Predicting Mycoplasma pneumoniae and Chlamydophila pneumoniae in community-acquired pneumonia (CAP) pneumonia: epidemiological study of respiratory tract infection using multiplex PCR assays

Abstract

Community-acquired pneumonia (CAP) is a common illness that can lead to mortality. β-lactams are ineffective against atypical pathogen including Mycoplasma pneumoniae . We used molecular examinations to develop a decision tree to predict atypical pathogens with CAP and to examine the prevalence of macrolide resistance in Mycoplasma pneumoniae . We conducted a prospective observational study of patients aged ≥ 18 years who had fever and respiratory symptoms and were diagnosed with CAP in one of two community hospitals between December 2016 and October 2018. We assessed combinations of clinical variables that best predicted atypical pathogens with CAP by classification and regression tree (CART) analysis. Pneumonia was defined as respiratory symptoms and new infiltration recognized on chest X-ray or chest computed tomography. We analyzed 47 patients (21 females, 44.7%, mean age: 47.6 years). Atypical pathogens were detected in 15 patients (31.9%; 12 Mycoplasma pneumoniae , 3 Chlamydophila pneumoniae ). Ten patients carried macrolide resistant Mycoplasma pneumoniae (macrolide resistant rate 83.3%). CART analysis suggested that factors associated with presence of atypical pathogens were absence of crackles, age < 45 years, and LD ≥ 183 U/L (sensitivity 86.7% [59.5, 98.3], specificity 96.9% [83.8, 99.9]). ur simple clinical decision rules can be used to identify primary care patients with CAP that are at risk for atypical pathogens. Further research is needed to validate its usefulness in various populations. Trial registration Clinical Trial (UMIN trial ID: UMIN000035346).

Epidemiological Study on Mycoplasma pneumoniae and Chlamydia pneumoniae Infection of Hospitalized Children in a Single Center During the COVID-19 Pandemic

“…Although the positive rate of CP was low in both 2019 and 2020, the number of CP -positive patients monthly in 2020 was still significantly decreased compared with that in 2019. A low prevalence of CP infections was also found in other countries, such as Japan ( Oishi et al., 2020 ; Ishimaru et al., 2021 ), or other regions in China ( Li et al., 2021 ; Luo et al., 2021 ). Due to the strict prevention and control policy for COVID-19 in China, the positive rate of CP reached a lower degree (0.0%-0.5%) from April to December 2020.…”

Seasonal predominance of atypical agents in adult community-acquired pneumonia in India's northeastern region: Is it the time to look again at empirical therapy guidelines?

“…A total of 663 subjects were included in the initial screening, but 75 subjects were lost to follow up or non-traceable results (51), refusal to be part of the study (9), and inadequate sample (15). A detected atypical agent profile is shown in the Supplementary Table . Distribution of risk factors (atypical infection) are shown in Table 1.…”

“…3 One Japanese study too concluded the same. 5 One article concluded that an age <45 years to be significantly linked to atypical bacterial CAP, 9 but another could find no specific risk factor for atypical agents in their cohort of severe hospitalized CAP patients. 6 Nonetheless, a multicentric Indian study found COPD to be significantly associated with CAP by atypical agents.…”

WACPN: A Neural Network for Pneumonia Diagnosis

“…The AUCs of the models removing AIWF or RA are only 0.9319 and 0.9456, respectively, demonstrating that both AIWF and RA help improve the standard PSO. The proposed WACPN model is judged with six state-of-the-art models: GAN [4], CADe [5], SVM [6], IQNN [7], DT [8], and CSO [9]. The evaluation results on the same dataset via ten runs of 10-fold CV are listed in Tab.…”

“…Dong, et al [ 7 ] proposed an improved quantum neural network (IQNN) for pneumonia image recognition. Ishimaru, et al [ 8 ] proposed a decision tree (DT) model to foresee the atypical pathogens of CAP. Zhou [ 9 ] introduced the cat swarm optimization (CSO) method to recognize CAP.…”