A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia.
BACKGROUND:Distinguishing arboviral infections from bacterial causes of febrile illness is of great importance for clinical management. The Infection Manager System (IMS) is a novel diagnostic algorithm equipped on a Sysmex hematology analyzer that evaluates the host response using novel techniques...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2019-03-01
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| Series: | PLoS Neglected Tropical Diseases |
| Online Access: | http://europepmc.org/articles/PMC6435198?pdf=render |
| _version_ | 1818580814724595712 |
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| author | Susantina Prodjosoewojo Silvita F Riswari Hofiya Djauhari Herman Kosasih L Joost van Pelt Bachti Alisjahbana Andre J van der Ven Quirijn de Mast |
| author_facet | Susantina Prodjosoewojo Silvita F Riswari Hofiya Djauhari Herman Kosasih L Joost van Pelt Bachti Alisjahbana Andre J van der Ven Quirijn de Mast |
| author_sort | Susantina Prodjosoewojo |
| collection | DOAJ |
| description | BACKGROUND:Distinguishing arboviral infections from bacterial causes of febrile illness is of great importance for clinical management. The Infection Manager System (IMS) is a novel diagnostic algorithm equipped on a Sysmex hematology analyzer that evaluates the host response using novel techniques that quantify cellular activation and cell membrane composition. The aim of this study was to train and validate the IMS to differentiate between arboviral and common bacterial infections in Southeast Asia and compare its performance against C-reactive protein (CRP) and procalcitonin (PCT). METHODOLOGY/PRINCIPAL FINDINGS:600 adult Indonesian patients with acute febrile illness were enrolled in a prospective cohort study and analyzed using a structured diagnostic protocol. The IMS was first trained on the first 200 patients and subsequently validated using the complete cohort. A definite infectious etiology could be determined in 190 of 463 evaluable patients (41%), including 89 arboviral infections (81 dengue and 8 chikungunya), 94 bacterial infections (26 murine typhus, 16 salmonellosis, 6 leptospirosis and 46 cosmopolitan bacterial infections), 3 concomitant arboviral-bacterial infections, and 4 malaria infections. The IMS detected inflammation in all but two participants. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the IMS for arboviral infections were 69.7%, 97.9%, 96.9%, and 77.3%, respectively, and for bacterial infections 77.7%, 93.3%, 92.4%, and 79.8%. Inflammation remained unclassified in 19.1% and 22.5% of patients with a proven bacterial or arboviral infection. When cases of unclassified inflammation were grouped in the bacterial etiology group, the NPV for bacterial infection was 95.5%. IMS performed comparable to CRP and outperformed PCT in this cohort. CONCLUSIONS/SIGNIFICANCE:The IMS is an automated, easy to use, novel diagnostic tool that allows rapid differentiation between common causes of febrile illness in Southeast Asia. |
| first_indexed | 2024-12-16T07:23:35Z |
| format | Article |
| id | doaj.art-3d016313a7e54a7f8d88a53a144ad6dd |
| institution | Directory Open Access Journal |
| issn | 1935-2727 1935-2735 |
| language | English |
| last_indexed | 2024-12-16T07:23:35Z |
| publishDate | 2019-03-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Neglected Tropical Diseases |
| spelling | doaj.art-3d016313a7e54a7f8d88a53a144ad6dd2022-12-21T22:39:34ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352019-03-01133e000718310.1371/journal.pntd.0007183A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia.Susantina ProdjosoewojoSilvita F RiswariHofiya DjauhariHerman KosasihL Joost van PeltBachti AlisjahbanaAndre J van der VenQuirijn de MastBACKGROUND:Distinguishing arboviral infections from bacterial causes of febrile illness is of great importance for clinical management. The Infection Manager System (IMS) is a novel diagnostic algorithm equipped on a Sysmex hematology analyzer that evaluates the host response using novel techniques that quantify cellular activation and cell membrane composition. The aim of this study was to train and validate the IMS to differentiate between arboviral and common bacterial infections in Southeast Asia and compare its performance against C-reactive protein (CRP) and procalcitonin (PCT). METHODOLOGY/PRINCIPAL FINDINGS:600 adult Indonesian patients with acute febrile illness were enrolled in a prospective cohort study and analyzed using a structured diagnostic protocol. The IMS was first trained on the first 200 patients and subsequently validated using the complete cohort. A definite infectious etiology could be determined in 190 of 463 evaluable patients (41%), including 89 arboviral infections (81 dengue and 8 chikungunya), 94 bacterial infections (26 murine typhus, 16 salmonellosis, 6 leptospirosis and 46 cosmopolitan bacterial infections), 3 concomitant arboviral-bacterial infections, and 4 malaria infections. The IMS detected inflammation in all but two participants. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the IMS for arboviral infections were 69.7%, 97.9%, 96.9%, and 77.3%, respectively, and for bacterial infections 77.7%, 93.3%, 92.4%, and 79.8%. Inflammation remained unclassified in 19.1% and 22.5% of patients with a proven bacterial or arboviral infection. When cases of unclassified inflammation were grouped in the bacterial etiology group, the NPV for bacterial infection was 95.5%. IMS performed comparable to CRP and outperformed PCT in this cohort. CONCLUSIONS/SIGNIFICANCE:The IMS is an automated, easy to use, novel diagnostic tool that allows rapid differentiation between common causes of febrile illness in Southeast Asia.http://europepmc.org/articles/PMC6435198?pdf=render |
| spellingShingle | Susantina Prodjosoewojo Silvita F Riswari Hofiya Djauhari Herman Kosasih L Joost van Pelt Bachti Alisjahbana Andre J van der Ven Quirijn de Mast A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia. PLoS Neglected Tropical Diseases |
| title | A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia. |
| title_full | A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia. |
| title_fullStr | A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia. |
| title_full_unstemmed | A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia. |
| title_short | A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia. |
| title_sort | novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in southeast asia |
| url | http://europepmc.org/articles/PMC6435198?pdf=render |
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