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Antigen-Capture Enzyme-Linked Immunosorbent Assay for Specific Detection of Mycoplasma pneumoniae
Published on: February 24, 2023
[A multicenter prospective study on early identification of refractory Mycoplasma pneumoniae pneumonia in children]
1Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou 310052, China.
Insights
Early identification of refractory Mycoplasma pneumoniae pneumonia (RMPP) is possible using peak body temperature and lactate dehydrogenase (LDH) levels. This prediction model aids in distinguishing RMPP from general Mycoplasma pneumoniae pneumonia (GMPP) in children.
Area of Science:
- Pediatric Infectious Diseases
- Respiratory Medicine
- Microbiology
Background:
- Mycoplasma pneumoniae pneumonia (MPP) is a common childhood respiratory infection.
- Refractory MPP (RMPP) presents a significant clinical challenge due to its severity and potential complications.
- Early identification of RMPP is crucial for timely and effective treatment.
Purpose of the Study:
- To identify early predictors of refractory Mycoplasma pneumoniae pneumonia (RMPP) in pediatric patients.
- To develop a predictive model for RMPP based on clinical and laboratory parameters.
- To differentiate RMPP from general Mycoplasma pneumoniae pneumonia (GMPP) in the early stages of illness.
Main Methods:
- A prospective multicenter study involving 1,428 pediatric patients with fever lasting 48-120 hours.
- Detection of Mycoplasma pneumoniae DNA in pharyngeal swabs.
- Comparison of clinical data, including peak body temperature and lactate dehydrogenase (LDH) levels, between RMPP and GMPP groups using Mann-Whitney U test and logistic regression.
- Receiver operating characteristic (ROC) curve analysis to evaluate predictive power.
Main Results:
- Mycoplasma pneumoniae DNA was detected in 37.4% of patients, with 446 diagnosed with MPP.
- Macrolides-resistant Mycoplasma pneumoniae was prevalent (91.9%).
- Patients with RMPP exhibited significantly higher peak body temperatures and LDH levels compared to GMPP patients (P<0.05).
- A logistic regression model incorporating peak body temperature and LDH levels demonstrated good predictive performance for RMPP (AUC=0.682, P<0.01).
Conclusions:
- Peak body temperature and LDH levels are significant early predictors of RMPP in pediatric patients.
- A predictive probability model using these parameters can facilitate early identification of RMPP.
- This model aids in distinguishing RMPP from GMPP, allowing for prompt clinical intervention.
Abstract:
Objective: To explore potential predictors of refractory Mycoplasma pneumoniae pneumonia (RMPP) in early stage. Methods: The prospective multicenter study was conducted in Zhejiang, China from May 1st, 2019 to January 31st, 2020. A total of 1 428 patients with fever >48 hours to <120 hours were studied. Their clinical data and oral pharyngeal swab samples were collected; Mycoplasma pneumoniae DNA in pharyngeal swab specimens was detected. Patients with positive Mycoplasma pneumoniae DNA results underwent a series of tests, including chest X-ray, complete blood count, C-reactive protein, lactate dehydrogenase (LDH), and procalcitonin. According to the occurrence of RMPP, the patients were divided into two groups, RMPP group and general Mycoplasma pneumoniae pneumonia (GMPP) group. Measurement data between the 2 groups were compared using Mann-Whitney U test. Logistic regression analyses were used to examine the associations between clinical data and RMPP. Receiver operating characteristic (ROC) curves were used to analyse the power of the markers for predicting RMPP. Results: A total of 1 428 patients finished the study, with 801 boys and 627 girls, aged 4.3 (2.7, 6.3) years. Mycoplasma pneumoniae DNA was positive in 534 cases (37.4%), of whom 446 cases (83.5%) were diagnosed with Mycoplasma pneumoniae pneumonia, including 251 boys and 195 girls, aged 5.2 (3.3, 6.9) years. Macrolides-resistant variation was positive in 410 cases (91.9%). Fifty-five cases were with RMPP, 391 cases with GMPP. The peak body temperature before the first visit and LDH levels in RMPP patients were higher than that in GMPP patients (39.6 (39.1, 40.0) vs. 39.2 (38.9, 39.7) ℃, 333 (279, 392) vs. 311 (259, 359) U/L, both P<0.05). Logistic regression showed the prediction probability π=exp (-29.7+0.667×Peak body temperature (℃)+0.004×LDH (U/L))/(1+exp (-29.7+0.667×Peak body temperature (℃)+0.004 × LDH (U/L))), the cut-off value to predict RMPP was 0.12, with a consensus of probability forecast of 0.89, sensitivity of 0.89, and specificity of 0.67; and the area under ROC curve was 0.682 (95%CI 0.593-0.771, P<0.01). Conclusion: In MPP patients with fever over 48 to <120 hours, a prediction probability π of RMPP can be calculated based on the peak body temperature and LDH level before the first visit, which can facilitate early identification of RMPP.
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