Serum inflammatory markers in children with Mycoplasma pneumoniae pneumonia and their predictive value for mycoplasma severity

Abstract

BACKGROUND

Mycoplasma pneumoniae pneumonia (MPP) significantly impacts pediatric health, necessitating markers for early severe disease identification.

AIM

To investigate the correlation between serum inflammatory marker and the severity of MPP in children.

METHODS

A prospective study was carried out from January 2023 to November 2023. A total of 160 children with MPP who underwent treatment were selected: 80 had severe MPP and 80 had mild MPP. Clinical and laboratory data were collected at the time of hospital admission and during hospitalization. Receiver operating characteristic curves were utilized to assess the diagnostic and prognostic for severe MPP.

RESULTS

Fever duration and length of hospitalization in pediatric patients with severe MPP exceeded those with mild MPP. The incidence of pleural effusion, lung consolidation, and bronchopneumonia on imaging was markedly elevated in the severe MPP cohort compared to the mild MPP cohort. In contrast to the mild cohort, there was a notable increase in C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate, lactic dehydrogenase, D-dimer, and inflammatory cytokines [interleukin (IL)-6, IL-8, IL-10 and tumor necrosis factor (TNF)-α] in the severe MPP group were significantly higher.

CONCLUSION

Serum inflammatory markers (CRP, PCT, IL-6, D-dimer, IL-10 and TNF-α) were considered as predictors in children with severe MPP.

Core Tip: This study highlights the significant correlation between elevated serum inflammatory markers and severity of Mycoplasma pneumoniae pneumonia (MPP) in children. Key markers such as C-reactive protein, procalcitonin, erythrocyte sedimentation rate, lactic dehydrogenase, D-dimer, and cytokines [interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor] serve as valuable predictors for severe MPP, aiding in early diagnosis and improved prognosis.

INTRODUCTION

Childhood community-acquired pneumonia is defined as a rapid-onset lung infection in children caused by pathogens acquired outside of medical facilities, particularly in non-hospital environments[1,2]. Over the past few years, environmental changes and various other factors have contributed to an increase in cases of Mycoplasma pneumoniae pneumonia (MPP) among children. This condition now represents 20%–40% of all community-acquired pneumonia (CAP) cases in pediatric populations. The incidence of MPP tends to be even higher during epidemic periods, indicating a significant public health concern that demands attention and intervention[3,4]. MPP can invade the lungs and other tissues, causing both upper and lower respiratory infections in children[5]. While some cases of MPP infection are self-limiting, however, severe MPP in children is often accompanied by lung consolidation, necrosis and respiratory failure. Additionally, in China, MPP has led to increased morbidity, mortality and medical costs[6]. Due to the atypical clinical symptoms and insidious onset of early MPP, the progression to severe MPP poses a significant threat to children’s health and increases the economic burden. Therefore, early prediction of refractory MPP, extrapulmonary manifestations and the development of complications can aid in the clinical prevention, diagnosis and treatment of MPP at an earlier stage, thus improving the prognosis and quality of life for patients[7,8].

Previous researches have indicated several biomarkers [such as interleukin (IL), ferritin, α1-antitrypsin and lactic dehydrogenase (LDH)] for the prediction of refractory MPP or treatment responses in MPP[9-11]. One study has shown that D-dimer and CRP are classic biomarker of severe MPP[12]. Many children with respiratory infections have low levels of immune factor; however, there has been no research on the link between these parameters and the severity of illness[13].

Therefore, this study determined the differences in laboratory tests, clinical manifestations and inflammatory cytokines between children with severe and mild MPP. This study aimed to provide reliable data to support early and aggressive treatment, thereby improving patient outcome and prognosis.

MATERIALS AND METHODS

Patients

Children hospitalized for MPP at The First People's Hospital of Linping District between January and November 2023 were included. A total of 160 children with MPP who underwent treatment were selected: 80 had severe MPP and 80 had mild MPP. All children’s parents provided written consent to participate in the study. The first People's Hospital of Linping District Ethics Commit approved the study (Approval number: linping2023044).

The inclusion criteria for the MPP group were as follows: (1) Age 1–14 years; (2) meeting the diagnostic criteria of CAP, having respiratory tract infection symptoms, chest imaging findings showing pneumonia, with or without pleural effusion; and (3) fourfold or more increase in the serum M. pneumonia IgM titer during the recovery period (but not the acute period), or a positive polymerase chain reaction test for M. pneumoniae in sputum[14]. Exclusion criteria: (1) Inclusion criteria were not met; (2) severe immune dysfunction or deficiency; (3) incomplete clinical data; and (4) automatic discharge within 48 h of hospitalization.

Data collection

Clinical and laboratory parameters of patients were collected from the hospital, including hospital stays, duration of fever, chief complaint, cough, lung computed tomography scans, chest radiography, white blood cell count (WBC), C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR), albumin and LDH. The levels of serum cytokines were measured through a sandwich ELISA with double antibodies.

Data analyses and statistics

Statistical analyses were performed using SPSS for Windows version 26. Statistical data are expressed as n (%), When reporting normally distributed measures, it is common to express them as the mean ± SD. In this study, the t-test for two independent samples was utilized to compare different groups[15]. Additionally, a logistic regression model was used for multivariate analysis. The value of inflammatory markers in diagnosing and predicting severe MPP was used the receiver operating characteristic (ROC) curve. Differences were considered statistically significant at P < 0.05.

RESULTS

The study included 160 children with CAP, comprising 80 with mild MPP and 80 with severe MPP. Their main demographic and clinical characteristics are shown in Table 1. Clinical characteristics of severe MPP, such as asthma, oxygen need, postinfectious bronchiolitis obliterans (PIBO), pleural effusion, macrolide-resistant MPP, extrapulmonary manifestations, and lung consolidation were observed in the severe MPP group at rates of 25%, 100%, 22.5%, 20%, 92.5%, 60%, and 72.5%, respectively. In addition, the fever time, pediatric intensive care unit stay, and hospital stay were significantly longer than in the mild MPP group (P < 0.05).

Table 1.

Baseline characteristics of the studied population, n (%)

	Severe MPP (n = 80)	Mild MPP (n = 80)	P value
Sex (male, %)	38 (47.5)	43 (53.8)	0.362
Age, yr	6.82 ± 2.55	7.63 ± 2.67	0.287
Asthma	20 (25)	4 (5)	0.001
Allergic rhinitis	36 (45)	32 (40)	0.325
Fever time, d	6.54 ± 2.83	3.65 ± 1.81	0.001
Hospital stay, d	9.25 ± 2.53	6.54 ± 2.58	0.001
Oxygen need	80 (100)	5 (6.25)	0.001
PICU stay, d	3.62 ± 1.53	0	0.001
PIBO	18 (22.5)	0	0.001
Pleural effusion	16 (20)	0	0.001
Macrolide-resistant MPP	74 (92.5)	32 (40)	0.001
Extrapulmonary manifestations	48 (60)	2 (2.5)	0.001
Lung consolidation	58 (72.5)	4 (5)	0.001

Data are presented as mean ± standard deviation, n (%), or median (interquartile range). SMPP: Severe mycoplasma pneumoniae pneumonia; PICU: Pediatric intensive care unit; PIBO: Postinfectious bronchiolitis obliterans; MPP: Mycoplasma pneumoniae pneumonia.

Inflammatory cytokines and laboratory findings showed that the levels or activities of CRP, PCT, ESR, LDH, D-dimer, IL-6, IL-8, IL-10 and TNF-α were significantly higher in the severe MPP group compared to the MMPP group. However, the albumin and WBC levels did not differ significantly between the severe and mild MPP groups (Table 2).

Table 2.

Inflammatory cytokines and laboratory findings between severe mycoplasma pneumoniae pneumonia group and mild group

	Severe MPP (n = 80)	Mild MPP (n = 80)	P value
WBC (109/L)	8.5 ± 1.2	7.6 ± 1.4	0.386
CRP (mg/L)	21.4 ± 5.8	5.4 ± 2.6	0.001
PCT (ng/mL)	0.25 ± 0.12	0.05 ± 0.01	0.001
ESR (mm/h)	32.6 ± 7.9	15.8 ± 4.6	0.001
Albumin (g/L)	39.4 ± 4.2	40.5 ± 3.8	0.412
LDH (U/L)	484.2 ± 61.4	246.9 ± 54.6	0.001
D-dimer (mg/L)	1.2 ± 0.6	0.35 ± 0.14	0.001
IL-6 (pg/mL)	25.7 ± 5.6	10.6 ± 3.8	0.001
IL-8 (pg/mL)	102.4 ± 38.8	28.6 ± 14.3	0.001
IL-10 (pg/mL)	36.6 ± 8.9	8.4 ± 2.6	0.001
TNF-α (pg/mL)	26.6 ± 6.5	12.2 ± 4.4	0.001

Data are presented as mean ± SD. SMPP: Severe mycoplasma pneumoniae pneumonia; WBC: White blood cell count; CRP: C-reactive protein; PCT: Procalcitonin; ESR: Erythrocyte sedimentation rate; LDH: Lactic dehydrogenase; IL: Interleukin.

Logistic regression analysis of serum inflammatory cytokines and laboratory indicators was performed. CRP, PCT, ESR, IL-8 and pleural effusion were excluded from the analysis (P > 0.05). However, the logistic regression showed that LDH, IL-6, IL-10, TNF-α, D-dimer, lung consolidation, extrapulmonary manifestations, asthma and macrolide-resistant MPP (P < 0.001) were independent risk factors for severe MPP. Therefore, these factors were included as predictive indicators (Table 3).

Table 3.

Logistic regression analysis predictors of severe Mycoplasma pneumoniae pneumonia

Factors	OR	95%CI	P value
CRP	3.24	1.36-6.38	0.267
PCT	1.6	1.41-3.81	0.564
ESR	2.45	1.36-4.64	0.642
LDH	2.83	1.58-5.90	0.001
IL-6	4.82	3.26-8.92	0.001
IL-8	5.23	4.42-7.85	0.415
IL-10	8.96	6.28-12.56	0.001
TNF-α	5.85	4.23-7.94	0.001
D-dimer	1.88	1.28-2.58	0.001
Lung consolidation	9.24	6.56-12.48	0.001
Extrapulmonary manifestations	7.24	5.12-10.26	0.001
Pleural effusion	4.42	3.15-6.22	0.524
Macrolide-resistant MPP	8.27	6.82-16.74	0.001
Asthma	4.27	3.56-9.56	0.001

CRP: C-reactive protein; PCT: Procalcitonin; ESR: Erythrocyte sedimentation rate; LDH: Lactic dehydrogenase; IL: Interleukin; TNF-α: Tumor necrosis factor–α; MPP: Mycoplasma pneumoniae pneumonia.

We used an ROC curve to evaluate LDH, IL-6, IL-10, TNF-α and D-dimer index in the diagnosis of children with severe MPP (Figure 1). AUCs for LDH, IL-6, IL-10, TNF-α, and D-dimer index were: 0.812 [95% confidence interval (CI): 0.664–0.880, and specificity and sensitivity were 84.29% and 88.36%]; 0.789 (95%CI: 0.715–0.853, specificity and sensitivity 78.65% and 84.16%); 0.673 (95%CI: 0.636–0.756, specificity and sensitivity 72.35% and 74.76%); 0.681 (95%CI: 0.624–0.768, specificity and sensitivity 68.58% and 74.96%); and 0.776 (95%CI: 0.734–0.842, specificity and sensitivity 81.25% and 84.16%), respectively.

Figure 1.

Receiver operating characteristic curves for predicting severe mycoplasma pneumoniae pneumonia. ROC: Receiver operating characteristic; TNF-α: Tumor necrosis factor-α; LDH: Lactic dehydrogenase; IL: Interleukin.

DISCUSSION

Recently, the incidence of MPP has been increasing annually in Chinese children, especially after the COVID-19 pandemic[16]. If not treated promptly, it can damage multiple organs and even lead to death. In our research, there were 80 children with mild MPP and 80 with severe MPP, and we found that children with severe MPP had a high rate of asthma, oxygen need, PIBO, pleural effusion, macrolide-resistant MPP, extrapulmonary manifestations, and lung consolidation compared to those with mild MPP. Some studies have confirmed that children with severe MPP were frequently associated with exacerbations of asthma in children[17,18]. In addition, some research has shown that severe MPP had extrapulmonary manifestations, macrolide-resistant MPP, and PIBO, which is consistent with our study[19-21].

D-dimer levels may reflect the coagulation status in infectious diseases and are associated with the inflammatory response[22]. Research has found that the progression of MPP is primarily associated with coagulation system disorders and is closely related to disease prognosis[23]. In addition, researchers have found higher D-dimer levels in children with MPP than in healthy children, particularly those with severe MPP with extra-pulmonary complications[23,24]. Specifically, we found that D-dimer was an independent risk factors for severe MPP and has a value in the diagnosis of children with severe MPP.

In our study, serum LDH level was identified as an independent risk factor for severe MPP. In addition, serum LDH level demonstrated significant diagnostic value for children with severe MPP. Elevated serum LDH level is associated with respiratory virus coinfection, pleural effusion, greater extent of pneumonic lesions on chest radiography, oxygen need, and extrapulmonary manifestations[25]. The significant association of LDH level with severe MPP suggests that elevated LDH levels are indicative of clinically severe pneumonia. Therefore, MPP patients with a high level of LDH require close attention[26].

Some researchers have found that cytokine-mediated inflammation plays a significant role in mycoplasma pathogenicity[27]. In our research, we studied the levels of serum IL-8, IL-6, IL-10 and TNF-α in children with MPP. The levels of serum IL-6, TNF-α and IL-10 in severe MPP were increasingly higher than those in mild MPP. Meanwhile, we demonstrated that the levels of IL-6, TNF-α and IL-10 can be useful predictors for severe MPP. Some research has reported that the severe MPP group has a higher level of IL-6 compared with the control group[28]. Moreover, it was found that IL-6 was a significant predictor regarding MPP[29]. Those conclusions are consistent with our study. Although our study demonstrated an association between serum inflammatory markers and severity of MPP in children, larger studies are needed to strengthen the evidence regarding this relationship and severe MPP.

CONCLUSION

The levels of IL-6, IL-10, LDH, TNF-α and D-dimer can aid in the early identification of severe MPP. However, further studies conducted across multiple centers are needed to validate our findings.

Data sharing statement

No additional data are available.