| Literature DB >> 33239106 |
Olawale Salami1, Philip Horgan2, Catrin E Moore2, Abhishek Giri3, Asadu Sserwanga4, Ashish Pathak5, Buddha Basnyat3, Francois Kiemde6, Frank Smithuis7, Freddy Kitutu8, Gajanan Phutke9, Halidou Tinto6, Heidi Hopkins10, James Kapisi4, Myo Maung Maung Swe7, Neelam Taneja11, Rita Baiden12, Shanta Dutta13, Adelaide Compaore10, David Kaawa-Mafigiri14, Rashida Hussein7, Summita Udas Shakya3, Vida Kukula15, Stefano Ongarello1, Anjana Tomar16, Sarabjit S Chadha16, Kamini Walia17, Cassandra Kelly-Cirino1, Piero Olliaro18.
Abstract
BACKGROUND: The management of acute febrile illnesses places a heavy burden on clinical services in many low- and middle-income countries (LMICs). Bacterial and viral aetiologies of acute fevers are often clinically indistinguishable and, in the absence of diagnostic tests, the 'just-in-case' use of antibiotics by many health workers has become common practice, which has an impact on drug-resistant infections. Our study aims to answer the following question: in patients with undifferentiated febrile illness presenting to outpatient clinics/peripheral health centres in LMICs, can we demonstrate an improvement in clinical outcomes and reduce unnecessary antibiotic prescription over current practice by using a combination of simple, accurate diagnostic tests, clinical algorithms, and training and communication (intervention package)?Entities:
Keywords: Antibiotic prescription; Antimicrobial resistance; Febrile illness; Outpatient fever management; Randomized controlled trial
Mesh:
Year: 2020 PMID: 33239106 PMCID: PMC7687811 DOI: 10.1186/s13063-020-04897-9
Source DB: PubMed Journal: Trials ISSN: 1745-6215 Impact factor: 2.279
List of clinical trial sites, their locations and age ranges of participants
| Country | Uganda | Nepal | Myanmar | Ghana | Burkina Faso | India | |||
| Institution | Infectious Diseases Research Collaboration (IDRC) | Oxford University Clinical Research Unit-Nepal | Myanmar Oxford Clinical Research Unit (MOCRU) and Medical Action Myanmar (MAM) | Dodowa Health Research Centre | IRSS-DRCO/Clinical Research Unit of Nanoro (CRUN) | Chhattisgarh: Jan Swasthya Sahyog (JSS) | Chandigarh: Post Graduate Institute of Medical Education & Research (PGIMER) | Madhya Pradesh: RD Gardi medical college | West Bengal: National Institute for Cholera and Enteric Diseases (NICED) |
| Number of recruiting sites | 3 | 1 | 4 | 2 | 2 | 4 | 1 | 1 | 2 |
| Nature of recruiting sites | Health centres in three regions (two rural and one peri-urban) with varied geography and malaria endemicity, outside Kampala | Large, urban teaching hospital in Kathmandu | NGO supported, stand-alone clinics located in peri-urban areas, and one hospital in Yangon | one regional referral hospital in greater Accra, and one rural hospital | Rural, health centres 90 km from the capital | Rural health centres | Teaching hospital for urban and rural patients | Urban medical college | Small clinics located in urban slums in Kolkata |
| Age ranges included | all ages > 1 year | all ages > 6 months | all ages > 1 year | 6 months to 18 years | 6 months to 18 years | 6 months to 18 years | all ages > 6 months | all ages > 3 months | 6 months to 18 years |
Pathogen-specific point-of-care (POC) tests
| Pathogen | Type of test |
|---|---|
| Dengue virus | Lateral flow RDT: detects Dengue virus NS1 antigen and IgM (and IgG) from serum or whole blood |
| Lateral flow RDT: detects group A streptococcal antigen from throat swabs | |
| Lateral flow RDT: detects | |
| Lateral flow RDT: detects | |
| Influenza virus | Lateral flow RDT: detects influenza virus type A, type B and A(H1N1) pandemic antigens directly from nasal/throat/nasopharyngeal swab or nasal/nasopharyngeal aspirate |
| Chikungunya virus | Lateral flow RDT: detects Chikungunya virus IgG/IgM antibodies in serum, plasma or whole blood |
| Lateral flow RDT: detects | |
| Respiratory syncytial virus | Lateral flow RDT: detects respiratory syncytial virus (RSV) fusion protein antigen in nasal wash and nasopharyngeal (NP) swab specimens |
| Lateral flow RDT: detects | |
| Lateral flow RDT as per national guidelines |
Fig. 1Outline of diagnostic and clinical algorithm. RSV, respiratory syncytial virus; GAS, group A streptococci; CRP, C-reactive protein; WBC/DIFF, white blood cells total counts/differential counts; Rx, treatment; ATB, antibiotic; Y, prescribe antibiotic; N, antibiotic prescription not warranted; P, antibiotic prescription possible if clinically indicated
Fig. 2Study participant flow
Timeline for study participants
| Schedule of events | |||
|---|---|---|---|
| Day 0 visit | Day 7 visit (+/− 2 days) | Unscheduled visit | |
| Informed consent and enrolment | x | ||
| Demographic data collection | x | ||
| History/physical examination | x | x | x |
| Diagnostic tests | x | ||
| Treatment prescription | x | x | |
| Patient adherence evaluation | x | x | |
| Collection of qualitative data | x | x | |
| Delivery of communication messages | x | ||
| Adverse event monitoring (see | x | x | |
Fig. 3Sample size chart
Baseline antibiotic prescription rates for acute febrile illnesses
| Country | Expected antibiotic prescription rate in control arm (based on historic prescribing) | Reduction in prescribing | Total sample size (both arms, including losses to follow-up) | ||
|---|---|---|---|---|---|
| Nepal | 55% | 30% | 1760 | 1760 | 3520 |
| Uganda | 73% | 30% | 1200 (combined) | 2400 | |
| Ghana | 43% | 30% | 1383 | n/a | 2766 |
| Burkina Faso | 77% | 30% | 859 | n/a | 1718 |
| Myanmar | 43% | 30% | 440 | 440 | 1760 |
| India JSS | 50% | 30% | 864 | n/a | 1728 |
| India PGIMER | 50% | 30% | 864 | 864 | 3456 |
| India RD Gardi | 20% (children), 40% (adults) | 30% | 553 | 831 | 2768 |
| India NICED | 50% | 30% | 880 | n/a | 1760 |
| Total | 21,876 | ||||
Populations for statistical analyses
| Population | Description |
|---|---|
| 1. Enrolled | All participants who sign the ICF |
| 2. Randomly assigned to trial intervention (RAI) | Randomized to either intervention or control arm |
| 3. Modified intent to treat (mITT) | Participants in RAI with partial data (but not fully compliant with the protocol) |
| 4. Evaluable per protocol population (PP) | All participants who fully complied with the protocol |
| 5. Safety population for analysis | All participants randomly assigned to trial intervention. Participants will be analysed according to the intervention they actually received. |