Yang Liu , Qiuping Tang , Sishi Tang , Hengjian Huang , Lanxi Kou , Yi Zhou , Hongxia Ruan , Yu Yuan , Chao He , Binwu Ying
{"title":"Clinical evaluation of droplet digital PCR in suspected invasive pulmonary aspergillosis","authors":"Yang Liu , Qiuping Tang , Sishi Tang , Hengjian Huang , Lanxi Kou , Yi Zhou , Hongxia Ruan , Yu Yuan , Chao He , Binwu Ying","doi":"10.1016/j.cca.2025.120153","DOIUrl":null,"url":null,"abstract":"<div><div>Invasive pulmonary aspergillosis (IPA), the most common fungal infection, is associated with high mortality of affected patients. Traditional diagnostic methods exhibit limited sensitivity and specificity, raising big challenges for precise management of the patients. There is thus an urgent need to find out a timely and accurate diagnostic method in clinical practice. In this study, 163 patients suspected with IPA were enrolled. The medical data of the patients were retrieved from hospital information system. The 158 patients with complete data were classified into an IPA group with 122 cases (58 putative IPA, 19 probable IPA, and 45 possible IPA cases) and a non-IPA group with 36 cases. Cell-free DNA (cfDNA) of bronchoalveolar lavage fluid (BALF) or plasma samples was detected via a droplet digital PCR (ddPCR) assay targeting <em>Aspergillus</em> spp. Overall, this ddPCR assay demonstrated a higher sensitivity of 50.8 % for IPA diagnosis, compared with that of fungal culture (44.3 %) and smear test (10.7 %). Moreover, its sensitivity was higher in the IPA group (73.1 %) and putative IPA subgroup (88.2 %) when using BALF samples, compared with those using plasma samples (<em>P</em> < 0.01). It achieved a high specificity of 94.4 % for IPA diagnosis, with significant variations in cfDNA copy numbers across the subgroups (<em>P</em> < 0.05). In addition, the ddPCR results were associated with the prognosis of the patients at the discharge (<em>P</em> < 0.05). In conclusion, ddPCR assay demonstrated a good performance for IPA diagnosis when using BALF samples, especially for putative IPA. The ddPCR results could be integrated with clinical data to improve prognostic prediction.</div></div>","PeriodicalId":10205,"journal":{"name":"Clinica Chimica Acta","volume":"569 ","pages":"Article 120153"},"PeriodicalIF":3.2000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinica Chimica Acta","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0009898125000324","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Invasive pulmonary aspergillosis (IPA), the most common fungal infection, is associated with high mortality of affected patients. Traditional diagnostic methods exhibit limited sensitivity and specificity, raising big challenges for precise management of the patients. There is thus an urgent need to find out a timely and accurate diagnostic method in clinical practice. In this study, 163 patients suspected with IPA were enrolled. The medical data of the patients were retrieved from hospital information system. The 158 patients with complete data were classified into an IPA group with 122 cases (58 putative IPA, 19 probable IPA, and 45 possible IPA cases) and a non-IPA group with 36 cases. Cell-free DNA (cfDNA) of bronchoalveolar lavage fluid (BALF) or plasma samples was detected via a droplet digital PCR (ddPCR) assay targeting Aspergillus spp. Overall, this ddPCR assay demonstrated a higher sensitivity of 50.8 % for IPA diagnosis, compared with that of fungal culture (44.3 %) and smear test (10.7 %). Moreover, its sensitivity was higher in the IPA group (73.1 %) and putative IPA subgroup (88.2 %) when using BALF samples, compared with those using plasma samples (P < 0.01). It achieved a high specificity of 94.4 % for IPA diagnosis, with significant variations in cfDNA copy numbers across the subgroups (P < 0.05). In addition, the ddPCR results were associated with the prognosis of the patients at the discharge (P < 0.05). In conclusion, ddPCR assay demonstrated a good performance for IPA diagnosis when using BALF samples, especially for putative IPA. The ddPCR results could be integrated with clinical data to improve prognostic prediction.
期刊介绍:
The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)
Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells.
The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.