D-dimer: The Risk Factor of Children's Severe Mycoplasma Pneumoniae Pneumonia

Detection of Mycoplasma pneumoniae in hospitalized pediatric patients presenting with acute lower respiratory tract infections utilizing targeted next-generation sequencing

BACKGROUND

Mycoplasma pneumoniae is a prevalent pathogen in pediatric community-acquired pneumonia. Currently, limited literature exists on the clinical utilization of pathogen-targeted sequencing technologies.

METHODS

Targeted next-generation sequencing (tNGS) technology was employed to analyze bronchoalveolar lavage fluid (BALF) from 1,070 hospitalized pediatric patients with acute lower respiratory tract infections. Subsequently, the clinical data of children diagnosed with Mycoplasma pneumoniae pneumonia were systematically evaluated.

RESULTS

tNGS identified pathogenic infections in 1,064 (99.4%) of these patients, with M. pneumoniae infections representing 56.9% of the cases. Of these with M. pneumoniae cases, 169 patients (27.75%, 169/609) had infections solely due to with M. pneumoniae, while 440 patients (72.25%, 440/609) presented with co-infections involving M. pneumoniae and additional microorganisms. Among the co-infections, Rhinovirus was the most frequent co-infecting pathogen (120/609), followed by Streptococcus pneumoniae (91/609), human respiratory syncytial virus (78/609) and human parainfluenza virus (74/609). Among the 609 children identified M. pneumoniae infection, 274 were found to harbor macrolide-resistant M. pneumoniae (MRMP), yielding a resistance rate of 45.0% (274/609). In children with M. pneumoniae infection, pleural effusion and respiratory failure emerged as the most prevalent respiratory complications, while hepatic impairment and myocardial impairment were the predominant complications of other systems. The median duration of hospitalization for the children diagnosed with M. pneumoniae infection was 7 days. Out of 609 children with M. pneumoniae infection, 10 cases required intensive care unit (ICU) admission, accounting for 1.64% of the total.

CONCLUSION

tNGS technology exhibits substantial clinical utility in identifying pathogens associated with respiratory tract infections. This study delineates the clinical manifestations and co-infection patterns of M. pneumoniae in Guangxi, China.

Predictive value of ig Mycoplasma pneumoniae-DNA, high-density lipoprotein, natural killer cell, and platelet levels for diagnosing severe M. pneumoniae pneumonia in children

OBJECTIVE

The present study aimed to assess the predictive value of Ig Mycoplasma pneumoniae (MP)-DNA, high-density lipoprotein (HDL), natural killer (NK) cell, and platelet (PLT) levels for the diagnosis of severe MP pneumonia (SMPP) in children with MP pneumonia (MPP).

METHODS

Children with MPP admitted to our hospital from August 2022 to February 2024 were selected and assigned to the non-SMPP (NSMPP) and SMPP groups according to whether they had severe pneumonia. The following parameters were analyzed and compared between the two groups by the rank-sum test: age; Ig MP-DNA level; white blood cell, neutrophil (N), and monocyte counts; platelet (PLT), C-reactive protein (CRP), lactate dehydrogenase (LDH), triglycerides, high-density lipoprotein (HDL), low-density lipoprotein, and procalcitonin levels; and levels of T cells, CD4+ T cells, CD8+ T cells, B cells, and NK cells. The chi-square test was used to analyze differences in these variables between genders. One-way analysis of variance was used to select significant variables (P < 0.1) from the abovementioned ones, and the selected variables were analyzed by multivariate analysis of variance to detect independent risk factors. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) value were determined for the independent risk factors.

RESULTS

The two groups showed significant differences in the levels of Ig MP-DNA, N, PLT, CRP, LDH, HDL, CD8+ T cells, and NK cells. PLT and Ig MP-DNA levels were positively correlated with the risk of SMPP development; however, HDL and NK levels showed a negative correlation. The AUC values for Ig MP-DNA + HDL, Ig MP-DNA + NK, Ig MP-DNA + PLT, NK + HDL, NK + PLT, and PLT + HDL were 0.825, 0.812, 0.813, 0.724, 0.717, and 0.701, respectively.

CONCLUSION

The combination of variables, including Ig MP-DNA + HDL, Ig MP-DNA + NK, and Ig MP-DNA + PLT, can predict whether MPP children would develop SMPP.

Severe Mycoplasma pneumoniae infection in a young child: An emerging increase in incidence?

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Predictive value of immune-related parameters in severe Mycoplasma pneumoniae pneumonia in children

Background

The severity of Mycoplasma pneumoniae pneumonia (MPP) is strongly correlated with the extent of the host's immune-inflammatory response. In order to diagnose the severity of MPP early, this study sought to explore the predictive value of immune-related parameters in severe MPP (sMPP) in admitted children.

Methods

We performed a database analysis consisting of patients diagnosed at our medical centers with MPP between 2021 and 2023. We included pediatric patients and examined the association between complete blood cell count (CBC), lymphocyte subsets and the severity of MPP. Binary logistic regression was performed to identify the independent risk factors of sMPP. Receiver operating characteristic (ROC) curves were used to estimate discriminant ability.

Results

A total of 245 MPP patients were included in the study, with 131 males and 114 females, median aged 6.0 [interquartile range (IQR), 4.0-8.0] years, predominantly located in 2023, and accounted for 64.5%. Among them, 79 pediatric patients were diagnosed as sMPP. The parameters of CBC including white blood cell (WBC) counts, neutrophil counts, monocyte counts, platelet counts, and neutrophil-to-lymphocyte ratio (NLR), were higher in the sMPP group (all P<0.05). The parameters of lymphocyte subsets including CD3+ T cell ratio (CD3+%) and CD3+CD8+ T cell ratio (CD3+CD8+%), were lower in the sMPP group (all P<0.05). And CD3-CD19+ B cell ratio (CD3-CD19+%) was higher in the sMPP group. Logistic regression analysis showed that age, CD3-CD19+%, and monocyte counts were identified as independent risk factors for the development of sMPP (all P<0.001). The three factors were applied in constructing a prediction model that was tested with 0.715 of the area under the ROC curve (AUC). The AUC of the prediction model for children aged ≤5 years was 0.823 and for children aged >5 years was 0.693.

Conclusions

The predictive model formulated by age, CD3-CD19+%, and monocyte counts may play an important role in the early diagnosis of sMPP in admitted children, especially in children aged ≤5 years.

Epidemiological characteristics and early predict model of children Mycoplasma Pneumoniae Pneumonia outbreaks after the COVID-19 in Shandong

Since October 2023, a significant outbreak of Mycoplasma Pneumoniae Pneumonia (MPP) has been observed in children in northern China. Chinese health authorities have attributed this epidemiological to immune debt resulting from the relaxation of coronavirus disease 2019 (COVID-19) control measures. This study described the epidemiological features of Mycoplasma pneumoniae (MP) prevalence in children and developed a straightforward prediction model to differentiate between MPP and viral pneumonia in children. The infection rate of MP in children notably increased from 8.12 in 2022 to 14.94% in 2023, peaking between October and November, especially among school-age children. Logistic regression screening identified four key indicators: Age, D-Dimer levels, erythrocyte sedimentation rate, and gender. The developed nomogram exhibited a receiver operator characteristic curve-area under the curve (ROC-AUC) of 0.858, with external validation confirming an ROC-AUC of 0.794. This study examined the epidemiological characteristics of MPP prevalence in children in Shandong Province during and after the COVID-19 pandemic. An early predict model was developed and validated to differentiate between Mycoplasma Pneumoniae and viral infections.

Clinical value of monitoring cytokine levels for assessing the severity of mycoplasma pneumoniae pneumonia in children

BACKGROUND

To investigate the clinical relevance of cytokine levels in assessment of the severity of mycoplasma pneumoniae pneumonia (MPP) in children.

METHODS

A retrospective study was conducted on 150 pediatric cases of MPP admitted to a local hospital in China from November 1, 2022 to October 31, 2023. These MPP cases were divided into mild (n=100) and severe (n=50) groups according to the severity of the disease. Cytokine levels, including Interferon-γ (IFN-γ), Tumor Necrosis Factor-α (TNF-α), C-reactive protein (CRP), Interleukin-6 (IL-6), Interleukin-2 (IL-2), and D-Dimer (D-D), were compared between the two groups. The diagnostic efficacy of each cytokine in assessing the severity of MPP was analyzed through Receiver Operating Characteristic (ROC) curves, and correlation between cytokine levels and disease severity was assessed using Pearson's correlation coefficient.

RESULTS

The IL-2 level was significantly lower, while TNF-α, IL-6, and IFN-γ levels were significantly higher in the severe group compared to the mild group (all P<0.05). TNF-α, IFN-γ, IL-2, IL-6, CRP, and D-D were identified as factors influencing the severity of MPP (all P<0.05). The ROC curve analysis showed that the areas under the curve (AUCs) of TNF-α, IL-2, IL-6, IFN-γ, CRP, and D-D were 0.864, 0.692, 0.874, 0.949, 0.814, and 0.691, respectively (all P<0.001), indicating their diagnostic value in assessing the severity of MPP. There exists a positive correlation between IL-2 and the percentage of normal lung density on Computed Tomography (CT) scan (P<0.05), while TNF-α, IL-6, IFN-γ, CRP, and D-D showed negative correlations with the percentage of normal lung density (P<0.05).

CONCLUSION

Cytokines such as TNF-α, IL-2, IL-6, IFN-γ, CRP, and D-D are aberrantly expressed in children with MPP and are associated with the severity of the disease. These cytokines have high diagnostic value and can serve as reference indicators for clinical, especially prognostic assessment of the severity of (pediatric) MPP.

Early predictors of delayed radiographic resolution of lobar pneumonia caused by Mycoplasma pneumoniae in children: a retrospective study in China

BACKGROUND

Lobar pneumonia caused by Mycoplasma pneumoniae is a relatively difficult-to-treat pneumonia in children. The time of radiographic resolution after treatment is variable, a long recovery time can result in several negative effects, and it has attracted our attention. Therefore, exploring factors associated with delayed radiographic resolution will help to identify these children at an early stage and prepare for early intervention.

METHODS

The data of 339 children with lobar pneumonia caused by Mycoplasma pneumoniae were collected from the Department of Pediatrics of Fu Yang People's Hospital, China from January 2021 to June 2022. After discharge, the children were regularly followed up in the outpatient department and on the WeChat platform for > 8 weeks. According to whether pulmonary imaging (chest radiography or plain chest computed tomography) returned to normal within 8 weeks, the children were divided into the delayed recovery group (DRG) (n = 69) and the normal recovery group (NRG) (n = 270). The children's general information, laboratory examination findings, bronchoscopy results, and imaging findings were retrospectively analyzed. Single-factor analysis was performed to identify the risk factors for delayed radiographic resolution of lobar pneumonia caused by Mycoplasma pneumoniae, and the factors with statistically significant differences underwent multiple-factor logistic regression analysis. Receiver operating characteristic (ROC) analysis was then performed to calculate the cutoff value of early predictive indicators of delayed radiographic resolution.

RESULTS

Single-factor analysis showed that the following were significantly greater in the DRG than NRG: total fever duration, the hospitalization time, C-reactive protein (CRP) level, lactate dehydrogenase (LDH) level, D-dimer level, pulmonary lesions involving two or more lobes, a large amount of pleural effusion, the time to interventional bronchoscopy, and mucus plugs formation. Multivariate logistic regression analysis showed that the hospitalization time, CRP level, LDH level, pulmonary lesions involving two or more lobes, and a large amount of pleural effusion were independent risk factors for delayed radiographic resolution of lobar pneumonia caused by Mycoplasma pneumoniae. The cutoff values on the receiver operating characteristic curve were a hospitalization time of ≥ 10.5 days, CRP level of ≥ 25.92 mg/L, and LDH level of ≥ 378 U/L.

CONCLUSION

If patients with lobar pneumonia caused by Mycoplasma pneumoniae have a hospitalization time of ≥ 10.5 days, CRP level of ≥ 25.92 mg/L, and LDH level ≥ 378 U/L, the time of radiographic resolution is highly likely to exceed 8 weeks. Pediatricians must maintain a high level of vigilance for these factors, control the infection as early as possible, strengthen airway management, and follow up closely to avoid complications and sequelae of Mycoplasma pneumoniae pneumonia.

The Clinical Value of Systemic Immune Inflammation Index (SII) in Predicting the Severity of Hospitalized Children with Mycoplasma Pneumoniae Pneumonia: A Retrospective Study

Objective

The Systemic Immune Inflammation Index (SII), as a novel inflammation biomarker that comprehensively reflects the inflammatory and immune status of the body, has not been reported in studies on Mycoplasma pneumoniae pneumonia (MPP) in children. This study aims to investigate whether SII can serve as an effective indicator for evaluating the condition of MPP.

Methods

This study recruited a total of 304 hospitalized patients with mycoplasma pneumoniae pneumonia (MPP), including 78 patients with severe MPP (SMPP) and 226 patients with non-SMPP. Univariate analysis using chi-square test, t-test, and Mann-Whitney U-test was conducted to analyze the clinical data of the patients. Logistic regression analysis was employed to identify the main risk factors for SMPP. Receiver operating characteristic curves were plotted to evaluate the potential of using neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic immune response index (SIRI) to predict the severity of MPP.

Results

The ROC curve results show that patients with SII values ≥ 699.00 are more likely to develop severe MPP (sensitivity=0.876, specificity=0.987, AUC=0.940), and the predictive value of SII is significantly better than that of NLR, PLR, and SIRI. The results of multivariate logistic regression analysis indicate that SII can serve as a major risk factor for distinguishing non-SMPP from SMPP.

Conclusion

This study suggests that SII may be an effective indicator for predicting the severity of MPP in children. SII is more sensitive and specific than NLR, PLR, and SIRI in evaluating the condition of MPP.

Machine learning algorithms for prediction of ventilator associated pneumonia in traumatic brain injury patients from the MIMIC-III database

BACKGROUND

Ventilator associated pneumonia (VAP) is a common complication and associated with poor prognosis of traumatic brain injury (TBI) patients.

OBJECTIVES

This study was conducted to explore the predictive performance of different machine-learning algorithms for VAP in TBI patients.

METHODS

TBI patients receiving mechanical ventilation more than 48 hours from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were eligible for the study. The VAP was confirmed based on the ICD-9 code. Included patients were separated to the training cohort and the validation cohort with a ratio of 7:3. Predictive models based on different machine learning algorithms were developed using 5-fold cross validation in the training cohort and then verified in the validation cohort by evaluating the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy and F score.

RESULTS

786 TBI patients from the MIMIC-III were finally included with the VAP incidence of 44.0%. The random forest performed the best on predicting VAP in the training cohort with a AUC of 1.000. The XGBoost and AdaBoost were ranked the second and the third with a AUC of 0.915 and 0.789 in the training cohort. While the AdaBoost performed the best on predicting VAP in the validation cohort with a AUC of 0.706. The XGBoost and random forest were ranked the second and the third with the AUC of 0.685 and 0.683 in the validation cohort. Generally, the random forest and XGBoost were likely to be over-fitting while the AdaBoost was relatively stable in predicting the VAP.

CONCLUSIONS

The AdaBoost performed well and stably on predicting the VAP in TBI patients. Developing programs using AdaBoost in portable electronic devices may effectively assist physicians in assessing the risk of VAP in TBI.

Changes in coagulation markers in children with Mycoplasma pneumoniae pneumonia and their predictive value for Mycoplasma severity

BACKGROUND

This study investigates the correlation between coagulation levels and the severity of Mycoplasma pneumoniae pneumonia (MPP) in children. In addition, the study analyses the predictive value of coagulation abnormalities in MPP combined with necrotising pneumonia (NP).

METHODS

A total of 170 children with MPP who underwent treatment between June 2021 and February 2022 were selected for this study. The study population was divided into groups according to the severity of the disease to compare differences in the incidence of coagulation abnormalities between the groups. The participants were also divided into groups according to imaging manifestations to compare the differences in coagulation function among the different groups. All data information was processed for statistical analysis using SPSS Statistics 25.0 and GraphPad Prism 7.0 statistical analysis software.

RESULTS

The incidence of coagulation abnormalities in the children in the severe MPP (SMPP) group was significantly higher than that in the normal MPP (NMPP) group (P < 0.05). The multi-factor logistic regression analysis revealed that the D-dimer level is an independent risk factor for the development of NP in SMPP (P < 0.05). The receiver operating characteristic curve analysis revealed statistically significant differences (P < 0.05) in D-dimer, fibrinogen degeneration products (FDP), neutrophils, lactate dehydrogenase and serum ferritin for predicting SMPP combined with NP. Bronchoscopic manifestations of coagulation indicators (D-dimer and FDP levels) were significantly higher in the mucus plug group than in the non-mucus plug group, while the activated partial thromboplastin time levels were lower in the former than in the latter (P < 0.05).

CONCLUSION

The degree of elevated D-dimer and FDP levels was positively correlated with the severity of MPP, with elevated serum D-dimer levels (> 3.705 mg/L) serving as an independent predictor of MPP combined with NP in children.

Predictive value of platelet-related parameters combined with pneumonia severity index score for mortality rate of patients with severe pneumonia

Background

To analyse the predictive value of platelet-related parameters combined with pneumonia severity index (PSI) score for the mortality rate of patients with severe pneumonia.

Methods

The clinical data of 428 severe pneumonia patients were retrospectively analysed. They were divided into survivor and death groups according to 28-day prognosis. Platelet-related parameters platelet count (PLT), mean platelet volume (MPV), platelet-large-cell ratio (P-LCR) and platelet distribution width (PDW) were measured within 24 hours after admission. The receiver operating characteristic (ROC) curves were plotted. The areas under the ROC curves (AUC) were used to describe the predictive efficiencies of platelet-related parameters, PSI score and their combination for death within 28 days.

Results

On the 28th day, there were 184 deaths and 244 survivors, and the deaths had significantly higher PLT and PSI score but lower PDW, MPV and P-LCR than those of the survivors (P<0.05). The combination of platelet-related parameters and PSI score had the highest sensitivity (96.56%) and specificity (99.34%) and the largest AUC (0.902) for predicting 28-day mortality.

Conclusion

PLT, PDW, MPV and P-LCR are significantly abnormal in patients with severe pneumonia, and the combination of platelet-related parameters with PSI score has the highest predictive value for 28-day mortality.

Risk Prediction Model for Necrotizing Pneumonia in Children with Mycoplasma pneumoniae Pneumonia

Objective

To analyze the predictive factors for necrotizing pneumonia (NP) in children with Mycoplasma pneumoniae pneumonia (MPP) and construct a prediction model.

Methods

The clinical data with MPP at the Children's Hospital of Kunming Medical University from January 2014 to November 2022 were retrospectively analyzed. Eighty-four children with MPP who developed NP were divided into the necrotizing group, and 168 children who did not develop NP were divided into the non-necrotizing group by propensity-score matching. LASSO regression was used to select the optimal factors, and multivariate logistic regression analysis was used to establish a clinical prediction model. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate the discrimination and calibration of the nomogram. Clinical decision curve analysis was used to evaluate the clinical predictive value.

Results

LASSO regression analysis showed that bacterial co-infection, chest pain, LDH, CRP, duration of fever, and D-dimer were the influencing factors for NP in children with MPP (P < 0.05). The results of ROC analysis showed that the AUC of the prediction model established in this study for predicting necrotizing MPP was 0.870 (95% CI: 0.813-0.927, P < 0.001) in the training set and 0.843 (95% CI: 0.757-0.930, P < 0.001) in the validation set. The Bootstrap repeated sampling for 1000 times was used for internal validation, and the calibration curve showed that the model had good consistency. The Hosmer-Lemeshow test showed that the predicted probability of the model had a good fit with the actual probability in the training set and the validation set (P values of 0.366 and 0.667, respectively). The clinical decision curve showed that the model had good clinical application value.

Conclusion

The prediction model based on bacterial co-infection, chest pain, LDH, CRP, fever duration, and D-dimer has a good predictive value for necrotizing MPP.

Meningitis patients with pneumonia: correlation between blood parameters and clinical features

Background: This research aimed to explore the possible relationship between the main experimental parameters and clinical status in meningitis patients with pneumonia infection. Methods: A retrospective analysis of the demographic characteristics, clinical features and laboratory parameters of meningitis patients was performed. Results: D-dimer, C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) exhibited good diagnostic ability for meningitis complicated with pneumonia. Additionally, we observed a positive correlation between D-dimer and CRP in cases of meningitis with pneumonia infection. D-dimer, ESR and Streptococcus pneumoniae (S. pneumoniae) were independently associated with meningitis patients with pneumonia infection. Conclusion: D-dimer, CRP, ESR and S. pneumoniae infection may effectively anticipate disease progression and adverse consequences in meningitis patients with pneumonia infection.