Abstract
Background Antimicrobial resistance (AMR) is a major global health threat, but there is scarcity of laboratory surveillance data linked to clinical information to determine burden and inform interventions, especially from low-income and middle-income countries. The ACORN2 study sought to address this through prospective case-based surveillance in 19 hospitals across Africa and Asia to characterise drug-resistant infections by origin, clinical syndrome, patient age, outcome, and geographical location. Methods Patients were enrolled on selected wards and clinical data were collected daily for community-acquired infections (CAIs). Point prevalence surveys for hospital-acquired infections (HAIs) were conducted weekly. Mortality was assessed at discharge and after 28 days. Linked microbiology data were extracted from local laboratory databases. Primary descriptive analyses focused on WHO Global Antimicrobial Resistance and Use Surveillance System pathogen (target organism) bloodstream infections (BSIs). Comparisons were adjusted for clustering by site using random effects models. Findings Over 31 months, 41 907 infections were characterised from 41 032 admissions. Two-thirds were children (19 351; 47·2%) or neonates (6649; 16·2%). There were marked differences in pathogen incidence and antibiotic resistance when clinical infections were stratified by patient age category and infection origin (CAI/HAI). The highest rates of target organism AMR BSI were third-generation cephalosporin-resistant (3GC-R) Escherichia coli (718 56/100 000 blood cultured infection episodes), meticillin-resistant Staphylococcus aureus (586 89/100 000 blood cultured infection episodes), and 3GC-R Klebsiella pneumoniae (364 92/100 000 blood cultured infection episodes). In-hospital mortality was 13·1% (166/1265) in patients with target organism BSI versus 6·2% (1357/21 845) in those with negative blood cultures, p<0·0001. Interpretation ACORN2 has shown practical implementation of collecting linked clinical-laboratory AMR data in low-income and middle-income countries and identified a significant burden of WHO GLASS BSI. Adoption of the ACORN2 approach at scale might enhance use of diagnostic microbiology and improve the volume of clinical data included in national and global AMR surveillance datasets. Funding Wellcome.
| Original language | English |
|---|---|
| Article number | 101228 |
| Journal | The Lancet Microbe |
| DOIs | |
| Publication status | Accepted/In press - 2025 |
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In: The Lancet Microbe, 2025.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Prospective characterisation of drug-resistant bloodstream infections in Africa and Asia (ACORN2)
T2 - a surveillance network assessment
AU - Hopkins, Jill
AU - Lee, Sue J.
AU - Waithira, Naomi
AU - Painter, Chris
AU - Ling, Clare L.
AU - Roberts, Tamalee
AU - Miliya, Thyl
AU - Obeng-Nkrumah, Noah
AU - Opintan, Japheth A.
AU - Abbeyquaye, Emmanuel P.
AU - Hamers, Raph L.
AU - Saharman, Yulia Rosa
AU - Sinto, Robert
AU - Karyanti, Mulya Rahma
AU - Ibrahim, R. Fera
AU - Akech, Samuel O.
AU - Ashley, Elizabeth A.
AU - Douangnouvong, Anousone
AU - Choumlivong, Khamla
AU - Feasey, Nicholas A.
AU - Kululanga, Diana
AU - Lissauer, Samantha
AU - Karkey, Abhilasha
AU - Kunwar, Narayan
AU - Erakhaiwu, Justice Enosetale
AU - Okeke, Iruka N.
AU - Adebiyi, Ini
AU - Adekanmbi, Olukemi A.
AU - Oduola, Abiodun B.
AU - Ogunbosi, Babatunde Oluwatosin
AU - Ojifinni, Kehinde Abraham
AU - Tongo, Olukemi O.
AU - Ude, Ifeoma Azuka
AU - Aboderin, Aaron O.
AU - Adekanle, Olusegun
AU - Adeyemo, Adeyemi T.
AU - Edward, Sylvester S.
AU - Osagie, Ugowe
AU - Nguyen, Thi Hoa
AU - Pham, Ngoc Thach
AU - Tran, Van Giang
AU - Hoàng, Thị Lan Hương
AU - Trịnh, Hữu Tùng
AU - van Doorn, H. Rogier
AU - Turner, Paul
AU - Hopkins, Jill
AU - Lee, Sue J.
AU - Waithira, Naomi
AU - Painter, Chris
AU - Ling, Clare L.
AU - Roberts, Tamalee
AU - Miliya, Thyl
AU - Obeng-Nkrumah, Noah
AU - Opintan, Japheth A.
AU - Abbeyquaye, Emmanuel P.
AU - Hamers, Raph L.
AU - Saharman, Yulia R.
AU - Sinto, Robert
AU - Karyanti, Mulya R.
AU - Ibrahim, R. Fera
AU - Akech, Samuel O.
AU - Ashley, Elizabeth A.
AU - Douangnouvong, Anousone
AU - Choumlivong, Khamla
AU - Feasey, Nicholas A.
AU - Kululanga, Diana
AU - Lissauer, Samantha
AU - Karkey, Abhilasha
AU - Kunwar, Narayan
AU - Erakhaiwu, Justice E.
AU - Okeke, Iruka N.
AU - Adebiyi, Ini
AU - Adekanmbi, Olukemi A.
AU - Oduola, Abiodun B.
AU - Ogunbosi, Babatunde O.
AU - Ojifinni, Kehinde A.
AU - Tongo, Olukemi O.
AU - Ude, Ifeoma A.
AU - Aboderin, Aaron O.
AU - Adekanle, Olusegun
AU - Adeyemo, Adeyemi T.
AU - Edward, Sylvester S.
AU - Osagie, Ugowe
AU - Thi, Hoa Nguyen
AU - Pham, Ngoc Thach
AU - Tran, Van Giang
AU - Hoang Thi, Lan Huong
AU - Trinh, Huu Tung
AU - Rogier van Doorn, H.
AU - Turner, Paul
AU - Lubell, Yoel
AU - Celhay, Olivier
AU - Chamsukhee, Vanapol
AU - Wannapinij, Prapass
AU - Bran, Sambou
AU - Ngoun, Chanpheaktra
AU - Sar, Poda
AU - Bediako-Bowan, Antoinette A.A.
AU - Labi, Appiah Korang
AU - Dankwah, Thomas
AU - Fandoh, Maud E.
AU - Gakpo, Margaret
AU - Okine, Esther
AU - Tetteh, Francis M.
AU - Dewi, Fitri A.
AU - Karman, Michelle M.
AU - Mahpud, Nunung N.
AU - Valleri, Theresa
AU - Brevian, Kevin
AU - Indrajaya, Erika
AU - Janaria, Ikhlima P.
AU - Pangulu, Lili H.
AU - Sutanto, Samuel T.
AU - Tatodi, Martha F.A.
AU - Haliman, Cliff C.
AU - Karuniawati, Anis
AU - Khatib, Aulia
AU - Margono, Djiwa
AU - Tsaniy, Aghnia N.
AU - Indracahyani, Agustin
AU - Makarim, Iqbal A.
AU - Roza, Ro R.R.
AU - Saputri, Uci R.
AU - Susilo, Adityo
AU - Amulele, Anne V.
AU - Gachoki, Jackline W.
AU - Gumbi, Wilson
AU - Kamau, Stephen N.
AU - Kigo, Joyce W.
AU - Musyimi, Robert M.
AU - Mvera, Benedict C.
AU - Mwarumba, Salim Y.
AU - Ndumba, Linnytiffan M.
AU - Nyamwaya, Brian M.
AU - Inginia, Rachel M.
AU - Njuguna, James M.
AU - Katayi, Anthony S.
AU - Lubanga, Dickens I.
AU - Chang, Ko
AU - Chansamouth, Vilada
AU - Davong, Viengmon
AU - Phommachanh, Douangkham
AU - Sayarath, Manoloth
AU - Senesouphonh, Keovongmany
AU - Thammavongsa, Peeyanout
AU - Thanadabouth, Khamphong
AU - Vongphachanh, Susath
AU - Vongsouvath, Manivanh
AU - Choumlivong, Khamloune
AU - Manivanh, Loungnilanh
AU - Sibounheuang, Souphalack
AU - Vongxay, Phoutmany
AU - Xayyalarth, Sonesavanh
AU - Musicha, Patrick
AU - Dongol, Sabina
AU - Gyawali, Sushma
AU - Shrestha, Basudha
AU - Khanal, Basudha
AU - Ajiboye, Jola Ade J.
AU - Ogunleye, Veronica O.
AU - Adekola, Faith
AU - Aderinto, Abdulmumin A.
AU - Adeyemi, Fatima
AU - Ajakaiye, Blessing
AU - Alonge, Victoria
AU - Bamidele, Folasade
AU - Chike, Benedicta
AU - Elaturoti, Oluseyi
AU - Kazeem, Oluwatobiloba S.
AU - Kehinde, Aderemi O.
AU - Nwankwo, Aishetu
AU - Oladokun, Suliat
AU - Oladokun, Regina E.
AU - Ololo, Chinyelo
AU - Oluwalusi, Okainemen P.
AU - Omolawal, Olamide
AU - Oni, Oluwapelumi M.
AU - Adewale, Isaiah
AU - Anuforo, Anthony
AU - Ibrahim, Atinuke
AU - Ogunbiyi, Taiwo S.
AU - Popoola, Oluwafemi A.
AU - Kesteman, Thomas
AU - Nguyen, Phuong Mai
AU - Nguyen, Quynh Mai
AU - Thi, Tam Nguyen
AU - Nguyen Thi, Hong Thuong
AU - Pragasam, Agilakumari
AU - Trinh, Son Tung
AU - Vu Thi, Ngoc Bich
AU - Vu Tien, Viet Dung
AU - Dao, Thanh Hai
AU - Doan, Duy Thanh
AU - Dong, Phu Khiem
AU - Hoang, Thuy Trang
AU - Luong, Huong Giang
AU - Nguyen, Quoc Phuong
AU - Thi, Ha Nguyen
AU - Thi, Ngoc Ninh
AU - Thi, Dung Pham
AU - Phan, Manh Cuong
AU - Tran, Van Bac
AU - Van, Dinh Trang
AU - Duong, Thai Duy
AU - Hoang, Van Long
AU - Le Thi, Thu
AU - Mai, Van Tuan
AU - Nguyen, Tat Dung
AU - Nguyen, Thanh Dat
AU - Nguyen, Xuan Hien
AU - Nguyen Thi, Bach Oanh
AU - Nguyen Thi, Dieu Doan
AU - Thi, Huong Nguyen
AU - Nguyen Thi, Yen Lan
AU - Phan Le, Quynh Thi
AU - Thi, Phuong Phan
AU - Tran, Van Binh
AU - Tran, Quang Nhat
AU - Tran, Duc Huy
AU - Tran Thi, Huyen Tran
AU - Bui, The Trung
AU - Ho, Kieu Giang
AU - Ho Thi, Minh Thao
AU - Le, Ngoc Anh
AU - Le Thi, Hong Hanh
AU - Nguyen, Minh Ngoc
AU - Nguyen, Ha Duc
AU - Nguyen, Thanh Thien
AU - Nguyen Cao, Minh Uyen
AU - Nguyen Thi, Quynh Anh
AU - Nguyen Thi, Kim Nhi
AU - Nguyen Thi, Kim Anh
AU - Nguyen Thi, Dieu Truong
AU - Thi, Nhieu Nguyen
AU - Nguyen Thi, Lan Phuong
AU - Nguyen Thi, Thuy Trang
AU - Pham Thi, Duc Loi
AU - Tran Thi, Bich Kim
AU - Trinh Thi, Hong Phuong
N1 - Publisher Copyright: © 2025 The Author(s).
PY - 2025
Y1 - 2025
N2 - Background Antimicrobial resistance (AMR) is a major global health threat, but there is scarcity of laboratory surveillance data linked to clinical information to determine burden and inform interventions, especially from low-income and middle-income countries. The ACORN2 study sought to address this through prospective case-based surveillance in 19 hospitals across Africa and Asia to characterise drug-resistant infections by origin, clinical syndrome, patient age, outcome, and geographical location. Methods Patients were enrolled on selected wards and clinical data were collected daily for community-acquired infections (CAIs). Point prevalence surveys for hospital-acquired infections (HAIs) were conducted weekly. Mortality was assessed at discharge and after 28 days. Linked microbiology data were extracted from local laboratory databases. Primary descriptive analyses focused on WHO Global Antimicrobial Resistance and Use Surveillance System pathogen (target organism) bloodstream infections (BSIs). Comparisons were adjusted for clustering by site using random effects models. Findings Over 31 months, 41 907 infections were characterised from 41 032 admissions. Two-thirds were children (19 351; 47·2%) or neonates (6649; 16·2%). There were marked differences in pathogen incidence and antibiotic resistance when clinical infections were stratified by patient age category and infection origin (CAI/HAI). The highest rates of target organism AMR BSI were third-generation cephalosporin-resistant (3GC-R) Escherichia coli (718 56/100 000 blood cultured infection episodes), meticillin-resistant Staphylococcus aureus (586 89/100 000 blood cultured infection episodes), and 3GC-R Klebsiella pneumoniae (364 92/100 000 blood cultured infection episodes). In-hospital mortality was 13·1% (166/1265) in patients with target organism BSI versus 6·2% (1357/21 845) in those with negative blood cultures, p<0·0001. Interpretation ACORN2 has shown practical implementation of collecting linked clinical-laboratory AMR data in low-income and middle-income countries and identified a significant burden of WHO GLASS BSI. Adoption of the ACORN2 approach at scale might enhance use of diagnostic microbiology and improve the volume of clinical data included in national and global AMR surveillance datasets. Funding Wellcome.
AB - Background Antimicrobial resistance (AMR) is a major global health threat, but there is scarcity of laboratory surveillance data linked to clinical information to determine burden and inform interventions, especially from low-income and middle-income countries. The ACORN2 study sought to address this through prospective case-based surveillance in 19 hospitals across Africa and Asia to characterise drug-resistant infections by origin, clinical syndrome, patient age, outcome, and geographical location. Methods Patients were enrolled on selected wards and clinical data were collected daily for community-acquired infections (CAIs). Point prevalence surveys for hospital-acquired infections (HAIs) were conducted weekly. Mortality was assessed at discharge and after 28 days. Linked microbiology data were extracted from local laboratory databases. Primary descriptive analyses focused on WHO Global Antimicrobial Resistance and Use Surveillance System pathogen (target organism) bloodstream infections (BSIs). Comparisons were adjusted for clustering by site using random effects models. Findings Over 31 months, 41 907 infections were characterised from 41 032 admissions. Two-thirds were children (19 351; 47·2%) or neonates (6649; 16·2%). There were marked differences in pathogen incidence and antibiotic resistance when clinical infections were stratified by patient age category and infection origin (CAI/HAI). The highest rates of target organism AMR BSI were third-generation cephalosporin-resistant (3GC-R) Escherichia coli (718 56/100 000 blood cultured infection episodes), meticillin-resistant Staphylococcus aureus (586 89/100 000 blood cultured infection episodes), and 3GC-R Klebsiella pneumoniae (364 92/100 000 blood cultured infection episodes). In-hospital mortality was 13·1% (166/1265) in patients with target organism BSI versus 6·2% (1357/21 845) in those with negative blood cultures, p<0·0001. Interpretation ACORN2 has shown practical implementation of collecting linked clinical-laboratory AMR data in low-income and middle-income countries and identified a significant burden of WHO GLASS BSI. Adoption of the ACORN2 approach at scale might enhance use of diagnostic microbiology and improve the volume of clinical data included in national and global AMR surveillance datasets. Funding Wellcome.
UR - https://www.scopus.com/pages/publications/105025159592
U2 - 10.1016/j.lanmic.2025.101228
DO - 10.1016/j.lanmic.2025.101228
M3 - Article
AN - SCOPUS:105025159592
SN - 2666-5247
JO - The Lancet Microbe
JF - The Lancet Microbe
M1 - 101228
ER -