دورية أكاديمية
Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis.
| العنوان: | Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis. |
|---|---|
| المؤلفون: | Mwanga EP; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania. emwanga@ihi.or.tz., Minja EG; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania., Mrimi E; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania., Jiménez MG; School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK., Swai JK; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania., Abbasi S; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania., Ngowo HS; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania.; Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., Siria DJ; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania., Mapua S; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania.; School of Life Sciences, University of Keele, Keele, Staffordshire, ST5 5BG, UK., Stica C; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania., Maia MF; KEMRI Wellcome Trust Research Programme, P.O. Box 230, Kilifi, 80108, Kenya.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus Roosevelt Drive, Oxford, OX3 7FZ, UK., Olotu A; KEMRI Wellcome Trust Research Programme, P.O. Box 230, Kilifi, 80108, Kenya.; Interventions and Clinical Trials Department, Ifakara Health Institute, Bagamoyo, Tanzania., Sikulu-Lord MT; School of Public Health, University of Queensland, Saint Lucia, Australia.; Department of Mathematics, Statistics and Computer Science, Marquette University, Wisconsin, USA., Baldini F; Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., Ferguson HM; Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., Wynne K; School of Chemistry, University of Glasgow, Glasgow, G12 8QQ, UK., Selvaraj P; Institute for Disease Modeling, Bellevue, WA, 98005, USA., Babayan SA; Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK., Okumu FO; Environmental Health and Ecological Sciences Department, Ifakara Health Institute, Morogoro, Tanzania. fredros@ihi.or.tz.; Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, G12 8QQ, UK. fredros@ihi.or.tz.; School of Public Health, University of Witwatersrand, Johannesburg, South Africa. fredros@ihi.or.tz. |
| المصدر: | Malaria journal [Malar J] 2019 Oct 07; Vol. 18 (1), pp. 341. Date of Electronic Publication: 2019 Oct 07. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: BioMed Central Country of Publication: England NLM ID: 101139802 Publication Model: Electronic Cited Medium: Internet ISSN: 1475-2875 (Electronic) Linking ISSN: 14752875 NLM ISO Abbreviation: Malar J Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: London : BioMed Central, [2002- |
| مواضيع طبية MeSH: | Supervised Machine Learning*, Dried Blood Spot Testing/*instrumentation , Malaria, Falciparum/*diagnosis , Plasmodium falciparum/*isolation & purification , Spectrophotometry, Infrared/*methods, Humans ; Logistic Models ; Malaria, Falciparum/blood ; Tanzania |
| مستخلص: | Background: Epidemiological surveys of malaria currently rely on microscopy, polymerase chain reaction assays (PCR) or rapid diagnostic test kits for Plasmodium infections (RDTs). This study investigated whether mid-infrared (MIR) spectroscopy coupled with supervised machine learning could constitute an alternative method for rapid malaria screening, directly from dried human blood spots. Methods: Filter papers containing dried blood spots (DBS) were obtained from a cross-sectional malaria survey in 12 wards in southeastern Tanzania in 2018/19. The DBS were scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) spectrometer to obtain high-resolution MIR spectra in the range 4000 cm -1 to 500 cm -1 . The spectra were cleaned to compensate for atmospheric water vapour and CO Results: Logistic regression was the best-performing model. Considering PCR as reference, the models attained overall accuracies of 92% for predicting P. falciparum infections (specificity = 91.7%; sensitivity = 92.8%) and 85% for predicting mixed infections of P. falciparum and Plasmodium ovale (specificity = 85%, sensitivity = 85%) in the field-collected specimen. Conclusion: These results demonstrate that mid-infrared spectroscopy coupled with supervised machine learning (MIR-ML) could be used to screen for malaria parasites in human DBS. The approach could have potential for rapid and high-throughput screening of Plasmodium in both non-clinical settings (e.g., field surveys) and clinical settings (diagnosis to aid case management). However, before the approach can be used, we need additional field validation in other study sites with different parasite populations, and in-depth evaluation of the biological basis of the MIR signals. Improving the classification algorithms, and model training on larger datasets could also improve specificity and sensitivity. The MIR-ML spectroscopy system is physically robust, low-cost, and requires minimum maintenance. |
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| معلومات مُعتمدة: | Grant No. MR/P025501/1 United Kingdom MRC_ Medical Research Council; WT200086/Z/15/Z United Kingdom WT_ Wellcome Trust; Grant No. WT102350/Z/13/Z United Kingdom WT_ Wellcome Trust; Grant No. OPP1099295 Howard Hughes Medical Institute (US) and Bill and Melinda Gates Foundation; MR/P025501/1 United Kingdom MRC_ Medical Research Council |
| فهرسة مساهمة: | Keywords: Attenuated total reflection-Fourier Transform Infrared spectrometer; Dried blood spots; Ifakara Health Institute; Malaria diagnosis; Mid-infrared spectroscopy; PCR; Plasmodium; Supervised machine learning |
| تواريخ الأحداث: | Date Created: 20191009 Date Completed: 20200128 Latest Revision: 20231014 |
| رمز التحديث: | 20240628 |
| مُعرف محوري في PubMed: | PMC6781347 |
| DOI: | 10.1186/s12936-019-2982-9 |
| PMID: | 31590669 |
| قاعدة البيانات: | MEDLINE |
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