*Corresponding Author: Khutade Kalpesh, Department of Biological Sciences, Sandip University,
School of Science, Nashik, Maharashtra, India Email: [email protected]. 67
International Journal of Zoology and Applied Biosciences ISSN: 2455-9571
Volume 10, Issue 5, pp: 67-74, 2025 http://www.ijzab.com
https://doi.org/10.55126/ijzab.2025.v10.i05.009
Research Article
QUANTITATIVE ASSESSMENT OF MYCOBACTERIAL LOAD THROUGH
SPUTUM SMEAR GRADING AND TRUENAT CFU/mL MEASUREMENT
1a,b*Khutade Kalpesh, 2Hadal Ashwini, 2Narlya Manisha, 3Dhinde Harshila, 3Shah Harshada
1a*Department of Biological Sciences, Sandip University, School of Science, Nashik, Maharashtra, India
2 Department of Microbiology, Dr. Homi Bhabha State University, The Institute of Science, 15,
Madame Cama Rd, Mantralaya, Fort, Mumbai, Maharashtra 400032, India
1b*,3 Department of Microbiology, MUHS University, Vedantaa Institute of Medical Sciences and Research Centre,
Palghar-401606, Maharashtra, India
Article History: Received 31st July 2025; Accepted 7th September 2025; Published 30th September 2025
ABSTRACT
This study assessed mycobacterial load in sputum samples using smear microscopy grading and Truenat CFU/mL
quantification, and evaluated the correlation between these diagnostic methods. Sputum specimens were collected from
suspected pulmonary tuberculosis patients. Prepared sputum smears were stained using the Ziehl-Neelsen method, and the
same sputum samples were tested using the Truenat platform. 85 (14.2%) tested positive for mycobacterium tuberculosis
using Truenat. The infection rate was higher in males (61.2%), with the highest prevalence observed in the 21–30 age
group. Of the 85 Truenat-positive cases, 66 (77.6%) were also positive on smear microscopy. Notably, adult males were
more likely to present with high-grade smears (3+), indicating greater infectivity. The correlation between smear grade and
Truenat CFU/mL was statistically significant (Chi-square = 4.2736, p = 0.0387), meeting the threshold for significance at p
< 0.05. Bacterial loads ranged from 2.7 × 10¹ to 5.6 × 10⁷ CFU/mL. A high bacterial load (≥10⁶ CFU/mL) was observed in
over 21% of patients, reflecting advanced disease stages. However, Truenat demonstrated superior diagnostic performance,
achieving 100% sensitivity and specificity, compared to smear microscopy, which showed 61.67% sensitivity and 76%
specificity.
Keywords: Microscopy, Mycobacterial load, Truenat, Ziehl-neelsen staining, Diagnostic sensitivity, Specificity.
INTRODUCTION
The “World Health Organization (WHO)” reported 10.6
million TB cases in 2021, leading to 1.6 million deaths
(Akhtar et al., 2022; Ali et al., 2012;). India launched the
“National Strategic Plan 2017-2025” to combat TB,
focusing on Test, Treat, Prevent, and Build pillars. The
goal is to make India TB-free by 2025 (Brahmapurkar et
al., 2017; Khutade et al., 2023; WHO, 2022). For rapid
diagnosis, automated, cartridge-based nucleic acid
amplification tests (NAATs) are now widely used (Hai et
al., 2021). However, conventional sputum smear
microscopy continues to play a crucial role, especially in
high-burden settings. It remains a cost-effective and
accessible diagnostic tool that categorizes bacterial load
into semi-quantitative grades (e.g., 1+, 2+, 3+), offering a
quick, though somewhat limited, estimate of bacillary
burden (Hazra et al., 2019).
Timely evaluation of treatment response through the
detection of viable bacteria is critical for assessing
therapeutic efficacy and predicting clinical outcomes
(Imam & Oyeyi, 2010). Such evaluations improve the
accuracy of patient management. However, reliable follow-
up in patients with TB remains challenging ( Kassa et al.,
2021). Bacillary load in TB patients is commonly estimated
using automated culture systems like the Mycobacterial
Growth Indicator Tube (MGIT) or molecular methods such
as Truenat. While culture-based techniques are considered
the gold standard, they are inherently slow and susceptible
to contamination. Moreover, the presence of non-culturable
Mtb populations limits the reliability of culture-based
Khutade Kalpesh et al. Int. J. Zool. Appl. Biosci., 10(5), 67-74, 2025
www.ijzab.com 68
assays for evaluating treatment response (Khan et al.,
2006). Although DNA-based molecular diagnostics offer
faster results, they cannot distinguish between live and
dead bacteria, as bacterial DNA may persist even after cell
death. In contrast, the Molecular Bacterial Load Assay
(MBLA)—which targets 16S rRNA—provides a rapid and
accurate quantification of viable Mtb. Because rRNA
degrades quickly after cell death, MBLA offers a more
precise reflection of bacterial viability and holds promise as
a valuable tool for early prediction of treatment failure or
disease progression (Khutade et al., 2024).
Recently introduced molecular diagnostics, such as the
Truenat MTB/MTB-RIF test, utilize chip-based real-time
PCR technology and have been endorsed by the WHO as
reliable tools for TB diagnosis (MacLean et al., 2020). One
of the key advantages of Truenat is its ability to quantify
bacillary load in colony-forming units per milliliter
(CFU/mL), offering a more sensitive and objective
assessment compared to conventional methods (Magar et
al., 2020). Although both smear microscopy and molecular
diagnostics are widely used in clinical practice, there is a
lack of systematic evaluation correlating smear grading
with quantitative CFU/mL results obtained from Truenat.
Exploring this relationship can help identify potential
synergies and complementarities between the two methods.
Establishing this correlation could enhance diagnostic
accuracy, particularly in resource-limited settings where
rapid, reliable tools are essential for effective TB control
(Mistry et al., 2016). The aim of this study was to
objectively evaluate the mycobacterial load in sputum
samples by quantifying bacillary burden through both
smear microscopy grading and Truenat CFU/mL
measurements, and to determine the correlation between
these two diagnostic methods.
MATERIALS AND METHOD
Ethics statement
A prospective study was conducted at the “Vedantaa
Institute of Medical Sciences and Research Centre, Palghar,
Maharashtra, India”, over a one-year period from January
to December 2024. Sputum samples were collected and
processed in accordance with institutional protocols,
ensuring adherence to relevant biosafety and ethical
guidelines (Approval number: EC/VIMS/12/2023).
Study design and setting
The study involved the analysis of 599 sputum samples.
Inclusion criteria: Samples were collected from patients
suspected of Mycobacterium tuberculosis, meeting WHO
criteria for TB suspicion, including cough, chronic fever,
night sweats, or unintentional weight loss. Exclusion
criteria: Participants with extra-pulmonary tuberculosis
were not included in the research study (WHO, 2024).
Sample Collection
Sputum specimens were collected from patients who met
the WHO inclusion criteria. Clear instructions on proper
sputum collection techniques were provided to each patient
to ensure the quality of the sample. Patients were instructed
to take a deep breath, hold it for a few seconds, and then
forcefully cough up sputum (not saliva) from deep in the
lungs. The sputum was to be spat into a clean, sterile
container with a tightly fitting screw cap. Patients were also
advised to avoid any contact between the mouthpiece and
saliva, food remnants, or any other potential contaminants.
Both microscopy and Truenat analysis were performed on
the morning sputum samples, as bacillary concentration
tends to be higher in specimens collected in the morning.
Z-N Staining
Our research center is accredited as a Designated
Microscopy Centre (DMC) and is equipped for Truenat
testing under the RNTCP in Palghar, Maharashtra. In
accordance with RNTCP guidelines, Z-N staining was
utilized to detect acid-fast bacilli (AFB). Under the
microscope, acid-fast bacilli appear bright red against a
light blue background, enabling easy identification.
Truenat MTB Assay
Sample handling was performed using the Trueprep AUTO
MTB Sample Pre-treatment Pack, which facilitates the
homogenization and concentration of sputum samples. This
step enhances the efficient lysis of Mycobacterium
tuberculosis cells while also eliminating potential PCR
inhibitors. Following this, DNA was extracted and purified
using the “Trueprep AUTO Universal Cartridge-based
Sample Preparation Kit,” a miniaturized, handheld system
that operates effectively at room temperature. Molecular
testing was then carried out using the “Truenat MTB
micro-PCR chip”. This highly sensitive test detects
bacterial DNA by measuring the cycle threshold (Ct) value,
which represents the cycle number at which fluorescence
crosses the detection threshold. Once the test is completed,
the system provides a qualitative result of "Detected" or
"Not Detected," along with an Internal Positive Control
(IPC) to validate the testing process. For samples positive
for M. tuberculosis, further testing was conducted to assess
rifampicin resistance using the “Truenat MTB-RIF micro-
PCR chip,” performed on the same analytical platform
(Wagh et al., 2024; Molbio, 2025).
Statistically analysis
The relationship between gender (male/female) and AFB
result (positive/negative) was evaluated using a Chi-Square
Test of Independence. The test was conducted online tools
“https://www.socscistatistics.com/tests/chisquare2/default2.
aspx”. Additionally, data analysis for diagnostic
performance was determinate using “MedCalc Statistical
Software
https://www.medcalc.org/calc/diagnostic_test.php.”
www.ijzab.com 68
assays for evaluating treatment response (Khan et al.,
2006). Although DNA-based molecular diagnostics offer
faster results, they cannot distinguish between live and
dead bacteria, as bacterial DNA may persist even after cell
death. In contrast, the Molecular Bacterial Load Assay
(MBLA)—which targets 16S rRNA—provides a rapid and
accurate quantification of viable Mtb. Because rRNA
degrades quickly after cell death, MBLA offers a more
precise reflection of bacterial viability and holds promise as
a valuable tool for early prediction of treatment failure or
disease progression (Khutade et al., 2024).
Recently introduced molecular diagnostics, such as the
Truenat MTB/MTB-RIF test, utilize chip-based real-time
PCR technology and have been endorsed by the WHO as
reliable tools for TB diagnosis (MacLean et al., 2020). One
of the key advantages of Truenat is its ability to quantify
bacillary load in colony-forming units per milliliter
(CFU/mL), offering a more sensitive and objective
assessment compared to conventional methods (Magar et
al., 2020). Although both smear microscopy and molecular
diagnostics are widely used in clinical practice, there is a
lack of systematic evaluation correlating smear grading
with quantitative CFU/mL results obtained from Truenat.
Exploring this relationship can help identify potential
synergies and complementarities between the two methods.
Establishing this correlation could enhance diagnostic
accuracy, particularly in resource-limited settings where
rapid, reliable tools are essential for effective TB control
(Mistry et al., 2016). The aim of this study was to
objectively evaluate the mycobacterial load in sputum
samples by quantifying bacillary burden through both
smear microscopy grading and Truenat CFU/mL
measurements, and to determine the correlation between
these two diagnostic methods.
MATERIALS AND METHOD
Ethics statement
A prospective study was conducted at the “Vedantaa
Institute of Medical Sciences and Research Centre, Palghar,
Maharashtra, India”, over a one-year period from January
to December 2024. Sputum samples were collected and
processed in accordance with institutional protocols,
ensuring adherence to relevant biosafety and ethical
guidelines (Approval number: EC/VIMS/12/2023).
Study design and setting
The study involved the analysis of 599 sputum samples.
Inclusion criteria: Samples were collected from patients
suspected of Mycobacterium tuberculosis, meeting WHO
criteria for TB suspicion, including cough, chronic fever,
night sweats, or unintentional weight loss. Exclusion
criteria: Participants with extra-pulmonary tuberculosis
were not included in the research study (WHO, 2024).
Sample Collection
Sputum specimens were collected from patients who met
the WHO inclusion criteria. Clear instructions on proper
sputum collection techniques were provided to each patient
to ensure the quality of the sample. Patients were instructed
to take a deep breath, hold it for a few seconds, and then
forcefully cough up sputum (not saliva) from deep in the
lungs. The sputum was to be spat into a clean, sterile
container with a tightly fitting screw cap. Patients were also
advised to avoid any contact between the mouthpiece and
saliva, food remnants, or any other potential contaminants.
Both microscopy and Truenat analysis were performed on
the morning sputum samples, as bacillary concentration
tends to be higher in specimens collected in the morning.
Z-N Staining
Our research center is accredited as a Designated
Microscopy Centre (DMC) and is equipped for Truenat
testing under the RNTCP in Palghar, Maharashtra. In
accordance with RNTCP guidelines, Z-N staining was
utilized to detect acid-fast bacilli (AFB). Under the
microscope, acid-fast bacilli appear bright red against a
light blue background, enabling easy identification.
Truenat MTB Assay
Sample handling was performed using the Trueprep AUTO
MTB Sample Pre-treatment Pack, which facilitates the
homogenization and concentration of sputum samples. This
step enhances the efficient lysis of Mycobacterium
tuberculosis cells while also eliminating potential PCR
inhibitors. Following this, DNA was extracted and purified
using the “Trueprep AUTO Universal Cartridge-based
Sample Preparation Kit,” a miniaturized, handheld system
that operates effectively at room temperature. Molecular
testing was then carried out using the “Truenat MTB
micro-PCR chip”. This highly sensitive test detects
bacterial DNA by measuring the cycle threshold (Ct) value,
which represents the cycle number at which fluorescence
crosses the detection threshold. Once the test is completed,
the system provides a qualitative result of "Detected" or
"Not Detected," along with an Internal Positive Control
(IPC) to validate the testing process. For samples positive
for M. tuberculosis, further testing was conducted to assess
rifampicin resistance using the “Truenat MTB-RIF micro-
PCR chip,” performed on the same analytical platform
(Wagh et al., 2024; Molbio, 2025).
Statistically analysis
The relationship between gender (male/female) and AFB
result (positive/negative) was evaluated using a Chi-Square
Test of Independence. The test was conducted online tools
“https://www.socscistatistics.com/tests/chisquare2/default2.
aspx”. Additionally, data analysis for diagnostic
performance was determinate using “MedCalc Statistical
Software
https://www.medcalc.org/calc/diagnostic_test.php.”
Khutade Kalpesh et al. Int. J. Zool. Appl. Biosci., 10(5), 67-74, 2025
www.ijzab.com 69
RESULTS AND DISCUSSION
Of the 599 registered cases, 85 (14.2%) tested positive and
514 (85.8%) tested negative, using Truenat as the reference
method. Among the confirmed cases, male - 52 (61.2%)
and female- 33 (38.8%). Across all age groups, males were
consistently more affected, especially in the 41–60 years
range. This suggests that the infection is more prevalent in
males, particularly in the working-age population (Figure
1).
Figure 1. Age and gender wise distribution of TB patients (n=85). The highest proportion of confirmed cases were in the
21–30 years age group, accounting for 29.4% of the cases, with 11 males and 14 females. The 41–50 years age
group was the second most affected, contributing 17 cases (20.0%), predominantly male (14 cases). The 51–60
years age group accounted for 15 cases (17.6%), again with a male predominance. There were 14 cases (16.5%) in
the 31–40 years age range. Fewer cases were observed in both the ≤20 years and ≥60 years age groups.
A total of 85 samples were tested for AFB, with results
analyzed by age and sex distribution. Among these, 66
(77.6%) tested positive for AFB, while 19 (22.4%) were
negative. The majority of AFB-positive cases (29, 43.9%)
had a bacillary load of 3+, indicating high infectivity. The
45–54 years male age group had the highest number of
positives (15, 22.7%), with 9 of them showing a 3+ grade.
Across all age groups, the positive rate and bacillary load
were consistently higher in males.
Notably, there were no positive AFB results in the
younger age group (0–14 years). Males dominated the
significant positive cases in the 35–44 and 25–34 years age
groups. In contrast, 15–24 and 55–64 years age groups
showed scantier and 1+ bacillary grades. Females had
fewer high-grade positive results (2+ or 3+) compared to
males, which suggests a greater exposure and intensity of
infection among adult males, particularly those of working
age (Table 1). The chi-square value, p-value and
determination of significance is displayed under the table.
To measure the relationship between gender and
swimming, a chi square for independence was used. A
significant relationship was observed between these factors.
The chi-square value was 4.2736. The p-value was.
038709. The result was statistically significance at p <
0.05.
Table 1. Stratification of AFB positivity by demographics in sputum samples (n=85).
Age Group Gender
Total
Samples
Examined
AFB
Negative
Scanty
(1–9/100
fields)
1+ (10–
99/100
fields)
2+ (1–
10/field)
3+
(>10/field)
Total
AFB
Positive
0–14 yrs Male 2 (2.4%) 2 (2.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%)
Female 1 (1.2%) 1 (1.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%)
15–24 yrs Male 5 (5.9%) 0 (0.0%) 3 (4.5%) 1 (1.5%) 0 (0.0%) 1 (1.5%) 5 (7.6%)
www.ijzab.com 69
RESULTS AND DISCUSSION
Of the 599 registered cases, 85 (14.2%) tested positive and
514 (85.8%) tested negative, using Truenat as the reference
method. Among the confirmed cases, male - 52 (61.2%)
and female- 33 (38.8%). Across all age groups, males were
consistently more affected, especially in the 41–60 years
range. This suggests that the infection is more prevalent in
males, particularly in the working-age population (Figure
1).
Figure 1. Age and gender wise distribution of TB patients (n=85). The highest proportion of confirmed cases were in the
21–30 years age group, accounting for 29.4% of the cases, with 11 males and 14 females. The 41–50 years age
group was the second most affected, contributing 17 cases (20.0%), predominantly male (14 cases). The 51–60
years age group accounted for 15 cases (17.6%), again with a male predominance. There were 14 cases (16.5%) in
the 31–40 years age range. Fewer cases were observed in both the ≤20 years and ≥60 years age groups.
A total of 85 samples were tested for AFB, with results
analyzed by age and sex distribution. Among these, 66
(77.6%) tested positive for AFB, while 19 (22.4%) were
negative. The majority of AFB-positive cases (29, 43.9%)
had a bacillary load of 3+, indicating high infectivity. The
45–54 years male age group had the highest number of
positives (15, 22.7%), with 9 of them showing a 3+ grade.
Across all age groups, the positive rate and bacillary load
were consistently higher in males.
Notably, there were no positive AFB results in the
younger age group (0–14 years). Males dominated the
significant positive cases in the 35–44 and 25–34 years age
groups. In contrast, 15–24 and 55–64 years age groups
showed scantier and 1+ bacillary grades. Females had
fewer high-grade positive results (2+ or 3+) compared to
males, which suggests a greater exposure and intensity of
infection among adult males, particularly those of working
age (Table 1). The chi-square value, p-value and
determination of significance is displayed under the table.
To measure the relationship between gender and
swimming, a chi square for independence was used. A
significant relationship was observed between these factors.
The chi-square value was 4.2736. The p-value was.
038709. The result was statistically significance at p <
0.05.
Table 1. Stratification of AFB positivity by demographics in sputum samples (n=85).
Age Group Gender
Total
Samples
Examined
AFB
Negative
Scanty
(1–9/100
fields)
1+ (10–
99/100
fields)
2+ (1–
10/field)
3+
(>10/field)
Total
AFB
Positive
0–14 yrs Male 2 (2.4%) 2 (2.4%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%)
Female 1 (1.2%) 1 (1.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%)
15–24 yrs Male 5 (5.9%) 0 (0.0%) 3 (4.5%) 1 (1.5%) 0 (0.0%) 1 (1.5%) 5 (7.6%)
Khutade Kalpesh et al. Int. J. Zool. Appl. Biosci., 10(5), 67-74, 2025
www.ijzab.com 70
Female 13
(15.3%) 5 (5.9%) 1 (1.5%) 1 (1.5%) 3 (4.5%) 3 (4.5%) 8 (12.1%)
25–34 yrs Male 10
(11.8%) 2 (2.4%) 1 (1.5%) 1 (1.5%) 1 (1.5%) 5 (7.6%) 8 (12.1%)
Female 8 (9.4%) 4 (4.7%) 0 (0.0%) 0 (0.0%) 2 (3.0%) 2 (3.0%) 4 (6.1%)
35–44 yrs Male 9 (10.6%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 4 (6.1%) 4 (6.1%) 9 (13.6%)
Female 5 (5.9%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 2 (3.0%) 2 (3.0%) 5 (7.6%)
45–54 yrs Male 15
(17.6%) 0 (0.0%) 0 (0.0%) 2 (3.0%) 4 (6.1%) 9 (13.6%) 15 (22.7%)
Female 2 (2.4%) 1 (1.2%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 1 (1.5%)
55–64 yrs Male 9 (10.6%) 4 (4.7%) 2 (3.0%) 1 (1.5%) 1 (1.5%) 1 (1.5%) 5 (7.6%)
Female 2 (2.4%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 1 (1.5%) 2 (3.0%)
65+ yrs Male 3 (3.5%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 2 (3.0%) 1 (1.5%) 3 (4.5%)
Female 1 (1.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 1 (1.5%)
Total
(Statistical
significant)
Male 8 (11.85)
[1.25]
45 (41.14)
[0.36]
Female 11 (7.15)
[2.07]
21 (24.85)
[0.60]
Total 85 (100%) 19 (22.4%) 8
(12.1%)
8
(12.1%) 21 (31.8%) 29 (43.9%) 66 (100%)
Bacterial loads among the 85 patients varied significantly,
ranging from 2.7 × 10¹ to 5.6 × 10⁷ CFU/mL, reflecting the
diverse severity of the disease. Moderate bacterial loads,
ranging from 10⁴ to 10⁵ CFU/mL, were seen in 30 patients
(35.3%), with common values being 4.2 × 10⁴ CFU/mL and
3.9 × 10⁴ CFU/mL. Low bacterial counts (≤10³ CFU/mL)
were found in 15 cases It is noteworthy that some patients
exhibited very low bacterial loads (e.g., 2.7 × 10¹
CFU/mL), which may suggest latent infection. The overall
distribution of bacterial loads was skewed toward higher
values, consistent with active disease. These findings
suggest that quantifying bacterial load could serve as a
reliable surrogate marker for both infectious burden and
clinical status (Figure 2).
Figure 2. Frequency of bacterial loads detected in sputum samples correlation between smear grading and truenat
CFU/mL. The most common bacterial load observed was 5.9 × 10⁵ CFU/mL, found in 8 patients (9.4%). High
bacterial loads (≥10⁶ CFU/mL) were detected in 18 patients (21.2%), indicating advanced stages of infection in
this subset. The highest reported bacterial load was 5.6 × 10⁷ CFU/mL, observed in 4 patients.0
1
2
3
4
5
6
7
8
9
1.0 ×
10⁶
1.1 ×
10⁴
1.3 ×
10²
1.4 ×
10³
1.5 ×
10²
1.6 ×
10⁴
1.9 ×
10³
2.1 ×
10²
2.3 ×
10⁴
2.5 ×
10⁷
2.7 ×
10¹
2.9 ×
10²
3.5 ×
10²
3.3 ×
10²
3.9 ×
10⁴
4.2 ×
10⁵
5.6 ×
10⁶
4.7 ×
10³
5.9 ×
10⁵
5.8 ×
10²
6.7 ×
10⁵
8.0 ×
10³
8.7 ×
10⁴
9.3 ×
10⁴
Total numbers of patients
Mycobacterial load (CFU/mL)
www.ijzab.com 70
Female 13
(15.3%) 5 (5.9%) 1 (1.5%) 1 (1.5%) 3 (4.5%) 3 (4.5%) 8 (12.1%)
25–34 yrs Male 10
(11.8%) 2 (2.4%) 1 (1.5%) 1 (1.5%) 1 (1.5%) 5 (7.6%) 8 (12.1%)
Female 8 (9.4%) 4 (4.7%) 0 (0.0%) 0 (0.0%) 2 (3.0%) 2 (3.0%) 4 (6.1%)
35–44 yrs Male 9 (10.6%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 4 (6.1%) 4 (6.1%) 9 (13.6%)
Female 5 (5.9%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 2 (3.0%) 2 (3.0%) 5 (7.6%)
45–54 yrs Male 15
(17.6%) 0 (0.0%) 0 (0.0%) 2 (3.0%) 4 (6.1%) 9 (13.6%) 15 (22.7%)
Female 2 (2.4%) 1 (1.2%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 1 (1.5%)
55–64 yrs Male 9 (10.6%) 4 (4.7%) 2 (3.0%) 1 (1.5%) 1 (1.5%) 1 (1.5%) 5 (7.6%)
Female 2 (2.4%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 1 (1.5%) 2 (3.0%)
65+ yrs Male 3 (3.5%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 2 (3.0%) 1 (1.5%) 3 (4.5%)
Female 1 (1.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 1 (1.5%)
Total
(Statistical
significant)
Male 8 (11.85)
[1.25]
45 (41.14)
[0.36]
Female 11 (7.15)
[2.07]
21 (24.85)
[0.60]
Total 85 (100%) 19 (22.4%) 8
(12.1%)
8
(12.1%) 21 (31.8%) 29 (43.9%) 66 (100%)
Bacterial loads among the 85 patients varied significantly,
ranging from 2.7 × 10¹ to 5.6 × 10⁷ CFU/mL, reflecting the
diverse severity of the disease. Moderate bacterial loads,
ranging from 10⁴ to 10⁵ CFU/mL, were seen in 30 patients
(35.3%), with common values being 4.2 × 10⁴ CFU/mL and
3.9 × 10⁴ CFU/mL. Low bacterial counts (≤10³ CFU/mL)
were found in 15 cases It is noteworthy that some patients
exhibited very low bacterial loads (e.g., 2.7 × 10¹
CFU/mL), which may suggest latent infection. The overall
distribution of bacterial loads was skewed toward higher
values, consistent with active disease. These findings
suggest that quantifying bacterial load could serve as a
reliable surrogate marker for both infectious burden and
clinical status (Figure 2).
Figure 2. Frequency of bacterial loads detected in sputum samples correlation between smear grading and truenat
CFU/mL. The most common bacterial load observed was 5.9 × 10⁵ CFU/mL, found in 8 patients (9.4%). High
bacterial loads (≥10⁶ CFU/mL) were detected in 18 patients (21.2%), indicating advanced stages of infection in
this subset. The highest reported bacterial load was 5.6 × 10⁷ CFU/mL, observed in 4 patients.0
1
2
3
4
5
6
7
8
9
1.0 ×
10⁶
1.1 ×
10⁴
1.3 ×
10²
1.4 ×
10³
1.5 ×
10²
1.6 ×
10⁴
1.9 ×
10³
2.1 ×
10²
2.3 ×
10⁴
2.5 ×
10⁷
2.7 ×
10¹
2.9 ×
10²
3.5 ×
10²
3.3 ×
10²
3.9 ×
10⁴
4.2 ×
10⁵
5.6 ×
10⁶
4.7 ×
10³
5.9 ×
10⁵
5.8 ×
10²
6.7 ×
10⁵
8.0 ×
10³
8.7 ×
10⁴
9.3 ×
10⁴
Total numbers of patients
Mycobacterial load (CFU/mL)
Khutade Kalpesh et al. Int. J. Zool. Appl. Biosci., 10(5), 67-74, 2025
www.ijzab.com 71
Bacteriological load (CFU/mL) was compared with
microscopic smear grading to assess bacillary load. In the
cohort of 85 patients, a significant proportion exhibited
high-grade smears (3+), which also correlated with peak
bacterial loads (5.9 × 10⁵ and 5.6 × 10⁷ CFU/mL). This
smear grading system provides a reliable means of
quantifying infectious burden, even in resource-limited
settings. The quantitative measurement of CFU/mL
enhances the interpretive accuracy of conventional smear
microscopy (Figure 3).
Figure 3. Smear grading based on bacterial concentration. Loads in the 10¹–10² CFU/mL range were typically associated
with negative smears, found in individuals with low bacteria. Sparse smears were linked to bacterial loads around
10³ CFU/mL, suggesting early or low infection. 1+ smears were generally observed in patients with bacterial
loads between 10³–10⁴ CFU/ml, while 2+ smears were seen in those with loads ranging from 10⁴–10⁵ CFU/mL.
The majority of cases with high bacterial burdens (10⁵–10⁷ CFU/mL) corresponded to 3+ smear grades, indicative
of a high bacilli load.
The performance of microscopy was assessed against the
reference standard method, Truenat. Among the 85
confirmed MTB cases, 66 individuals were True Positives
(TP). Truenat identified all 66 TP cases without any False
Negatives (FN), yielding a clinical sensitivity rate of 100%
(95% CI: 94.56%–100%). Truenat also demonstrated 100%
specificity (95% CI: 82.35%–100%), correctly identifying
19 true negatives (TNs) with 0 false positives (FPs). In
contrast, microscopy detected only 37 true positives (TPs),
missing 23 cases (false negatives, FN), resulting in a
sensitivity of just 61.67% (95% CI: 48.21%–73.93%). The
specificity for microscopy was 76% (95% CI: 54.87%–
90.64%), based on 19 TNs and 6 FPs. These findings
highlight the superior accuracy of Truenat over routine
microscopy (Table 2).
Table 2. Sensitivity and specificity of truenat for mycobacterium tuberculosis diagnosis in 85 sputum samples.
Method TP FN TN FP Clinical Sensitivity (95% CI) Clinical Specificity (95% CI)
Microscopy 37 23 19 6 61.67% (48.21% to 73.93%) 76% (54.87% to 90.64%)
Truenat 66 0 19 0 100% (94.56% to 100%) 100% (82.35% to 100.00%)
The diagnostic accuracy of micro real-time PCR and
microscopy for pulmonary tuberculosis diagnosis. The
most significant prevalence of tuberculosis was studied in
the 21–30-year age group, while the lowest was seen in the
0–20 and 60+ years categories. Similarly, the “Xpert
MTB/RIF method” identified the highest rate of infection
among individuals aged 21–30 in Jumlah14. At Patan
Hospital, the oldest age group had a TB rate of 32.54%,
while the youngest group contributed only 5.79% (Sah et
al., 2020). In Ethiopia, the highest TB prevalence was
found in the 15–24 and 25–34 age groups (Banti et al.,
2023), while in Nigeria, the 30–43 age group showed the
highest prevalence at 17% (Ukoaka et al., 2024). In
Malaysia, the 21–40 age group had the highest TB
prevalence at 37% (Ahmad et al., 2021), whereas in
Pakistan, the <20 years group had the highest prevalence at
48.08% (Jawad et al., 2023). A steady increase in TB
prevalence was also observed by age in Satara district,
where men were found to be twice as affected as women
((Mohite et al., 2014). Our study yielded similar findings,
with a comparable pattern reported at Lumbini Provincial
Hospital (Paudel & Maharjan, 2018). Across much of
Nepal, men had a higher prevalence of tuberculosis than
women (Smith, 2024).
www.ijzab.com 71
Bacteriological load (CFU/mL) was compared with
microscopic smear grading to assess bacillary load. In the
cohort of 85 patients, a significant proportion exhibited
high-grade smears (3+), which also correlated with peak
bacterial loads (5.9 × 10⁵ and 5.6 × 10⁷ CFU/mL). This
smear grading system provides a reliable means of
quantifying infectious burden, even in resource-limited
settings. The quantitative measurement of CFU/mL
enhances the interpretive accuracy of conventional smear
microscopy (Figure 3).
Figure 3. Smear grading based on bacterial concentration. Loads in the 10¹–10² CFU/mL range were typically associated
with negative smears, found in individuals with low bacteria. Sparse smears were linked to bacterial loads around
10³ CFU/mL, suggesting early or low infection. 1+ smears were generally observed in patients with bacterial
loads between 10³–10⁴ CFU/ml, while 2+ smears were seen in those with loads ranging from 10⁴–10⁵ CFU/mL.
The majority of cases with high bacterial burdens (10⁵–10⁷ CFU/mL) corresponded to 3+ smear grades, indicative
of a high bacilli load.
The performance of microscopy was assessed against the
reference standard method, Truenat. Among the 85
confirmed MTB cases, 66 individuals were True Positives
(TP). Truenat identified all 66 TP cases without any False
Negatives (FN), yielding a clinical sensitivity rate of 100%
(95% CI: 94.56%–100%). Truenat also demonstrated 100%
specificity (95% CI: 82.35%–100%), correctly identifying
19 true negatives (TNs) with 0 false positives (FPs). In
contrast, microscopy detected only 37 true positives (TPs),
missing 23 cases (false negatives, FN), resulting in a
sensitivity of just 61.67% (95% CI: 48.21%–73.93%). The
specificity for microscopy was 76% (95% CI: 54.87%–
90.64%), based on 19 TNs and 6 FPs. These findings
highlight the superior accuracy of Truenat over routine
microscopy (Table 2).
Table 2. Sensitivity and specificity of truenat for mycobacterium tuberculosis diagnosis in 85 sputum samples.
Method TP FN TN FP Clinical Sensitivity (95% CI) Clinical Specificity (95% CI)
Microscopy 37 23 19 6 61.67% (48.21% to 73.93%) 76% (54.87% to 90.64%)
Truenat 66 0 19 0 100% (94.56% to 100%) 100% (82.35% to 100.00%)
The diagnostic accuracy of micro real-time PCR and
microscopy for pulmonary tuberculosis diagnosis. The
most significant prevalence of tuberculosis was studied in
the 21–30-year age group, while the lowest was seen in the
0–20 and 60+ years categories. Similarly, the “Xpert
MTB/RIF method” identified the highest rate of infection
among individuals aged 21–30 in Jumlah14. At Patan
Hospital, the oldest age group had a TB rate of 32.54%,
while the youngest group contributed only 5.79% (Sah et
al., 2020). In Ethiopia, the highest TB prevalence was
found in the 15–24 and 25–34 age groups (Banti et al.,
2023), while in Nigeria, the 30–43 age group showed the
highest prevalence at 17% (Ukoaka et al., 2024). In
Malaysia, the 21–40 age group had the highest TB
prevalence at 37% (Ahmad et al., 2021), whereas in
Pakistan, the <20 years group had the highest prevalence at
48.08% (Jawad et al., 2023). A steady increase in TB
prevalence was also observed by age in Satara district,
where men were found to be twice as affected as women
((Mohite et al., 2014). Our study yielded similar findings,
with a comparable pattern reported at Lumbini Provincial
Hospital (Paudel & Maharjan, 2018). Across much of
Nepal, men had a higher prevalence of tuberculosis than
women (Smith, 2024).
Khutade Kalpesh et al. Int. J. Zool. Appl. Biosci., 10(5), 67-74, 2025
www.ijzab.com 72
Among 520 pulmonary TB cases, “16.35% (95% CI:
13.40%, 19.79%) tested sputum smear-negative. Of the
remaining patients, 15.19% (95% CI: 13.40%, 19.79%) had
scanty (1 to 9 bacilli)” results, 18.27% (95% CI: 12.35%,
18.55%) had 1+, 15.77% (95% CI: 12.87%, 19.17%) had
2+, and 34.42% (95% CI: 30.45%, 38.65%) had 3+ smear
grades, respectively. In total, the sputum smear-positive
rate was 83.65% (95% CI: 80.21%, 86.60%) ( Kassa et al.,
2021). Among the positive cases, 40.1% had a 3+ grade,
while 6.8% had a scanty grade. The treatment success rate
was lowest in the scanty group (71.4%), followed by 1+
(80.2%), with the highest success rate observed in sputum
smear-negative cases (84.1%). The overall failure rate was
16.9%. Increased risks of poor outcomes were observed in
patients over 40 years old, males, and those undergoing
retreatment. The TB-MBLA assay quantified a “bacterial
load of 4.8 log10 eCFU per mL (SD 1.5)”. HIV-positive
participants had a lower mean bacterial load than HIV-
negative participants “(3.8 log10 eCFU per mL [SD 1.6] vs
5.2 log10 eCFU per mL [SD 1.3]; p = 0.0002). The median
MGIT time to positivity was 7 days (IQR 5–10), which was
associated with both Xpert-Ultra and TB-MBLA (r = 0.5, p
= 0.021)” (Sabiiti et al., 2020). Notably, the time to obtain
TB bacillary load results was significantly reduced from
days to hours, with early treatment responses detected by
the TB-MBLA assay. By week 12, 58% of patients showed
a reduction in bacillary load. This reduction was linked to
culture time-to-positivity (r = −0.51, p < 0.0001). Patients
with a higher bacillary burden before therapy were less
likely to convert to negative by week 8 (p = 0.0005) (
Neumann et al., 2025; Musisi et al., 2024). For smear-
negative TB, the sensitivities of both tests were similar
(Truenat MTB Plus: 55% vs Xpert: 53%). Regarding
specificity, Truenat MTB Plus showed 96% (95% CI: 94-
97%), while Xpert had a slightly higher specificity of 99%
(95% CI: 97-99%) (Ngangue et al., 2022).
In a cohort of 175 patients, 92.6% tested positive by Mini
PCR, while 84.6% were positive by smear microscopy. The
performance metrics of Z-N staining were as follows:
“sensitivity” 86.31%, “specificity” 57.14%, “positive
predictive value” (PPV) 97.97%, “negative predictive
value” (NPV) 14.81%, and accuracy 85.14%. In
comparison, the performance of TrueNat was as follows:
“sensitivity” 94.05%, “specificity” 42.86%, PPV 97.53%,
NPV 23.08%, and accuracy 92.00% (Akhtar et al., 2022).
This study was performed at a single tertiary care centre, so
the outcome result may not be directly applicable to regions
with different TB burdens or healthcare infrastructures.
Additionally, Truenat was only compared to microscopy,
not to MGIT culture systems or other advanced molecular
diagnostic methods, which could provide a more
comprehensive evaluation of its performance. The study
also did not account for potential co-infections or
comorbidities, such as HIV, which can influence both TB
diagnosis and treatment outcomes.
CONCLUSION
This study highlights the higher prevalence of pulmonary
TB among adult males, particularly those in the working-
age group, with a significant association between gender
and bacillary load. A strong correlation was observed
between smear grading and Truenat CFU/mL values,
validating smear microscopy as a practical indicator of
infectivity while confirming Truenat's superior sensitivity
and specificity in TB diagnosis. The findings emphasize the
value of bacterial load quantification in assessing disease
severity and underscore Truenat's potential as a more
accurate diagnostic tool, especially in settings where early
and reliable detection is critical for TB control.
ACKNOWLEDGMENT
The authors are grateful to District Tuberculosis Officer,
for helping to reach the cave and perform the sample
testing. The authors are grateful to the Department of
Microbiology Vedantaa Institute of Medical Sciences and
Research Centre, laboratory staff.
CONFLICT OF INTERESTS
The authors declare no conflict of interest
ETHICS APPROVAL
Sputum samples were collected and processed in
accordance with institutional protocols, ensuring adherence
to relevant biosafety and ethical guidelines (Approval
number: EC/VIMS/12/2023).
FUNDING
This study received no specific funding from public,
commercial, or not-for-profit funding agencies.
AI TOOL DECLARATION
The authors declares that no AI and related tools are used to
write the scientific content of this manuscript.
DATA AVAILABILITY
Data will be available on request
REFERENCES
Akhtar, S., Kaur, A., Kumar, D., Sahni, B., Chouhan, R.,
Tabassum, N., & Gandhi, S. G. (2022). Diagnostic
accuracy between CBNAAT, TrueNat, and smear
microscopy for diagnosis of pulmonary tuberculosis in
Doda District of Jammu and Kashmir: A comparative
study. Journal of Clinical and Diagnostic Research,
16(11), DC08–DC12.
https://doi.org/10.7860/jcdr/2022/59404.17055
Ali, H., Zeynudin, A., Mekonnen, A., Abera, S., & Ali, S.
(2012). Smear positive pulmonary tuberculosis (PTB)
prevalence amongst patients at Agaro Teaching Health
Center, South West Ethiopia. Ethiopian Journal of Health
Sciences, 22(1), 71–76.
www.ijzab.com 72
Among 520 pulmonary TB cases, “16.35% (95% CI:
13.40%, 19.79%) tested sputum smear-negative. Of the
remaining patients, 15.19% (95% CI: 13.40%, 19.79%) had
scanty (1 to 9 bacilli)” results, 18.27% (95% CI: 12.35%,
18.55%) had 1+, 15.77% (95% CI: 12.87%, 19.17%) had
2+, and 34.42% (95% CI: 30.45%, 38.65%) had 3+ smear
grades, respectively. In total, the sputum smear-positive
rate was 83.65% (95% CI: 80.21%, 86.60%) ( Kassa et al.,
2021). Among the positive cases, 40.1% had a 3+ grade,
while 6.8% had a scanty grade. The treatment success rate
was lowest in the scanty group (71.4%), followed by 1+
(80.2%), with the highest success rate observed in sputum
smear-negative cases (84.1%). The overall failure rate was
16.9%. Increased risks of poor outcomes were observed in
patients over 40 years old, males, and those undergoing
retreatment. The TB-MBLA assay quantified a “bacterial
load of 4.8 log10 eCFU per mL (SD 1.5)”. HIV-positive
participants had a lower mean bacterial load than HIV-
negative participants “(3.8 log10 eCFU per mL [SD 1.6] vs
5.2 log10 eCFU per mL [SD 1.3]; p = 0.0002). The median
MGIT time to positivity was 7 days (IQR 5–10), which was
associated with both Xpert-Ultra and TB-MBLA (r = 0.5, p
= 0.021)” (Sabiiti et al., 2020). Notably, the time to obtain
TB bacillary load results was significantly reduced from
days to hours, with early treatment responses detected by
the TB-MBLA assay. By week 12, 58% of patients showed
a reduction in bacillary load. This reduction was linked to
culture time-to-positivity (r = −0.51, p < 0.0001). Patients
with a higher bacillary burden before therapy were less
likely to convert to negative by week 8 (p = 0.0005) (
Neumann et al., 2025; Musisi et al., 2024). For smear-
negative TB, the sensitivities of both tests were similar
(Truenat MTB Plus: 55% vs Xpert: 53%). Regarding
specificity, Truenat MTB Plus showed 96% (95% CI: 94-
97%), while Xpert had a slightly higher specificity of 99%
(95% CI: 97-99%) (Ngangue et al., 2022).
In a cohort of 175 patients, 92.6% tested positive by Mini
PCR, while 84.6% were positive by smear microscopy. The
performance metrics of Z-N staining were as follows:
“sensitivity” 86.31%, “specificity” 57.14%, “positive
predictive value” (PPV) 97.97%, “negative predictive
value” (NPV) 14.81%, and accuracy 85.14%. In
comparison, the performance of TrueNat was as follows:
“sensitivity” 94.05%, “specificity” 42.86%, PPV 97.53%,
NPV 23.08%, and accuracy 92.00% (Akhtar et al., 2022).
This study was performed at a single tertiary care centre, so
the outcome result may not be directly applicable to regions
with different TB burdens or healthcare infrastructures.
Additionally, Truenat was only compared to microscopy,
not to MGIT culture systems or other advanced molecular
diagnostic methods, which could provide a more
comprehensive evaluation of its performance. The study
also did not account for potential co-infections or
comorbidities, such as HIV, which can influence both TB
diagnosis and treatment outcomes.
CONCLUSION
This study highlights the higher prevalence of pulmonary
TB among adult males, particularly those in the working-
age group, with a significant association between gender
and bacillary load. A strong correlation was observed
between smear grading and Truenat CFU/mL values,
validating smear microscopy as a practical indicator of
infectivity while confirming Truenat's superior sensitivity
and specificity in TB diagnosis. The findings emphasize the
value of bacterial load quantification in assessing disease
severity and underscore Truenat's potential as a more
accurate diagnostic tool, especially in settings where early
and reliable detection is critical for TB control.
ACKNOWLEDGMENT
The authors are grateful to District Tuberculosis Officer,
for helping to reach the cave and perform the sample
testing. The authors are grateful to the Department of
Microbiology Vedantaa Institute of Medical Sciences and
Research Centre, laboratory staff.
CONFLICT OF INTERESTS
The authors declare no conflict of interest
ETHICS APPROVAL
Sputum samples were collected and processed in
accordance with institutional protocols, ensuring adherence
to relevant biosafety and ethical guidelines (Approval
number: EC/VIMS/12/2023).
FUNDING
This study received no specific funding from public,
commercial, or not-for-profit funding agencies.
AI TOOL DECLARATION
The authors declares that no AI and related tools are used to
write the scientific content of this manuscript.
DATA AVAILABILITY
Data will be available on request
REFERENCES
Akhtar, S., Kaur, A., Kumar, D., Sahni, B., Chouhan, R.,
Tabassum, N., & Gandhi, S. G. (2022). Diagnostic
accuracy between CBNAAT, TrueNat, and smear
microscopy for diagnosis of pulmonary tuberculosis in
Doda District of Jammu and Kashmir: A comparative
study. Journal of Clinical and Diagnostic Research,
16(11), DC08–DC12.
https://doi.org/10.7860/jcdr/2022/59404.17055
Ali, H., Zeynudin, A., Mekonnen, A., Abera, S., & Ali, S.
(2012). Smear positive pulmonary tuberculosis (PTB)
prevalence amongst patients at Agaro Teaching Health
Center, South West Ethiopia. Ethiopian Journal of Health
Sciences, 22(1), 71–76.
Khutade Kalpesh et al. Int. J. Zool. Appl. Biosci., 10(5), 67-74, 2025
www.ijzab.com 73
Brahmapurkar, K., Brahmapurkar, V., & Zodpey, S.
(2017). Sputum smear grading and treatment outcome
among directly observed treatment-short course patients
of tuberculosis unit, Jagdalpur, Bastar. Journal of Family
Medicine and Primary Care, 6(2), 293.
Khutade, K., Shah, H., & Yadav, D. (2023). Smear positive
pulmonary tuberculosis patients: An epidemiological
perspective. International Journal of Health Sciences and
Research, 13(9), 7–11.
https://doi.org/10.52403/ijhsr.20230902
World Health Organization. (2022). Global tuberculosis
report 2022.
https://iris.who.int/bitstream/handle/10665/363752/97892
40061729-eng.pdf?sequence
Hai, H. T., Sabiiti, W., Thu, D. D. A., Phu, N. H., Gillespie,
S. H., Thwaites, G. E., & Thuong, N. T. T. (2021).
Evaluation of the molecular bacterial load assay for
detecting viable Mycobacterium tuberculosis in
cerebrospinal fluid before and during tuberculous
meningitis treatment. Tuberculosis (Edinburgh,
Scotland), 128, 102084.
https://doi.org/10.1016/j.tube.2021.102084
Hazra, D., Shenoy, V., & Chawla, K. (2019). Same-day
sputum microscopy for screening of pulmonary
tuberculosis: Its accuracy and usefulness in comparison
with conventional method. Journal of Pure and Applied
Microbiology, 13(2), 1251–1256.
https://doi.org/10.22207/jpam.13.2.67
Imam, T., & Oyeyi, T. (2010). A retrospective study of
pulmonary tuberculosis (PTB) prevalence amongst
patients attending Infectious Diseases Hospital, in Kano,
Nigeria. Bayero Journal of Pure and Applied Sciences,
1(1). https://doi.org/10.4314/bajopas.v1i1.57503
Kassa, G. M., Merid, M. W., Muluneh, A. G., & Fentie, D.
T. (2021). Sputum smear grading and associated factors
among bacteriologically confirmed pulmonary drug-
resistant tuberculosis patients in Ethiopia. BMC Infectious
Diseases, 21(1), 238. https://doi.org/10.1186/s12879-021-
05933-y
Khan, J. A., Irfan, M., Zaki, A., Beg, M., Hussain, S. F., &
Rizvi, N. (2006). Knowledge, attitude and
misconceptions regarding tuberculosis in Pakistani
patients. Journal of the Pakistan Medical Association,
56(5), 211–214.
Khutade, K., Patil, S., Shah, H., & Patel, H. (2024). The
diagnostic concordance between micro real-time PCR and
Lowenstein Jensen (LJ) media assays for pulmonary
tuberculosis detection with associated clinical
characteristics. IP International Journal of Medical
Microbiology and Tropical Diseases, 10(1), 41–47.
https://doi.org/10.18231/j.ijmmtd.2024.008
MacLean, E., Kohli, M., Weber, S. F., Suresh, A.,
Schumacher, S. G., Denkinger, C. M., & Pai, M. (2020).
Advances in molecular diagnosis of tuberculosis. Journal
of Clinical Microbiology, 58(10), e01582-19.
https://doi.org/10.1128/JCM.01582-19
Magar, P., Thapa, E., Rana, R., Joshi, R., Maharjan, B., &
Thapa, N. (2020). Prevalence of tuberculosis by
GeneXpert method in Karnali Academy of Health
Sciences Teaching Hospital. Biomedical Sciences, 6(3),
56–60.
Mistry, Y., Rajdev, S., & Mullan, S. (2016). Use of cost
effective semi-automated (manual/micro) MGIT system
over BACTEC 960 to perform first line anti-tuberculosis
drugs sensitivity testing. Journal of Tuberculosis
Research, 4(4), 227–234.
https://doi.org/10.4236/jtr.2016.44025
World Health Organization. (2024). Global tuberculosis
report 2024. https://www.who.int/teams/global-
programme-on-tuberculosis-and-lung-health/tb-reports
Wagh, S., Khutade, K., & Shah, H. (2024). An array of
various microbiological diagnostic modalities for
pulmonary tuberculosis: A review. Indian Journal of
Microbiology Research, 11(3), 147–155.
https://doi.org/10.18231/j.ijmr.2024.028
Molbio. (2025). Truenat assays precision, efficiency, and
reliability. https://www.molbiodiagnostics.com/truenat-
assays/
Sah, M. K., Maharjan, K., Aryal, P., Jha, A. K., Jha, G., &
Shrestha, S. R. (2020). Pulmonary tuberculosis at Patan
Hospital, Nepal: One year audit. Journal of Clinical
Tuberculosis and Other Mycobacterial Diseases, 22,
100207. https://doi.org/10.1016/j.jctube.2020.100207
Banti, A. B., Winje, B. A., Hinderaker, S. G., Heldal, E.,
Abebe, M., Dangisso, M. H., & Datiko, D. G. (2023).
Prevalence and incidence of symptomatic pulmonary
tuberculosis based on repeated population screening in a
district in Ethiopia: A prospective cohort study. BMJ
Open, 13(7), e070594. https://doi.org/10.1136/bmjopen-
2022-070594
Ukoaka, B. M., Daniel, F. M., Wagwula, P. M., Ahmed, M.
M., Udam, N. G., Okesanya, O. J., Babalola, A., Wali, T.
A., Afolabi, S., Udoh, R. A., Peter, I. G., & Maaji, L. A.
(2024). Prevalence, clinical characteristics, and treatment
outcomes of childhood tuberculosis in Nigeria: A
systematic review and meta-analysis. BMC Infectious
Diseases, 24(1), 1447. https://doi.org/10.1186/s12879-
024-10321-3
Ahmad, N., Baharom, M., Aizuddin, A. N., & Ramli, R.
(2021). Sex-related differences in smear-positive
pulmonary tuberculosis patients in Kuala Lumpur,
Malaysia: Prevalence and associated factors. PLoS One,
16(1), e0245304.
Jawad, M., Bilal, A., Khan, S., Rizwan, M., & Arshad, M.
(2023). Prevalence and awareness survey of tuberculosis
in the suspected population of Bajaur Agency in FATA,
Pakistan. Pakistan Journal of Health Sciences, 56–61.
www.ijzab.com 73
Brahmapurkar, K., Brahmapurkar, V., & Zodpey, S.
(2017). Sputum smear grading and treatment outcome
among directly observed treatment-short course patients
of tuberculosis unit, Jagdalpur, Bastar. Journal of Family
Medicine and Primary Care, 6(2), 293.
Khutade, K., Shah, H., & Yadav, D. (2023). Smear positive
pulmonary tuberculosis patients: An epidemiological
perspective. International Journal of Health Sciences and
Research, 13(9), 7–11.
https://doi.org/10.52403/ijhsr.20230902
World Health Organization. (2022). Global tuberculosis
report 2022.
https://iris.who.int/bitstream/handle/10665/363752/97892
40061729-eng.pdf?sequence
Hai, H. T., Sabiiti, W., Thu, D. D. A., Phu, N. H., Gillespie,
S. H., Thwaites, G. E., & Thuong, N. T. T. (2021).
Evaluation of the molecular bacterial load assay for
detecting viable Mycobacterium tuberculosis in
cerebrospinal fluid before and during tuberculous
meningitis treatment. Tuberculosis (Edinburgh,
Scotland), 128, 102084.
https://doi.org/10.1016/j.tube.2021.102084
Hazra, D., Shenoy, V., & Chawla, K. (2019). Same-day
sputum microscopy for screening of pulmonary
tuberculosis: Its accuracy and usefulness in comparison
with conventional method. Journal of Pure and Applied
Microbiology, 13(2), 1251–1256.
https://doi.org/10.22207/jpam.13.2.67
Imam, T., & Oyeyi, T. (2010). A retrospective study of
pulmonary tuberculosis (PTB) prevalence amongst
patients attending Infectious Diseases Hospital, in Kano,
Nigeria. Bayero Journal of Pure and Applied Sciences,
1(1). https://doi.org/10.4314/bajopas.v1i1.57503
Kassa, G. M., Merid, M. W., Muluneh, A. G., & Fentie, D.
T. (2021). Sputum smear grading and associated factors
among bacteriologically confirmed pulmonary drug-
resistant tuberculosis patients in Ethiopia. BMC Infectious
Diseases, 21(1), 238. https://doi.org/10.1186/s12879-021-
05933-y
Khan, J. A., Irfan, M., Zaki, A., Beg, M., Hussain, S. F., &
Rizvi, N. (2006). Knowledge, attitude and
misconceptions regarding tuberculosis in Pakistani
patients. Journal of the Pakistan Medical Association,
56(5), 211–214.
Khutade, K., Patil, S., Shah, H., & Patel, H. (2024). The
diagnostic concordance between micro real-time PCR and
Lowenstein Jensen (LJ) media assays for pulmonary
tuberculosis detection with associated clinical
characteristics. IP International Journal of Medical
Microbiology and Tropical Diseases, 10(1), 41–47.
https://doi.org/10.18231/j.ijmmtd.2024.008
MacLean, E., Kohli, M., Weber, S. F., Suresh, A.,
Schumacher, S. G., Denkinger, C. M., & Pai, M. (2020).
Advances in molecular diagnosis of tuberculosis. Journal
of Clinical Microbiology, 58(10), e01582-19.
https://doi.org/10.1128/JCM.01582-19
Magar, P., Thapa, E., Rana, R., Joshi, R., Maharjan, B., &
Thapa, N. (2020). Prevalence of tuberculosis by
GeneXpert method in Karnali Academy of Health
Sciences Teaching Hospital. Biomedical Sciences, 6(3),
56–60.
Mistry, Y., Rajdev, S., & Mullan, S. (2016). Use of cost
effective semi-automated (manual/micro) MGIT system
over BACTEC 960 to perform first line anti-tuberculosis
drugs sensitivity testing. Journal of Tuberculosis
Research, 4(4), 227–234.
https://doi.org/10.4236/jtr.2016.44025
World Health Organization. (2024). Global tuberculosis
report 2024. https://www.who.int/teams/global-
programme-on-tuberculosis-and-lung-health/tb-reports
Wagh, S., Khutade, K., & Shah, H. (2024). An array of
various microbiological diagnostic modalities for
pulmonary tuberculosis: A review. Indian Journal of
Microbiology Research, 11(3), 147–155.
https://doi.org/10.18231/j.ijmr.2024.028
Molbio. (2025). Truenat assays precision, efficiency, and
reliability. https://www.molbiodiagnostics.com/truenat-
assays/
Sah, M. K., Maharjan, K., Aryal, P., Jha, A. K., Jha, G., &
Shrestha, S. R. (2020). Pulmonary tuberculosis at Patan
Hospital, Nepal: One year audit. Journal of Clinical
Tuberculosis and Other Mycobacterial Diseases, 22,
100207. https://doi.org/10.1016/j.jctube.2020.100207
Banti, A. B., Winje, B. A., Hinderaker, S. G., Heldal, E.,
Abebe, M., Dangisso, M. H., & Datiko, D. G. (2023).
Prevalence and incidence of symptomatic pulmonary
tuberculosis based on repeated population screening in a
district in Ethiopia: A prospective cohort study. BMJ
Open, 13(7), e070594. https://doi.org/10.1136/bmjopen-
2022-070594
Ukoaka, B. M., Daniel, F. M., Wagwula, P. M., Ahmed, M.
M., Udam, N. G., Okesanya, O. J., Babalola, A., Wali, T.
A., Afolabi, S., Udoh, R. A., Peter, I. G., & Maaji, L. A.
(2024). Prevalence, clinical characteristics, and treatment
outcomes of childhood tuberculosis in Nigeria: A
systematic review and meta-analysis. BMC Infectious
Diseases, 24(1), 1447. https://doi.org/10.1186/s12879-
024-10321-3
Ahmad, N., Baharom, M., Aizuddin, A. N., & Ramli, R.
(2021). Sex-related differences in smear-positive
pulmonary tuberculosis patients in Kuala Lumpur,
Malaysia: Prevalence and associated factors. PLoS One,
16(1), e0245304.
Jawad, M., Bilal, A., Khan, S., Rizwan, M., & Arshad, M.
(2023). Prevalence and awareness survey of tuberculosis
in the suspected population of Bajaur Agency in FATA,
Pakistan. Pakistan Journal of Health Sciences, 56–61.
Khutade Kalpesh et al. Int. J. Zool. Appl. Biosci., 10(5), 67-74, 2025
www.ijzab.com 74
Mohite, R., Mohite, V., Ganganahalli, P., & Lale, S.
(2014). Trend of tuberculosis and performance evaluation
of new sputum positive tuberculosis from Satara district,
India. Asian Journal of Medical Sciences, 6(4), 30–35.
https://doi.org/10.3126/ajms.v6i4.11112
Paudel, S., & Maharjan, M. (2018). Prevalence of
tuberculosis among PTB-suspected patients visiting
Lumbini Zonal Hospital. Asian Journal of Science and
Technology, 9(2), 7648–7671.
Smith, I. (2024). Gender and tuberculosis in Nepal. Journal
of Nepal Medical Association, 24(117), 49–58.
Sabiiti, W., Azam, K., Farmer, E. C. W., Kuchaka, D.,
Mtafya, B., Bowness, R., Oravcova, K., Honeyborne, I.,
Evangelopoulos, D., McHugh, T. D., Khosa, C., Rachow,
A., Heinrich, N., Kampira, E., Davies, G., Bhatt, N.,
Ntinginya, E. N., Viegas, S., Jani, I., Kamdolozi, M., &
Gillespie, S. H. (2020). Tuberculosis bacillary load, an
early marker of disease severity: The utility of
tuberculosis molecular bacterial load assay. Thorax,
75(7), 606–608. https://doi.org/10.1136/thoraxjnl-2019-
214238
Neumann, M., Reimann, M., Chesov, D., Popa, C.,
Dragomir, A., Popescu, O., Munteanu, R., Hölscher, A.,
Honeyborne, I., Heyckendorf, J., Lange, C., Hölscher, C.,
& Kalsdorf, B. (2025). The molecular bacterial load assay
predicts treatment responses in patients with pre-
XDR/XDR-tuberculosis more accurately than GeneXpert
Ultra MTB/Rif. Journal of Infection, 90(2), 106399.
https://doi.org/10.1016/j.jinf.2024.106399
Ngangue, Y. R., Mbuli, C., Neh, A., Nshom, E., Koudjou,
A., Palmer, D., Ndi, N. N., Qin, Z. Z., Creswell, J.,
Mbassa, V., Vuchas, C., & Sander, M. (2022). Diagnostic
accuracy of the Truenat MTB Plus assay and comparison
with the Xpert MTB/RIF assay to detect tuberculosis
among hospital outpatients in Cameroon. Journal of
Clinical Microbiology, 60(8), e0015522.
https://doi.org/10.1128/jcm.00155-22
Musisi, E., Wamutu, S., Ssengooba, W., Kasiinga, S.,
Sessolo, A., Sanyu, I., Kaswabuli, S., Zawedde, J.,
Byanyima, P., Kia, P., Muwambi, W., Toskin, D. T.,
Kigozi, E., Walbaum, N., Dombay, E., Legrady, M. B.,
Ssemambo, K. D., Joloba, M., Kuchaka, D., Worodria,
W., & Sabiiti, W. (2024). Accuracy of the tuberculosis
molecular bacterial load assay to diagnose and monitor
response to anti-tuberculosis therapy: A longitudinal
comparative study with standard-of-care smear
microscopy, Xpert MTB/RIF Ultra, and culture in
Uganda. The Lancet Microbe, 5(4), e345–e354.
https://doi.org/10.1016/S2666-5247(23)00367-1
www.ijzab.com 74
Mohite, R., Mohite, V., Ganganahalli, P., & Lale, S.
(2014). Trend of tuberculosis and performance evaluation
of new sputum positive tuberculosis from Satara district,
India. Asian Journal of Medical Sciences, 6(4), 30–35.
https://doi.org/10.3126/ajms.v6i4.11112
Paudel, S., & Maharjan, M. (2018). Prevalence of
tuberculosis among PTB-suspected patients visiting
Lumbini Zonal Hospital. Asian Journal of Science and
Technology, 9(2), 7648–7671.
Smith, I. (2024). Gender and tuberculosis in Nepal. Journal
of Nepal Medical Association, 24(117), 49–58.
Sabiiti, W., Azam, K., Farmer, E. C. W., Kuchaka, D.,
Mtafya, B., Bowness, R., Oravcova, K., Honeyborne, I.,
Evangelopoulos, D., McHugh, T. D., Khosa, C., Rachow,
A., Heinrich, N., Kampira, E., Davies, G., Bhatt, N.,
Ntinginya, E. N., Viegas, S., Jani, I., Kamdolozi, M., &
Gillespie, S. H. (2020). Tuberculosis bacillary load, an
early marker of disease severity: The utility of
tuberculosis molecular bacterial load assay. Thorax,
75(7), 606–608. https://doi.org/10.1136/thoraxjnl-2019-
214238
Neumann, M., Reimann, M., Chesov, D., Popa, C.,
Dragomir, A., Popescu, O., Munteanu, R., Hölscher, A.,
Honeyborne, I., Heyckendorf, J., Lange, C., Hölscher, C.,
& Kalsdorf, B. (2025). The molecular bacterial load assay
predicts treatment responses in patients with pre-
XDR/XDR-tuberculosis more accurately than GeneXpert
Ultra MTB/Rif. Journal of Infection, 90(2), 106399.
https://doi.org/10.1016/j.jinf.2024.106399
Ngangue, Y. R., Mbuli, C., Neh, A., Nshom, E., Koudjou,
A., Palmer, D., Ndi, N. N., Qin, Z. Z., Creswell, J.,
Mbassa, V., Vuchas, C., & Sander, M. (2022). Diagnostic
accuracy of the Truenat MTB Plus assay and comparison
with the Xpert MTB/RIF assay to detect tuberculosis
among hospital outpatients in Cameroon. Journal of
Clinical Microbiology, 60(8), e0015522.
https://doi.org/10.1128/jcm.00155-22
Musisi, E., Wamutu, S., Ssengooba, W., Kasiinga, S.,
Sessolo, A., Sanyu, I., Kaswabuli, S., Zawedde, J.,
Byanyima, P., Kia, P., Muwambi, W., Toskin, D. T.,
Kigozi, E., Walbaum, N., Dombay, E., Legrady, M. B.,
Ssemambo, K. D., Joloba, M., Kuchaka, D., Worodria,
W., & Sabiiti, W. (2024). Accuracy of the tuberculosis
molecular bacterial load assay to diagnose and monitor
response to anti-tuberculosis therapy: A longitudinal
comparative study with standard-of-care smear
microscopy, Xpert MTB/RIF Ultra, and culture in
Uganda. The Lancet Microbe, 5(4), e345–e354.
https://doi.org/10.1016/S2666-5247(23)00367-1