Abstract
Background:
Early detection of latent tuberculosis infection (LTBI) might prevent active TB development in healthcare workers (HCWs). The aim of the study is to assess the prevalence of LTBI among HCWs exposed to active TB, compare QFT-GIT and TST in the diagnosis of LTBI, and explore possible risk factors of LTBI.
Setting and Design:
This was a cross-sectional study for a period of 6 months among 153 HCWs in high-risk departments dealing with TB infection – Beni-Suef University Hospital, Egypt.
Materials and Methods:
HCWs were asked to fill a questionnaire for possible LTBI risk factors, and tuberculin skin test (TST) and serum QuantiFERON test were used for LTBI screening.
Statistical Analysis:
Statistical Package for Social Science (SPSS-18) was used for data analysis; qualitative data were compared using Chi-square test, while associations between risk factors for TB and positive QFT or TST were analyzed by a logistic regression model.
Results:
LTBI detected by QuantiFERON-TB Gold In-Tube Test (QFT-GIT) and by TST was 9.1% and 34.6%, respectively (kappa = 0.028). Logistic regression showed that departments, duration of work, the use of N95 masks, and training in infection control practices were significant predictors for positive QFT-GIT among participants (P < 0.05).
Conclusion:
Work duration of >10 years, nurse profession, diabetics, and smokers were at increased risk of having LTBI. Increased training programs and implementation of infection control measures TB to reduce the risk of LTBI are recommended.
Keywords: Healthcare workers, latent tuberculosis, QuantiFERON, TB infection
INTRODUCTION
Latent tuberculosis infection (LTBI) poses a health-related problem reported to be one-third of the world's population.[1] In Egypt, the TB prevalence was reported to be 15 per 100,000 citizens in 2014.[2] LTBI is not infectious with no disease manifestations resulting in persistent immune response against mycobacterium tuberculosis antigens; its reactivation is considered a source of active mycobacterial infection[1] with a 10%–15% risk of developing active TB.[3] Active TB among healthcare workers (HCWs) was reported to range from “67/100,000 up to 1180/100,000 inhabitant.”[4] HCWs are considered a high-risk group that might be infected by TB due to patients' contact and frequent handling of potentially infected material.[5] Lack of adherence to infection control policy measures, defective use of personal preventive measures such as N95 face masks, and poor work place ventilation are considered as the risk factors.[6] The median annual risk of LTBI among HCWs ranges from 2.9% to 7.2%.[4]
Most of HCWs with active TB develop when the risk of TB infection is undermined. Effective implementation of infection control practices is encouraged aiming to reduce the risk of TB infection. Screening of high-risk HCWs for LTBI by chest X-rays and TST is an important procedure. LTBI targeted chemoprophylaxis and treatment is an essential component of an effective TB control program.[7] The aim of diagnosing LTBI is to provide an early treatment for the condition and prevent its progress to active “tuberculosis.” LTBI is commonly asymptomatic without radiological or clinical evidence of active tuberculosis but with the senescence of inactive bacilli in tissues.[8]
Although TST is considered a standard test for latent TB, its main drawback is its low specificity (cannot differentiate between Mycobacterium tuberculosis infection, history of BCG vaccination, and infection with nontuberculous Mycobacteria.[9] Recently, QuantiFERON-TB Gold In-Tube Test (QFT-GIT) is used with a higher specificity.[10]
The aim of this study was to assess the prevalence of LTBI among high-risk HCWs exposed to infected patients with TB, compare QFT-GIT and TST in the diagnosis of LTBI, and explore possible LTBI risk factors.
MATERIALS AND METHODS
Design and settings
A cross-sectional study was conducted from February 2017 to July 2017 in Beni-Suef University Hospital, Egypt.
Ethical committee approval
Study objectives and procedures were explained in detail to all study participants; they were informed that their laboratory test results would not be declared. Participation in the study was optional, and an individually based written informed consent was performed prior to study onset. The study protocol was approved by the Faculty of Medicine, Beni-Suef University Research.
Study population and sampling technique
A convenient sample of 153 HCWs were included with a response rate of 81% (153/188), chosen from high-risk departments dealing with patients with TB and their specimens. The participants included 110 nurses, 12 laboratory technicians, and 31 workers and support staff who were currently working in the departments of chest diseases, internal/tropical medicine, intensive care units, the emergency unit, and laboratories. A pilot study was done before starting the study aiming to assess the disease prevalence and to ensure the clarity and easy handling of the questions for 30 nurses and laboratory technicians. Content validity was assessed by reviewing the literature. The reliability of the questionnaire was calculated using the test–retest method, and no statistical differences were found.
The exclusion criteria included the following:
A positive history of active TB,
History of household contact with patients with TB,
Clinical evidence of active TB, and
The use of immune-suppressive drugs.
Study procedure
The key record identification of the study participants was kept confidential except for the investigator responsible for interpretation of the laboratory results. A report for the overall latent TB infection prevalence rate was provided to the hospital management and the infection control authority for further action.
Study tools
Questionnaire
All participants were asked to fill a self-administered questionnaire. The questionnaire included questions about possible risk factors predisposing to LTBI such as age, gender, residence, profession, work duration, previous vaccination by BCG (presence of scarring), and associated medical “illness” namely diabetes mellitus and smoking history. In addition, there was a part that focused on infection control measures including frequency of hand rub, the use of respirators (N95), and previous training in infection control standards.
QuantiFERON-TB Gold In-Tube Test
A 3-mL blood sample was collected from each participant using three collection tubes. The first tube was precoated with three TB-specific antigens (ESAT-6, CFP-10, and TB7.7), the second tube was mitogen-positive control precoated with phytohem-agglutinin, and the third tube was the negative control coated with anticoagulant with no antigen. Thereafter, the tubes were incubated at 37°C for overnight and centrifuged for 10 min. Afterward, testing by enzyme-linked immunosorbent assay was done for interferon (IFN)-γ concentrations (IU/mL). A value of ≥0.35 IU/mL for IFN-γ in TB-antigen tube minus IFN-γ in the negative control tube was considered a positive result (supplier's instruction). If the IFN-γ level was <0.35 IU/mL in the TB-antigen tube and mitogen control was positive (≥0.5 IU/mL), the test was considered negative.[11]
Tuberculin skin test (TST)
Tuberculin skin test (TST) was performed using the Mantoux method by intradermal injection of 0.1 mL from 5 units of PPD (Tuberculin PPD, VacSera, Egypt). Two or three days later, a reaction of induration ≥10 mm was considered positive for HCW participants.[12]
Chest X-ray and sputum stain: Three successive sputum samples were collected for all participants to examine the sample for acid-fast bacilli to exclude an active TB disease with a negative test for them. Individual chest X-rays were examined by a radiology consultant from the Department of Radiology, Beni-Suef University Hospital.
Statistical analysis
Data collection and coding was done by researchers, and then data entry and analysis was done using Statistical Package for Social Science (SPSS) version 20. Qualitative data as frequency distribution and percentages were compared using Chi-square test, while quantitative data were compared and presented as means ± standard deviation. Agreement between TST and QFT-GIT results was assessed by kappa (κ < 0.4 = poor agreement, κ > 0.4–<0.75 = fair to good agreement, and κ > 0.75 = excellent agreement). Logistic regression was done to predict the risk factors. P value <0.05 was considered statistically significant.
RESULTS
With regard to study participants' general characteristics, most of the participants (71.9%) were nurses followed by workers and support staff (22%) and 4% were laboratory technicians. With regard to the medical service section, 47% of them were working in the departments of chest diseases, internal, and tropical medicine, while 42% in the intensive care and emergency units, and 11% in the laboratories.
The prevalence rate of LTBI among study participants detected by TST was 34.6%, and only 9.2% were confirmed by QFT-GIT [Table 1].
Table 1.
Prevalence of latent TB infection among study participants
| Test | Positive No (%) | Negative No (%) |
|---|---|---|
| TST | 53 (34.6) | 100 (65.4) |
| QFT-GIT | 14 (9.1) | 139 (90.8) |
QFT=QuantiFERON test; TST=tuberculin skin test
The overall agreement between the two test results was 50%, with a kappa of 0.028; considered as a poor agreement [Table 2].
Table 2.
Agreement between QFT-GIT and tuberculin skin test among study participants
| Group | Overall agreement | Kappa | P |
|---|---|---|---|
| All | 50% | 0.028 | 0.341 |
QFT=QuantiFERON test
Among participants whose screening showed a positive TST, 56.6% had a work experience of >10 years, 94.4% had a history of BCG vaccination, 28.3% were diabetics under medical treatment, and 34% were active smokers. Frequent use of hand rub was reported by 66% while using the N95 masks as personal protective equipment (PPE) was reported by 22.6%. Previous training in infection control practices was reported by 43.4%. There was a significant difference between profession, work duration, previous BCG vaccination, diabetes mellitus, smoking, using N95 masks, previous training in infection control practices, and TST results (P = 0.04, 0.01, 0.007, 0.001, 0.001, 0.03, and 0.002, respectively) [Table 3].
Table 3.
Association between risk factors and TST results among study participants
| Item | Tuberculin test |
|||||
|---|---|---|---|---|---|---|
| No. positive (≥10 mm) | Percentage | No. negative (≤10 mm) | Percentage | P | ||
| Age (years) | ≤30 | 27 | (50.9) | 57 | (57) | 0.474 |
| <30 | 26 | (49.1) | 43 | (43) | ||
| Gender | Male | 12 | (22.6) | 24 | (24) | 0.850 |
| Female | 41 | (77.4) | 76 | (76) | ||
| Residence | Rural | 28 | (52.8) | 53 | (53) | 0.766 |
| Urban | 25 | (47.2) | 47 | (47) | ||
| Profession | Nurse | 36 | (67.9) | 74 | (74) | 0.04 |
| Laboratory technician | 8 | (15.1) | 4 | (4) | ||
| Worker and support staff | 9 | (17) | 22 | (22) | ||
| Department | Chest, internal and tropical medicine | 26 | (49.1) | 47 | (47) | 0.550 |
| ICUs and emergency | 24 | (45.3) | 42 | (42) | ||
| Laboratories | 3 | (5.7) | 11 | (11) | ||
| Duration of work | ≤10 years | 23 | (43.4) | 67 | (67) | 0.01 |
| <10 years | 30 | (56.6) | 33 | (33) | ||
| Past BCG vaccine | Yes | 50 | (94.4) | 79 | (79) | 0.007 |
| No | 3 | (5.6) | 21 | (21) | ||
| Diabetes mellitus | Yes | 15 | (28.3) | 11 | (11) | 0.001 |
| No | 38 | (71.7) | 89 | (89) | ||
| Smoking | Yes | 18 | (34) | 5 | (5) | 0.001 |
| No | 35 | (66) | 95 | (95) | ||
| Using hand rub | Yes | 35 | (66) | 64 | (64) | 0.802 |
| No | 18 | (34) | 36 | (36) | ||
| Using (N95) respirators | Yes | 12 | (22.6) | 90 | (90) | 0.03 |
| No | 41 | (77.4) | 10 | (10) | ||
| Training in infection control | Yes | 23 | (43.4) | 69 | (69) | 0.002 |
| No | 30 | (56.6) | 31 | (31) | ||
TST=tuberculin skin test; ICU=intensive care unit. P value < 0.05 was considered statistically significant
Among participants with a positive QFT-GIT test, all of them had a work experience of >10 years, 93% had a history of BCG vaccination, 57.1% were diabetics, and 35.7% were active smokers. Frequent use of hand rub was reported by 78.6% and 42.9% reported using the N95 masks as a PPE. Previous training in infection control practices was reported by 78.6%. Similarly, there was a significant difference between clinical departments, work duration, use of hand rubs, use of N95 masks, previous training in infection control practices, and QFT-GIT test results (P = 0.03, 0.013, 0.001, 0.01, and 0.001, respectively) [Table 4].
Table 4.
Association between risk factors and QFT-GIT test results among study participants
| Item | QuantiFERON test |
|||||
|---|---|---|---|---|---|---|
| Positive no. | Percentage | Negative no. | Percentage | P | ||
| Age (years) | ≤30 | 6 | (42.9) | 78 | (56.1) | 0.961 |
| <30 | 8 | (57.1) | 61 | (43.9) | ||
| Gender | Male | 3 | (21.4) | 33 | (23.7) | 0.818 |
| Female | 11 | (78.6) | 106 | (76.3) | ||
| Residence | Rural | 8 | (57.1) | 73 | (52.5) | 0.696 |
| Urban | 6 | (42.9) | 66 | (47.5) | ||
| Profession | Nurse | 7 | (50) | 103 | (74.1) | 0.128 |
| Technician | 2 | (14.3) | 10 | (7.2) | ||
| Workerand support staff | 5 | (35.7) | 26 | (18.7) | ||
| Department | Chest, internal and tropical medicine | 9 | (64.3) | 64 | (46) | 0.03 |
| ICUs and emergency | 4 | (28.6) | 62 | (44.6) | ||
| Laboratory technicians | 1 | (7.1) | 13 | (9.4) | ||
| Duration of work | ≤10 years | 0 | (0) | 90 | (64.7) | 0.013 |
| <10 years | 14 | (100) | 49 | (35.3) | ||
| Past BCG vaccine | Yes | 13 | (93) | 116 | (83.5) | 0.103 |
| No | 1 | (7) | 23 | (16.5) | ||
| Diabetes mellitus | Yes | 8 | (57.1) | 18 | (13) | 0.696 |
| No | 6 | (42.9) | 121 | (87) | ||
| Smoking | Yes | 5 | (35.7) | 18 | (13) | 0.919 |
| No | 9 | (64.3) | 121 | (87) | ||
| Using hand rub | Yes | 11 | (78.6) | 88 | (63.3) | 0.001 |
| No | 3 | (21.4) | 51 | (36.7) | ||
| Using (N95) respirators | Yes | 6 | (42.9) | 96 | (69) | 0.01 |
| No | 8 | (57.1) | 43 | (31) | ||
| Training in infection control | Yes | 11 | (78.6) | 81 | (58.3) | 0.001 |
| No | 3 | (21.4) | 58 | (41.7) | ||
QFT-GIT=QuantiFERON-TB Gold In-Tube Test; ICU=intensive care unit. P value < 0.05 was considered statistically significant
Logistic regression showed that clinical departments, work duration, use of N95 masks, and training in infection control were significant predictors for positive QFT-GIT among study participants (P = 0.02, 0.004, 0.05, and 0.01, respectively) [Table 5].
Table 5.
Logistic regression for factors predicting results of QFT-GIT among study participants
| Predictors of +ve of QFT-GIT | B | SE | P | Exp (B) | 95% CI for EXP (B) |
|
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| Department | 2.468 | 1.064 | 0.02 | 0.085 | 0.011 | 0.683 |
| Duration of work | 1.324 | 0.680 | 0.004 | 3.759 | 0.991 | 14.249 |
| Using (N95) respirators | 2.168 | 0.748 | 0.05 | 0.114 | 0.026 | 0.496 |
| Training in infection control | 3.511 | 0.696 | 0.01 | 0.030 | 0.008 | 0.117 |
QFT-GIT=QuantiFERON-TB Gold In-Tube Test; SE=standard error; CI=confidence interval
DISCUSSION
In this study; LTBI prevalence among participants was 9.2% confirmed by QFT-GIT. These results are in agreement with the reported figures: 10.6% and 13.5% in similar national and international studies[13,14] and higher than the 3.4% LTBI prevalence reported in a Norwegian study,[15] while it was lower when compared with that reported in South Africa with LTBI prevalence rates of 33%.[16]
LTBI tested by TST was positive in 34.6%, a lower rate when compared with that reported in two similar studies with a rate of 44.4% and 48%, respectively.[17,18]
The difference between QFT-GIT (9.2%) and TST (34.6%) positivity was in accordance with similar previous studies.[19,20,21] High TST positivity could be attributed to its low specificity to differentiate between LTBI, vaccinated BCG participants, and mixed infections by nontuberculous organisms.
Study participants who worked for >10 years had a higher prevalence of LTBI, a finding which matches another national study results done in Zagazig University Hospitals[21] and in accordance with international studies reporting a 3-fold higher LTBI prevalence among HCWs with >10 years of employment.[22,23] This could be explained by the longer undermined exposure of continuous to TB.
Poor agreement (50%) between TST and QFT-GIT (κ = 0.28) is in agreement with other studies,[12,13,21] which reported similar agreement values between TST and QFT-GIT (51.5%, κ = <0.12). These findings approve and ascertain that QFT-GIT is better than TST in the diagnosis of LTBI for any high-risk group.
There was a statistically significant difference between profession as a risk factor and LTBI by TST [Table 3], in agreement with other study reports.[21,24] In addition, there was a significant difference (P = 0.001) between LTBI TST-positive participants and diabetes mellitus in addition to smoking rather than by QFT-GIT testing, contrary to a similar study which reported LTBI-positive QFT-GIT testing rather than by TST in diabetic nurses.[21]
A higher percentage of LTBI was reported among study participants working in the chest, internal, and tropical medicine departments – exposed to patients with TB – with a statistical significant difference between LTBI QFT-GIT-positive testing and work departments [Table 4]. Similar results were reported from national studies[14,21] and contrary to a German study which observed no significant association of interferon-gamma release assay (IGRA) positivity and workplace.[25]
The results of TST were higher in vaccinated BCG participants with no effect of prior vaccination for those examined by QFT-GIT. This is in agreement with a similar Egyptian study which reported the same results.[21] QFT-GIT test depends on specific M. TB antigens not affected by the vaccination status, and therefore is considered a useful tool in LTBI cases in Egypt where BCG vaccination is a national policy. The only obstacle to its use is its higher cost when compared with TST.
There was a significant difference between TST and QFT-GIT test and using N95 masks and previous infection control training; matching similar study reporting that inadequate use of N95 masks and poor work place ventilation were the contributing factors for TB infection.[6]
The results of this study regression analysis showed that department, work duration, the use of N95 masks, and training in infection control were significant predictors for positive QFT-GIT among study participants. These results match a similar Egyptian study reporting the same predictors for positive QFT-GIT (profession, work duration).[21]
CONCLUSION
The prevalence of LTBI identified by QFT-GIT and TST was 9.2% and 34.6%, respectively. Working >10 years, nursing profession, diabetics, and smokers were at increased risk of LTBI. BCG vaccination affected TST “results,” but not QFT-GIT test, making the latter a useful test for LTBI detection in Egypt where BCG vaccination is compulsory. Preemployment and annual screening for HCWs at high risk of TB should be done including a chest X-ray and TST followed by QFT-GIT for TST positive ones. Increased implementation of TB infection control measures and practices are recommended, especially with the use of N95 respirators as a PPE for minimizing healthcare-associated transmission and TB infection and should be standardized in Egyptian hospitals dealing with chest diseases aiming to reduce the risk of LTBI.
Declaration of patient consent
The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
Contributors
MA designed and supervised the study, drafted the article, and was involved in critical revision. DA, MS, and MM collected and analyzed the data. DA, MS, NK, and RL carried out the laboratory work. MA and HE conducted the statistical analyses. All authors reviewed and approved the final version of the article.
Acknowledgement
The authors would like to thank all participants and other healthcare workers who helped all through the process of the research.
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