Increased Tuberculosis Case Detection - a Cluster-randomized Trial Combining Available Resources and Novel Strategies for High Endemic Areas
Phase: NA
Conditions: Tuberculosis
Sponsor: Aarhus University Hospital

Version 17 230524 
  
 
Increased Tuberculosis Case Detection 
- a cluster-randomized trial combining available 
resources and novel strategies for high endemic 
areas 
DiOpTB 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Protocol for a multi-centre, cluster-randomized clinical trial and PhD-project 
Department of Infectious Diseases, Aarhus University Hospital, Aarhus University, Linköping University, Gondar 
University and Bandim Health Project 

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Table of Contents 
1 Summary ......................................................................................................................................................... 4 
2 Objectives ....................................................................................................................................................... 4 
2.1 Primary objective ..................................................................................................................................... 4 
2.2 Secondary objectives ............................................................................................................................... 4 
3 Background ..................................................................................................................................................... 5 
4 Methods.......................................................................................................................................................... 6 
4.1 Location and nature of sites .................................................................................................................... 6 
4.2 Epidemiology and study population ........................................................................................................ 6 
4.2.1 Guinea-Bissau ................................................................................................................................... 6 
4.2.2 Ethiopia ............................................................................................................................................. 7 
4.3 Design ...................................................................................................................................................... 7 
4.4 Bandim TBscore ....................................................................................................................................... 8 
4.5 Buccal, tongue swap and saliva sample .................................................................................................. 9 
4.6 Computer-aided detection chest X-ray (CAD CXR) applying artificial intelligence (AI) ......................... 10 
4.7 Enrolment .............................................................................................................................................. 10 
4.7.1 Enhanced Usual Diagnostic Procedure (EUDP) .............................................................................. 10 
4.7.2 The Optimized Diagnostic Procedure (ODP) intervention .............................................................. 10 
4.7.3 Implementation of the ODP and EUDP .......................................................................................... 11 
 ................................................................................................................................................................. 13 
4.7.4 Inclusion criteria ............................................................................................................................. 14 
4.7.5 Exclusion criteria ............................................................................................................................. 14 
5 Outcomes ..................................................................................................................................................... 14 
5.1 Primary outcomes ................................................................................................................................. 14 
5.2 Secondary outcomes ............................................................................................................................. 14 
6 Sample size and statistical analyses ............................................................................................................. 14 
7 Timeframe .................................................................................................................................................... 15 
8 Public health importance ............................................................................................................................. 16 
8.1 Major advances ..................................................................................................................................... 16 
8.2. New approach ...................................................................................................................................... 16 
8.3. Generalizability of trial results .............................................................................................................. 16 
8.4. Contribution to improved disease management and public health .................................................... 16 

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8.5 Improvements in patient care ............................................................................................................... 17 
9 Ethical considerations ................................................................................................................................... 17 
10 Capacity Building and future implications .................................................................................................. 17 
11 The Nordic collaboration and study group ................................................................................................. 17 
12 Exploiting and disseminating the project results ....................................................................................... 19 
13 References .................................................................................................................................................. 20 
 

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1 Summary 
As estimated by the WHO 10.6 million new Tuberculosis (TB) cases were identified in 2022– while 
more than three million went undetected and untreated. The low detection rate illustrates the 
failure to recognise and diagnose TB in the current cascade of healthcare and is a major obstacle to 
effective TB control programs. This multi-centre cluster-randomised clinical trial will evaluate the 
effect (i.e., diagnostic yield) of improving the point-of-care diagnostics already in place in most 
primary health-care centres in low-resource settings. The present study will be conducted in two 
different geographical settings in the Western and Eastern African countries of Guinea Bissau and 
Ethiopia. This improved clinical diagnostic pathway may improve case detection rates at primary 
healthcare level, ensuring prompt commencement of treatment, thereby diminishing transmission 
risk in the community and improving treatment outcomes. The Optimized Diagnostic Procedure 
(ODP) will utilize instructed sputum sampling and pooling as well as computer-aided detection (CAD) 
chest X-ray (CXR) and additional pooled sputum sample as well as non-sputum sampling (faecal and 
a buccal/tongue swab and saliva) for GeneXpert Ultra PCR (Xpert) as state-of-the-art add-ons to the 
routine diagnostic pathway for TB. This adds to the key components of the WHO “End TB” strategy 
– early diagnosis – and if successful, may be rapidly approved by the WHO and implemented by 
governments globally with potentially major public health benefits. 
The study will be conducted in close liaison with the national Ministries of Health and TB programs 
in Guinea-Bissau and Ethiopia. This will facilitate any relevant findings to be taken forward for 
implementation into policy and practice. Capacity development, training and educational activities 
will be closely aligned to this study.  
2 Objectives 
2.1 Primary objective 
1. Diagnostic yield of active TB within ten days, comparing Enhanced Usual Diagnostic 
Procedure (EUDP) to Optimized Diagnostic Procedure (ODP). 
2.2 Secondary objectives 
1. Number of patients treated for TB within two weeks comparing EUDP to ODP.  
2. The additional diagnostic yield of CAD CXR compared to Xpert and culture.  
3. Improved follow-up (FU) rates in the cascade of care (i.e., one week and six months FU for 
all included and treatment start and outcome for all TB diagnosed). 

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4. Differences in diagnostic yield of active TB between routine sputum samples, instructed 
sputum samples and non-sputum samples (faecal and saliva combined with buccal/tongue 
swabs). 
5. Feasibility of including Oxford Nanopore sequencing for detection and molecular resistance 
patterns measured as rate of analysed samples within two weeks. 
3 Background 
In 2022, the WHO estimated that of a total 10.6 million new TB cases, more than three million went 
undiagnosed and of the remaining seven million only 57% were bacteriologically confirmed (1). In 
sub-Saharan African settings such as Ethiopia and Guinea Bissau, smear microscopy remains the 
major diagnostic tool in most areas despite the rollout of rapid diagnostic tests such as Xpert. In a 
multi-centre trial by Theron et al, the implementation of Xpert in African settings did indeed reduce 
diagnostic delay but unfortunately without any effect on the numbers who were initiated on TB 
treatment nor on mortality (2). The trial showed that Xpert rollout was not superior to enhanced, 
well-equipped, microscopy-based diagnostic facilities. In an editorial to the Lancet written by our 
group, it was concluded that TB elimination could be better advanced by improving currently 
available tools than by expanding Xpert testing to peripheral health facilities (2, 3). Nevertheless, 
when TB is diagnosed with a point of care test, there is a need to ensure that correct treatment is 
provided. However, culture-based drug susceptibility testing is very scarce in high endemic areas 
and often takes several weeks or months to perform (4). Recently, the Cryptic study (5) has shown 
that genotypic drug susceptibility testing (gDST) may guide treatment with a sensitivity and 
specificity well above 90% for key drugs. New techniques such as MinION (Oxford Nanopore 
Technologies) have also made it possible to perform sequencing and gDST directly from sputum 
samples. Such point-of-care-based sequencing technology is comparable in size to a USB flash drive 
(6)  and may be attached to a laptop computer at a health centre in a high endemic area.  
A cluster-randomised trial implementing the TBscore recently showed a fourfold increase in case 
detection rate in Ethiopia but not in Guinea-Bissau (7). It identified that factors such as laboratory 
capacity and routines in collecting and examining sputum smear samples may have a high impact 
on case detection rate and could be optimized based on the available resources. Surprisingly, the 
sensitivity of sputum smear microscopy ranges from 20-80% with an average of about 50% (8), 
which may partly be due to patient selection but also depend on considerable variability in sputum 
collection strategies and/or laboratory procedures. In a comparison of sputum collection methods 

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by Datta et al (9), pooling of sputum and structured instructions before sampling on average led to 
a twofold higher diagnostic yield whereas a spot versus morning sample showed no difference. A 
multi-centre study including Ethiopia, comparing fluorescence microscopy to conventional light 
microscopy showed a small but significant increase in sensitivity (72.8 vs 65.8%)(10). Further, recent 
research has shown that buccal and tongue swabs, that are easily obtained, can hold valuable 
diagnostic potential. (11) In smear-negative patients with presumed TB, the available diagnostic 
tools in high endemic countries include CXR but standardized procedures for evaluation of CXR have 
been scarce. Recently, CAD software based on artificial intelligence algorithms such as qXR (Qure.ai, 
India) have improved detection of microbiologically confirmed TB from 50-60% by experienced 
radiologists to 70-84% with a specificity of 80% by CAD (12). However, a recent systematic review 
concluded as did the WHO that there are too few high-quality studies to fully assess its diagnostic 
accuracy (13). We now propose to conduct a multi-centre cluster-randomised clinical trial to 
evaluate whether improvements on available diagnostic resources can increase the diagnostic yield 
of active TB and decrease mortality for patients diagnosed with TB. 
4 Methods 
4.1 Location and nature of sites 
The present study will be conducted in two African countries: Guinea-Bissau and Ethiopia. In Bissau, 
the capital of Guinea-Bissau, The Bandim Health Project has been a Health and Demographic 
Surveillance Site (HDSS) for 45 years and has a well-defined study population of approximately 
100,000 under continued surveillance. Within the study area there are two health centres (HCs) 
from where patients with presumed TB will be enrolled (Bandim HC, Belem HC). 
In Ethiopia the study will be conducted in collaboration with the University of Gondar in the region 
of North-Gondar, which has a population of more than two million. Two health centres located in 
North Gondar Zone, namely Azezo HC and Gondar HC will participate. The Gondar University 
Hospital is a teaching and referral hospital and will be used for further management of severe TB 
cases during this study. 
 
4.2 Epidemiology and study population 
4.2.1 Guinea-Bissau 
The epidemiology of TB in the Bissau study population has been extensively described (14-18). The 
overall incidence of TB has declined only slightly since 2004 and was estimated at 273/100,000 

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population in 2020, while TB/HIV co-infection declined from 108 per 100.000 to 14 per 100,000 over 
the period (19). Smear negative cases and case fatality rate likewise declined over the period. The 
incidence of smear positive TB remained stable at 188 per 100,000 between 2004 and 2011 (20). All 
HCs have basic laboratory facilities to carry out sputum smear microscopy and all provide TB 
treatment. The national referral hospital for TB, Hospital Raoul Follereau, is located adjacent to the 
study area and is a close collaborating partner. The incidence rate of TB in Guinea-Bissau as a whole 
is 361 per 100,000 with a case detection rate estimated at 35% (21, 22). 
4.2.2 Ethiopia 
TB continues to be a major public health concern in Ethiopia fuelled by the expansion of the HIV 
epidemic since the 1990s. According to the 2022 WHO TB report (1), Ethiopia is among high-burden 
countries for both TB and TB/HIV and has an estimated incidence rate of 119 per 100,000, and a TB 
mortality of 17.7 per 100,000 (21). HIV-positive TB incidence is 6.2 per 100,000 and case detection 
rate is currently estimated at 73% (21, 22). These figures are high considering that Ethiopia is the 
second most populous country in Africa with an estimated total population size of more than 100 
million. HIV screening is carried out as a routine.  
4.3 Design 
The present study is designed as an open-label, stepped-wedge cluster-randomised controlled trial 
(23) to investigate an optimized diagnostic procedure for active TB in healthcare centres in Guinea-
Bissau and Ethiopia. Applying the stepped-wedge design ensures that all participating HCs will 
implement the intervention during the study period. This design is particularly useful for evaluating 
the population-level impact of an intervention, which is of interest in this study. All clusters (i.e., 
HCs) start with Enhanced Usual Diagnostic Procedure (EUDP) and are then randomized to switch to 
the intervention phase at predefined time points (see table 1). 
See below for detailed description of sample size calculations. 
 
 
 
 
 

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Table 1 Intervention implementation by cluster 
Date 
Commencing 
03/06/2024 
– 
03/11/2024 
04/11/2024 
– 
06/04/2025 
07/04/2025 
– 
07/09/2025 
Week 
1-22 
23-45 
46-68 
Cluster/HC 
1 
0 
1 
1 
2 
0 
1 
1 
3 
0 
0 
1 
4 
0 
0 
1 
Week 
1-22 
23-45 
46-68 
 
4.4 Bandim TBscore 
The Bandim TBscore (TBscore) (Table 2) consists of five symptoms (cough, haemoptysis, dyspnoea, 
chest pain, and night sweats) and six signs (pale inferior conjunctivae, pulse >100 per minute, 
positive finding at lung auscultation, temperature >37°C (axillary), body mass index (BMI) <18/<16, 
and mid-upper-arm circumference (MUAC) <220 mm/<200 mm) (24). Each variable contributes one 
point while BMI and MUAC contribute an additional point if BMI<16/MUAC<200 mm; hence, the 
maximum score is 13. The score divides patients into three severity classes (SC): SC-I, TBscore 0-5; 
SC-II, TBscore 6-7, and SC-III, TBscore≥8. A simplified version of the score – TBscoreII – with a 
maximum score of 8 points has also been developed (25). The advantage of the latter score is that 
it can be performed without a physician present. The TBscore has been assessed in both Gondar 
and Bissau and found to be a useful add on in the diagnostic cascade of care.(7) 
 
 
 
 
 
 
 
 
 

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Table 2 Bandim TBscore – symptoms and signs. 
Variables included 
TBscore 
TBscoreII 
Symptoms 
 
 
  Cough 
1 
1 
  Haemoptysis 
1 
- 
  Dyspnoea 
1 
1 
  Chest pain 
1 
1 
  Night sweats 
1 
- 
Signs 
 
 
  Anemia 
1 
1 
  Pulse >100 beats/min 
1 
- 
  Positive finding at lung auscultation 
1 
- 
  Temperature >37°C 
1 
- 
  BMI<18 
1 
1 
  BMI<16 
1 
1 
  MUAC<220 mm 
1 
1 
  MUAC<200 mm 
1 
1 
Total number of points possible 
13 
8 
BMI=body mass index; MUAC=mid upper arm circumference. 
 
 
4.5 Buccal, tongue swap and saliva sample 
Buccal and tongue samples will be collected using the Omniswab (Whatman, catalogue 
#WB100035) and added to a container where patients leave a saliva sample. Samples will be 
collected by trained laboratory staff, who gently brush the inside of each cheek and then the 
tongue of the participant for 10 seconds with the OmniSwab. The OmniSwab has a breakpoint and 
the head will be ejected into 500 µl buffer containing 50 mM Tris pH 8.0, 50 mM EDTA, 50 mM 
sucrose, 100 mM NaCl, and 1% SDS, and transported to the laboratory at 4˚C. (11) There, the 
OmniSwab-collected samples will be vortexed in the saliva, and the swabs heads removed. One 
part of the sample will be analyzed using Xpert Ultrawhile the other part will be stored at – 80 °C 
until further processing.  

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4.6 Computer-aided detection chest X-ray (CAD CXR) applying artificial 
intelligence (AI) 
A preliminary study using an AI based CAD CXR software (qXR, Qure) compared to two Ethiopian 
radiologists included 498 CXRs from a previously performed randomized controlled trial on the 
TBscore. Of those, the less experienced radiologist found 50, the more experienced radiologist 
found 100 and CAD CXR found 83 to be indicative of TB. Using Xpert PCR as the gold standard for TB 
diagnosis, the overall AUC for the CAD CXR was 0.84 while the less experienced radiologist 
performed at a sensitivity of 41.4% and a specificity of 94.1% and the experienced radiologist’s 
assessments were 55.2% sensitive and 85.0% specific. The agreement between the radiologists was 
moderate (=0.45), as was the agreement between each radiologist and the software (=0.36, 
=0.59). 
In the present study we will include a mobile phone app to guide photographing analog X-ray films. 
These photographs will then be uploaded to a locally placed box (qbox) and analyzed on site. 
4.7 Enrolment 
At all sites adult patients will be screened during consultations carried out at primary healthcare 
centres. All patients presenting with cough of any duration, sputum production, or weight loss will 
have their TBscore assessed. All participating health centres have previous experience collecting the 
symptoms and signs necessary for the TBscore and completing a score chart from which the TBscore 
can be calculated. All patients with a TBscore≥4 will be referred for TB diagnostics. Patients with 
4≤TBscore<6 will be referred to fluorescence microscopy while patients with TBscore≥6 will be 
referred to Xpert PCR. The staff at the sites will receive general training in TB diagnosis and then the 
healthcare facilities will, following a random sequence, switch from Enhanced Usual Diagnostic 
Procedure (EUDP), consisting of standard TB program diagnostics but ensuring availability of all 
reagents, to intervention (i.e., OPD).  
4.7.1 Enhanced Usual Diagnostic Procedure (EUDP) 
The standard TB diagnostics in both settings consist of performing the sputum smear analysis by the 
clinical routine. Smear-negative cases will be followed as per standard routine (Figure 1A). 
4.7.2 The Optimized Diagnostic Procedure (ODP) intervention 
A three-step package which involves (Figure 1B):  
 
1. Oral and mobile phone-guided instructions by study staff  

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Patients will be instructed to take several deep breaths, hold their breath for a moment, and repeat 
this several times until coughing is induced including instructions to cough deeply and vigorously 
whilst breathing out (26). Instructions will be presented to the participating patients on a mobile 
phone to ensure consistent instructions to all participants. 
2. Pooling of two spot sputum samples (9)  
Two instructed pooled spot samples will be split into two parts (27) and investigated by fluorescence 
microscopy (28). The other part of the pooled sputum sample will be frozen for later confirmation 
with batch-wise BACTEC 960 MGIT as a gold standard for microbiological diagnosis. 
As an add on, we will analyze a subgroup of samples with the MinION to assess applicability in a low 
resource setting.   
3. Smear-negative cases at the first visit will be assessed for persisting symptoms and 
referred to a CXR unit 
Those with a CXR CAD result suggestive of active TB will be treated for TB. The smear negative cases 
will also leave an additional instructed spot sputum sample which will be pooled and one part 
analyzed by Xpert Ultra and the other part by BACTEC 960 MGIT culture. Additionally, non-sputum 
sampling will be performed and analyzed by Xpert Ultra including saliva combined with buccal and 
tongue sample using the same swab as well as a faecal sample Xpert Ultra using the WHO-
recommended direct procedure. (29) 
In a feasibility study, on the basis of intention to treat (either by smear microscopy or CXR/clinical 
grounds) the participants will be asked for an additional instructed sputum sample which will 
extracted using EZ1 and sequenced using nanopore sequencing and the EPI2ME bioinformatic 
platform as previously described. (6) 
4.7.3 Implementation of the ODP and EUDP 
Upon commencement of the intervention arm, the staff will be trained in applying optimized 
diagnostic procedures.  
For all included patients (both in the EUDP and the ODP) a follow-up visit one week from first 
encounter will take place, to ensure initiation of treatment (for smear positive cases) or to screen 
for persisting symptoms and carry out a second clinical evaluation (smear negative cases). Diagnosis 
will be according to local standards and based on smear microscopy, CXR, and WHO clinical criteria 
including for extrapulmonary cases (30, 31). During the intervention, the physician can overrule the 
TBscore if needed. At all clinics, both in the EUDP and ODP (i.e. intervention) phase, all included 

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patients will be referred to HIV testing at adjacent HIV-treatment clinics, where pre- and post-
testing counselling will be carried out. 
 
Figure 1A Diagnostic flow of the Enhanced Usual Diagnostic Procedure (EUDP), serving as control. 

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Figure 1B Diagnostic flow of the Optimized Diagnostic Procedure (ODP), serving as the intervention. Hexagons indicate 
deviations from the EUDP. 

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4.7.4 Inclusion criteria 
At the participating healthcare facilities, all patients ≥15 years old with presumed TB with cough, 
sputum production, and/or weight loss of any duration are eligible to participate. Healthcare 
facilities (n=4, two in each of the countries) will switch from Enhanced Usual Diagnostic Procedure 
(EUDP) to Optimized Diagnostic Procedure (ODP) following a random sequence. 
4.7.5 Exclusion criteria 
1. TB treatment within the past year.  
2. Cerebral disturbances impairing the ability to give informed consent or follow the treatment 
regime. 
5 Outcomes 
5.1 Primary outcomes 
1. Number of smear positive, Xpert PCR positive, or CXR positive patients comparing EUDP to 
ODP. 
5.2 Secondary outcomes 
1. Number of patients on active TB treatment comparing EUDP clinics to ODP clinics.  
2. Diagnostic yield of CAD CXR compared to smear microscopy, Xpert PCR, and culture. 
3. Follow-up rates in the cascade of care (i.e. one-week and six-months follow-up for all 
included and treatment start and outcome for all diagnosed with TB) 
4. Differences in diagnostic yield between instructed sampling, buccal samples, fecal samples 
and routine sputum sample. 
6 Sample size and statistical analyses 
Based on a previous study in the same setting, we found that among patients with a TBscore≥3 
there were a total of 5% smear positive cases both in Guinea-Bissau and Ethiopia. Using a higher 
cut-off value at TBscore≥4 increases specificity and is estimated to increase the case detection yield 
to 6% (based on previous data) using routine sputum collection and sputum smear analysis. 
Increasing the TBscore cut-off value thus leads to a lower referral rate of 54% of all screened (instead 
of 73%) while increasing the number of smear positive cases in the sample (from 5% to 6%). As both 
settings now use Xpert MTB/RIF Ultra as the primary diagnostic method, initial case rate is estimated 
at 8% (32). Based on systematic reviews, it is estimated that the diagnostic yield of an instructed 

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sputum where two spot-samples are pooled and processed using LED microscopy will lead to an at 
least twofold increase in sensitivity (9, 10, 27, 33). Adding CAD CXR onto those that are smear 
negative by the optimized sputum smear strategy is estimated to increase the number of patients 
diagnosed with TB 2.5-fold. To show an increase in diagnostic yield using ODP from a conservative 
estimate of 7% to 14% with a power of 80% and a significance level of 0.05, two clusters in each 
country are needed, including 132 patients per time interval (of 22 weeks). The estimated inclusion 
rate per cluster per week is 6 patients, which means that it should take 66 weeks to reach a target 
of 1584 inclusions.   
Sample size was calculated using the “steppedwedge” function in Stata (34).  
The diagnostic yield, time to diagnosis, and treatment outcomes will be calculated.  
Detection rates will be compared between control (EUDP) and intervention (ODP) in a generalized 
linear mixed effects model taking into account time and center effect and allowing for intra-cluster 
correlation, i.e., a mixed effect logistic regression for longitudinal data. A similar repeated 
measurements model will be used to analyze and compare groups on patient characteristics. 
7 Timeframe 
Study preparations will start August 2023 with establishment of enrolment procedures and training 
of staff. Enrolment will take place for 68 weeks (from June 2024 to September 2025). End of follow-
up will be April 2026. For details, please see Table 3. Overall responsible body for activities planned 
is the PI in collaboration with local VIP and TAP personnel. 
Table 3 Gantt chart of proposed activities. 
 

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8 Public health importance 
8.1 Major advances 
TB case-finding remains a challenge, particularly in overburdened healthcare facilities with limited 
access to diagnostics (35-37). A simple disease management strategy combined with improved 
utilization of available diagnostics may ensure that more patients with TB are treated and earlier 
and that those at high risk of dying are targeted appropriately with a rational use of limited 
resources. The major advance of adding a standardized approach to patients with presumed TB will 
be to decrease the substantial burden of undiagnosed TB with simple means, which makes it a 
sustainable, affordable, and practicable tool.  
8.2. New approach 
The strength of the Bandim TBscore strategy is that it guides the health care professional through a 
structured interview and uses the existing laboratory set-up, which is of great benefit compared to 
other more advanced diagnostic tools. The diagnostic algorithm simply utilizes what is already part 
of the primary healthcare setup, thereby increasing the chance of being applicable in similar settings 
worldwide. Similarly, the novel technologies employed in the ODP can easily be integrated into 
clinical settings worldwide. 
8.3. Generalizability of trial results 
This trial will test implementation of a cheap, readily available, practical point-of-care package which 
requires only minor additional training of staff. If shown to be effective in identifying additional TB 
cases, use of the Bandim TBscore and improved diagnostics may be expected to be endorsed with 
little delay by the WHO and national governments as a standard part of TB diagnosis and 
management.  
8.4. Contribution to improved disease management and public health 
In under-funded over-burdened healthcare facilities with a large patient load presenting with co-
morbidities, many patients with TB remain undiagnosed and untreated (35-37). Simple clinical tools 
at points of care which can identify up patients with active TB may have great potential for 
diagnosing patients with TB early and thereby preventing TB-associated morbidity and mortality. 
Targeting delayed TB diagnosis and TB-related mortality will add to the agenda of reducing poverty-
related diseases. The resources used to combat TB and the productive years lost to TB inflict a 
punishing toll on the economies of TB-endemic countries and helps perpetuate the cycle of poverty. 
The majority of TB is now concentrated in the World’s poorest countries, thus effective and 

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practicable programs to detect and cure TB early is the most feasible method of controlling the 
disease.  
8.5 Improvements in patient care 
A major strength of the Bandim TBscore is its ability to continually assess disease severity during 
treatment as has previously been shown by our group (25, 38, 39). Thus, the score may be used 
both to enhance the number of confirmed TB cases among patients with presumed TB and serve as 
an easily adaptable monitoring tool during the treatment or re-evaluation of these. 
9 Ethical considerations 
Consultative approval is expected to be granted from the Regional Ethics Committee in the Central 
Denmark Region, Denmark and permission to carry out the study will likewise be sought from the 
national ethics committees in Guinea-Bissau and Ethiopia. Written information will be provided in 
the official language Portuguese/Amharic and oral information will be provided to all eligible 
patients in the widely spoken language Portuguese Creole/Amharic. Informed written consent or a 
fingerprint if illiterate will be kept together with case report forms.  
10 Capacity Building and future implications 
The present study will serve as a platform for relevant capacity building for good clinical practice 
and good clinical laboratory practice in the two African sites as well as promote a stronger linkage 
within Africa, building on the existing links with Institutions in the EU. In addition, the capacity 
building and networking activities planned for this project aim to integrate African partners into the 
rapidly developing global network of TB trial sites; in particular it will build a resource of patients 
with presumed TB with detailed clinical data which is rare among TB studies in Africa(1). We have 
built a well-functioning infrastructure to carry out trials at the primary healthcare level, which is 
seldom done in TB research. We now aim to utilize this solid basis and our experience to improve 
TB case detection further. 
11 The Nordic collaboration and study group 
The Nordic collaborators in this trial have been working together since 2016. The main aim of the 
collaboration is to improve case finding of TB using applicable interventions in high endemic 
settings. Capacity building is an essential part of the collaboration and all trials make efforts to 

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involve existing structures and political elements in the settings in which they are carried out. 
Workshops will be held throughout the trial period. 
Christian Morberg Wejse (CW), MD, PhD is a consultant at the Department of Infectious Diseases, 
Aarhus University Hospital and Professor of Cross-Cultural Medicine and Global Health at the 
Department of Public Health, Aarhus University. He has supervised more than 20 research projects 
in Guinea-Bissau.  
Thomas Schön (TS), MD, PhD is a consultant of clinical microbiology and infectious diseases and a 
professor at the Department of Biomedical and Clinical Sciences Linköping University. He has 
undertaken multiple research projects in Ethiopia and Sweden. Both CW and TS have been involved 
in the development of the present research project and act as supervisors during the trial. 
Frauke Rudolf (FR), MD, PhD is senior registrar at the Department of Infectious Diseases, Aarhus 
University Hospital where she is responsible for TB patients, and clinical associate professor at 
Aarhus University. She has completed her PhD in Guinea-Bissau, evaluating a clinical score for TB. 
In recent years her research has focused on improving TB case detection and assessing gender 
differences in TB. 
Anita Zalisz, will be working on the project in the capacity of PhD-student. Anita will be responsible 
for supervising procedures in Bissau including data collection, data entry, as well as disseminating 
results. 
Mulugeta Aemero (MA), professor, Head, Tropical & Infectious Diseases Research Centre, 
CMHSCSH, University of Gondar, Ethiopia, will be working on the project in the capacity of project  
collaborator in Gondar, Ethiopia. 
Temesgen Tadesse (TT), MD, is a physician, who will be working on the project in the capacity of 
radiologist in Gondar, Ethiopia. 
Segenet Bizuneh (SB), MD, is a physician, who will be working on the project in the capacity of 
internist in Gondar, Ethiopia. 
Dessie Abebaw Angaw, Assistant Professor of Epidemiology and Biostatistics, will be working on 
the project in the capacity of project collaborator and supervisor in Gondar, Ethiopia. 
Masresha Seyoum, BSc, MSc, Diagnostic Coordinator at UoGCSH, will be working on the project 
in the capacity of microbiologist in Gondar, Ethiopia. 
Lilica Sanca (LS), BSc, and Ebba Abate (EA), PhD, are key personnel in Guinea-Bissau and Ethiopia 
respectively. LS is responsible for the national refence laboratory for TB in Guinea-Bissau while EA 

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has completed his PhD in Gondar, has formerly worked  as Director General, Ethiopian Public 
Health Institute (EPHI), Ethiopia and is now Project Director for the North Africa Saving Lives and 
Livelihood Initiative, Project Hope Namibia, Namibia. 
Armando Sifna (AS), MD, is a physician with extensive experience in TB and is part of the TB 
program under the ministry of health in Guinea-Bissau. 
12 Exploiting and disseminating the project results 
The standardised approach to TB management resulting from implementing the Bandim TBscore 
and improving available diagnostics is simple to communicate and translate into policy and WHO 
guidelines. The national partners in this project work within the national TB programs and may 
disseminate project results rapidly into policy changes at the national level. There are no intellectual 
property rights issues preventing a global dissemination of the Bandim TBscore which will be 
attempted through peer-reviewed publications and conference presentations. 

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