri, NigeriaZaporizhzhia State Medical and Pharmaceutical University, Ukraine; Corresponding author.Department of Medical Laboratory Science, Rhema University, Aba, NigeriaDepartment of Pediatrics, Federal University Teaching Hospital Owerri, NigeriaGroup A Streptococcus (GAS) infections, caused by Streptococcus pyogenes, are a major health concern among children under 12 years, leading to conditions such as tonsillitis, rheumatic fever, and post-streptococcal glomerulonephritis. Accurate diagnosis is essential for effective treatment and prevention. This study aimed to develop and validate a Clinical Prediction Rule (CPR) for predicting the presence of S. pyogenes in throat swabs from children under 12. We analyzed clinical and laboratory data from 1015 pediatric patients presenting with symptoms suggestive of GAS infection at Federal University Teaching Hospital, Owerri, Imo State, between January 2019 and December 2022. S. pyogenes was first isolated from throat swabs cultured on blood agar, and 233 positive isolates were further identified using Polymerase Chain Reaction (PCR) targeting the Spy 1258 gene, with DNA extracted via boiling and confirmed through phenotypic methods. Data from these 233 identified cases were used to develop and validate the CPR. Variables examined included gender, age, ward of admission, clinical diagnosis, and antibiotic susceptibility. Logistic regression modeling identified significant predictors of S. pyogenes presence, with potential biases minimized through systematic case review, standardized data extraction and cross-checking by multiple reviewers. Among the 233 cases analyzed, the mean age was 4 ± 0.25 years, with 62.7 % under age 3. Tonsillitis was the predominant diagnosis, with GAS prevalence ranging from 56.7 % to 69.3 %. Antibiotic susceptibility test result varied, with significant predictors including Sepsis/Tonsillitis and ear discharge/tonsillitis (p < 0.001). The CPR model demonstrated a sensitivity of 95.4 % and a specificity of 36.8 %, highlighting its potential to enhance clinical diagnosis and management of GAS infections. This study offers valuable insights into predictors of S. pyogenes infection in pediatric patients and highlights the CPR’s potential for improving clinical diagnosis and management.http://www.sciencedirect.com/science/article/pii/S2950194624001353Streptococcus pyogenesPediatricsPredictionAntibioticTonsillitis |
| spellingShingle | F.C. Ihenetu C.I. Okoro M.M. Ozoude K.E. Dunga C. Nwaoha Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model The Microbe Streptococcus pyogenes Pediatrics Prediction Antibiotic Tonsillitis |
| title | Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model |
| title_full | Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model |
| title_fullStr | Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model |
| title_full_unstemmed | Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model |
| title_short | Optimizing diagnosis of pediatric Streptococcus pyogenes infections: A clinical prediction model |
| title_sort | optimizing diagnosis of pediatric streptococcus pyogenes infections a clinical prediction model |
| topic | Streptococcus pyogenes Pediatrics Prediction Antibiotic Tonsillitis |
| url | http://www.sciencedirect.com/science/article/pii/S2950194624001353 |
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