Skip to main content
Download PDF

Drug resistance in drug-resistant tuberculosis patients with and without diabetes mellitus: a comparative analysis

BMC Infectious Diseases volume 24, Article number: 807 (2024) Cite this article

Abstract

Background

This dual burden of tuberculosis (TB) and diabetes mellitus (DM) has become a global public health concern. This study aims to compare drug resistance in drug-resistant tuberculosis (DR-TB) patients with and without DM and analyse the risk factors of multidrug-resistant tuberculosis (MDR-TB).

Methods

A total of 893 DR-TB patients were admitted to Wenzhou Central Hospital between January 2018 and December 2022. After excluding 178 cases with incomplete clinical and laboratory data, 715 patients were included in the study. These patients were then categorized into two groups based on the presence of type 2 DM: the DM group (160 cases) and the non-DM group (555 cases). Demographic information, baseline clinical characteristics, laboratory and imaging test results, clinical diagnoses, and other relevant data were collected for analysis. Statistical analysis was conducted on demographic information, clinical parameters, drug resistance spectrum, and risk factors for multidrug resistance.

Results

In both the DM and non-DM groups, the order of resistance to first-line anti-tuberculosis drugs is isoniazid, streptomycin, rifampicin, and ethambutol. There is no significant difference in the proportion of mono-resistant tuberculosis, polydrug-resistant tuberculosis, and multidrug-resistant tuberculosis between the two groups (P > 0.05). The prevalence of MDR-TB in both groups shows a downward trend between 2018 and 2022, but the trend is not statistically significant (P > 0.05). Among patients without DM, residence in rural areas, retreatment of tuberculosis, pulmonary cavity, and uric acid ≥ 346 µmol/L are identified as independent risk factors for MDR-TB. Among patients with DM, residence in rural areas, retreatment of tuberculosis, pulmonary cavity, and HbA1c ≥ 9.8% were identified as independent risk factors for MDR-TB.

Conclusion

Isoniazid is the most resistant drug among DR-TB patients with and without DM. There is no statistically significant difference in drug resistance patterns between the two groups. Some progress has been made in the prevention and control of DR-TB in this area, but the effect is not very significant. There are differences in the risk factors of MDR-TB between patients with and without DM.

Peer Review reports

Background

Tuberculosis (TB) remains the leading infectious disease causing human mortality and posing significant risks to human health [1]. As per the 2023 global Tuberculosis report, it is estimated that there were 10.6 million TB cases and 1.3 million deaths in 2022, with an incidence rate of 133 per 100,000 [2]. Despite the World Health Organization setting the ambitious goal of eradicating TB by 2035 in 2014, numerous challenges persist [3]. One major challenge is the emergence of drug-resistant tuberculosis (DR-TB), which severely hampers TB prevention and treatment efforts. Recent data reveals that approximately 410,000 individuals worldwide are afflicted with multidrug-resistant/rifampicin-resistant tuberculosis (MDR/RR-TB), while the success rate of treating DR-TB is only 63% [2]. Gaining an understanding of the current state of drug resistance in TB holds significant importance in evaluating and adjusting strategies for TB prevention, control, and treatment.

With an aging population and changes in lifestyle, it is estimated by the International Diabetes Federation that the number of people worldwide with diabetes mellitus (DM) will reach 537 million by 2021, and is expected to increase to 643 million by 2030 [4]. The prevalence of DM is closely linked to the incidence of TB. Research has revealed that 8 out of the top 10 countries with the highest DM incidence are also burdened with high TB rates [5]. This dual burden of TB and DM has become a global public health concern. China has the third highest burden of TB in the world. Previous studies have shown that Wenzhou has a heavy burden of DR-TB [6]. Additionally, factors such as the aging population and fast-paced lifestyle in Wenzhou increase the implications of the heavy DM burden [7]. Although it is widely agreed that DM negatively impacts the incidence and effectiveness of TB treatment, there is limited research on the relationship between DR-TB and DM, and the findings vary across different regions [8, 9]. Therefore, this study aims to analyse the differences in drug resistance between DR-TB patients with and without DM in Wenzhou, as well as identify the risk factors for MDR-TB. The findings of this study can serve as a valuable reference for clinical diagnosis and treatment.

Methods

Patient selection

A total of 893 patients with DR-TB were admitted to Wenzhou Central Hospital between January 2018 and December 2022. Among them, 178 cases with incomplete clinical and laboratory data were excluded. The study finally included 715 patients, who were divided into two groups: the DM group (160 cases) and the non-DM group (555 cases), based on whether they were combined with type 2 DM (Fig. 1). This study has been approved by the hospital medical ethics (batch No. L2023-04-163), utilising retrospective and anonymous data collection methods, which did not involve patient privacy. All experiments were carried out in compliance with relevant laws and guidelines and with the ethical standards of the Declaration of Helsinki.

Fig. 1
figure 1

Flow chart of the patients enrolled in the study. Abbreviation: DM, diabetes mellitus

Full size image

Data collection

The medical records of 715 DR-TB patients were reviewed. The clinical information was collected retrospectively, including the demographic information (age, sex, marriage, nationality, occupation, migration status, residence, age was grouped and analyzed in decades, the urban and rural typologies for the Chinese geographical regions were defined based on the “Provisions on the Statistical Division of Urban and Rural Areas” produced by the National Bureau of Statistics, which considered the differences in demographic, social and economic development [10]), baseline clinical characteristics (fever, cough, expectoration, hemoptysis, thoracodynia, chest tightness, fatigue, emaciation, night sweats), laboratory test results at first admission (erythrocyte sedimentation rate test, blood routine examination, biochemical examination, glycosylated hemoglobin test, acid-fast smear examination), CT imaging examination (pulmonary cavity condition, cavity is defined as an air-containing space within a pulmonary infiltrate or mass with a wall thicker than 4 mm [11]), and clinical diagnosis (diagnosis of type 2 DM and types of TB).

Definitions

Any drug resistance is defined as resistance to one anti-TB drug. Mono-resistant tuberculosis (MR-TB) is defined as resistance to one first-line anti-TB drug only [12]. Polydrug-resistant tuberculosis (PDR-TB) is defined as resistance to two or more first-line anti-TB drugs (except both isoniazid and rifampicin) [12]. Multidrug-resistant tuberculosis (MDR-TB) is defined as resistance to at least both isoniazid and rifampicin [12].

Initial treatment TB refers to three subcategories: (a) patients who have never received anti-TB drugs for TB, (b) patients who have not completed the entire course of standard chemotherapy treatment, and (c) patients who have received irregular chemotherapy for less than one month.

Retreatment TB refers to two subcategories: (a) patients who have been treated with anti-TB drugs for more than one month due to unreasonable or irregular use, and (b) patients who have experienced initial treatment failure and recurrence.

Laboratory examinations and drug susceptibility testing

The Mindray BC-6200 full-automatic hematology analyzer (Mindray, Shenzhen, China) was utilized for routine blood testing. For erythrocyte sedimentation rate testing, the ALIFAX ROLLER 20 fully automatic meter (ALIFAX, Padova, Italy) was employed. Biochemical detection was performed using the Beckman Coulter AU680 analyzer (Beckman Coulter, CA, USA). Lastly, the Premier HB9210 glycosylated hemoglobin meter (Primus, KS, USA) was used for HA1bC detection. All tests were performed according to the manufacturer’s instructions.

Sputum or bronchoalveolar lavage fluid samples of 5 ml were collected from patients upon admission. The specimens were pre-treated with NALC-NaOH and then inoculated into BACTEC MGIT liquid culture tubes for mycobacterial culture at 37 ℃. Clinical isolates obtained from positive cultures were differentiated Mycobacterium tuberculosis (MTB) from other mycobacteria through acid-fast smear microscopy combined with MPB64 antigen detection [13]. Drug susceptibility testing of MTB was conducted using the MGIT liquid method, following the operating instructions for both the instrument and reagents [14]. The concentrations of the four first-line anti-tuberculosis drugs were as follows: 0.1 µg/mL for isoniazid, 1.0 µg/mL for rifampicin, 1.0 µg/mL for streptomycin, and 5.0 µg/mL for ethambutol.

Statistical analysis

Statistical analyses were performed using SPSS software (version 26.0, IBM, New York, USA). The counting data were presented as frequency and percentage. The patient’s laboratory test results were dichotomized using the mean as the cut-off value, and comparisons of classified variables were performed using the chi-square test or Fisher’s exact test. The chi-square trend test was employed to examine the change and trend of the MDR-TB model over time. The patients were divided into DM and non-DM groups according to whether they were combined with type 2 DM or not, and the demographic and clinical data of the patients were subjected to univariate logistic analysis, and the variables for which statistical significance existed in the univariate analysis were then subjected to multivariate logistic regression analysis, so as to explore the risk factors for the occurrence of MDR-TB in patients of the DM and non-DM groups, respectively. A significance level of P-value < 0.05 was considered statistically significant.

Result

Patients’ characteristics

A total of 715 patients with DR-TB were included in this study. Among them, 160 cases (22.38%) were complicated with DM, while 555 (77.62%) did not have DM. The proportion of males is higher in the DM group compared to the non-DM group (83.75% vs. 72.07%, P < 0.05). Regarding patients, the highest percentage of patients were 51 ∼ 60 years old (17.35%). However, the DM group had the highest proportion of patients in this age range (27.50%), while the non-DM group had the highest proportion of patients aged 21 ∼ 30 years old (21.26%) (Fig. 2). The DM group also had higher proportions of married patients, smoking and drinking histories compared to the non-DM group (86.88% vs. 70.63%, 39.38% vs. 26.49%, 28.13% vs. 15.50%, all P < 0.05). The DM group have higher proportions of patients with symptoms such as cough, expectoration, emaciation, and Pulmonary cavity compared to the non-DM group (82.50% vs. 74.60%, 75.63% vs. 64.14%, 24.38% vs. 15.32%, 71.25% vs. 47.93%, all P < 0.05) (Table 1). Rgarding laboratory findings, the DM group have higher rates of elevated erythrocyte sedimentation rate (ESR, ≥ 39 mm/h), fasting plasma glucose (FPG, ≥ 6.1mmol/L), total cholesterol (TC, ≥ 3.82mmol/L), triglyceride (TG, ≥ 1.10mmol/L), C-reactive protein (CRP, ≥ 37.3 mg/L), and acid fast smear (AFS) positive results compared to the non-DM group (54.38% vs. 42.52%, 86.88% vs. 8.83%, 53.75% vs. 39.64%, 55.63% vs. 32.07%, 44.38% vs. 35.14%, 63.75% vs. 43.24%, all P < 0.05). However, the DM group have a lower proportion of albumin (ALB, ≥ 36.4 g/L) and prealbumin (PA, ≥ 171 mg/L) compared to the non-DM group (38.13% vs. 54.96%, 40.63% vs. 50.27%, P < 0.05) (Table 1).

Fig. 2
figure 2

Proportion of DR-TB with and without DM patients in different age groups. Abbreviation: DM, diabetes mellitus

Full size image
Table 1 The demographic and clinical parameters of DR-TB patients without and with DM
Full size table

Drug resistance of patients to first-line anti-TB drugs

The resistance rates of DM group and non-DM group to streptomycin, isoniazid, rifampicin and ethambutol were 63.13% and 61.08%, 76.88% and 77.29%, 54.37% and 51.17%, 18.12% and 16.39%, respectively. The order of drug resistance of the two groups to first-line anti-TB drugs was isoniazid, streptomycin, rifampicin and ethambutol. The proportion of MR-TB in the DM group and the non-DM group is 33.76% and 38.39% respectively. The proportion of PDR-TB is 19.38% and 16.21%, respectively, and the proportion of MDR-TB is 46.87% and 45.40% respectively (Table 2).

Annual drug resistance trends for MDR-TB from 2018 to 2022

Among the 715 patients, the rate of MDR-TB decreased from 54.67% in 2018 to 46.29% in 2022, with an average annual decrease of 4.07% (P = 0.057). Among the 555 patients without MDR-TB, the rate of MDR-TB decreased from 51.69% in 2018 to 45.57% in 2022, with an average annual decrease of 3.10% (P = 0.750). Among the 160 patients with DM, the prevalence rate of MDR-TB decreased from 65.63% in 2018 to 48.27% in 2022, with an average annual decline of 7.40% (P = 0.226) (Fig. 3).

Fig. 3
figure 3

Trends in the proportion of MDR among DR-TB patients without and with DM from 2018 to 2022. Abbreviation: DM, diabetes mellitus

Full size image

Risk factors of MDR-TB

Multivariate analysis shows that among patients without DM, the risk of MDR-TB in rural residents is 1.984 times higher than in urban residents (OR = 1.984, 95% CI: 1.339–2.954, P < 0.05). The risk of MDR-TB in retreated patients with TB is 3.772 times higher than in initially treated patients (OR = 3.772, 95% CI: 2.302–6.297, P < 0.05), the risk of MDR-TB in patients with pulmonary cavity is 3.029 times higher than in patients without pulmonary cavity (OR = 3.029, 95% CI: 2.027–4.564, P < 0.05), and the risk of MDR-TB in patients with uric acid (UA) ≥ 346 µmol/L is 2.266 times higher than in patients with UA < 346 µmol/L (OR = 2.266, 95% CI: 1.496–3.453, P < 0.05). The presence of emaciation and CRP levels ≥ 37.3 mg/L were identified as protective factors against the development of MDR-TB in patients. Patients with emaciation had a 0.437 times lower risk of MDR-TB compared to non-emaciated patients (OR = 0.437, 95% CI: 0.238–0.786, P < 0.05), while patients with CRP levels ≥ 37.3 mg/L had a 0.532 times lower risk of MDR-TB compared to those with CRP < 37.3 mg/L (OR = 0.532, 95% CI: 0.315–0.892, P < 0.05) (Table 3). Among DM patients, the risk of MDR-TB in rural residents is 3.197 times higher than in urban residents (OR = 3.197, 95% CI: 1.596–6.580, P < 0.05), and the risk of MDR-TB in retreated patients with TB is 3.141 times higher than in initially treated patients (OR = 3.141, 95% CI: 1.354–7.705, P < 0.05). The risk of developing MDR-TB in patients with a pulmonary cavity is 3.806 times higher than in patients without pulmonary cavity (OR = 3.806, 95% CI: 1.688–9.157, P < 0.05); the risk of developing MDR-TB in patients with HbA1c ≥ 9.8% is 2.215 times higher than in patients with HbA1c < 9.8% (OR = 2.215, 95% CI: 1.100-4.543, P < 0.05) (Table 4).

Table 2 Four first-line drug resistance profiles in DR-TB patients without and with DM
Full size table
Table 3 Risk factors of MDR-TB among DR-TB patients without DM
Full size table
Table 4 Risk factors of MDR-TB among DR-TB patients with DM
Full size table

Discussion

In this study, the clinical characteristics, drug resistance spectrum, drug resistance trend and risk factors of multi-drug resistance in DR-TB patients with and without DM in Wenzhou were analysed for the first time. The study found that compared with patients without DM, patients in the DM group had more men, older age, and a history of smoking and drinking, which is not difficult to explain. Previous studies have confirmed that men, old age, smoking and drinking are independent risk factors for diabetes and tuberculosis [15,16,17,18,19]. In addition, the proportion of married patients was higher in the DM group, which may be because the patients in the DM group were older and the proportion of married patients was relatively higher in older patients. Compared with DR-TB patients without DM, DR-TB patients with DM had more clinical symptoms such as cough, expectoration, emaciation and pulmonary cavity complications. DM can lead to a decline in the function of the immune system and increase the susceptibility of patients to MTB, so they may be more likely to show typical symptoms of TB, such as cough and expectoration [20]. The symptoms, such as weight loss, are more evident in DR-TB patients with DM due to metabolic disorders and malnutrition. Additionally, high blood glucose levels in diabetes affect the patient’s immune function, making it more likely to form cavities in the lungs [21].

Compared with DR-TB patients without DM, DR-TB patients with DM had a higher proportion of elevated ESR and CRP. Hyperglycemia in patients with DM can lead to vascular endothelial damage and increased inflammatory reaction [22]. Moreover, TB itself is also a serious inflammatory disease, which is more severe after DM, resulting in a more significant increase in ESR and CRP. The proportion of FPG, TC and TG in the DM group is higher. As we all know, DM patients experience insulin resistance or lack of insulin secretion, resulting in elevated blood glucose levels and lipid metabolism disorders, resulting in the increase of TC and TG [23]. Decreased ALB and PA levels in the DM group are higher than in the non-DM group. It is considered that the inadequate utilisation of glucose in patients with DM affects the body’s energy supply, which in turn affects the synthesis and metabolism of protein, leading to reduced levels of ALB and PA [24]. Secondly, DM may lead to liver function damage, resulting in decreased synthesis of ALB and PA [25]. The positive rate of AFS in the DM group is higher than in the non-DM group, which may be due to the fact that the high blood glucose level in DM patients is more suitable for the growth of MTB, which makes it easier for MTB to reproduce in the body, thus increasing the positive rate of AFS [26].

The resistance rate of the DM group and non-DM group to streptomycin, isoniazid and rifampicin is more than 50%, and the resistance rate of isoniazid is the highest, more than 70%. The order of drug resistance of the two groups to first-line anti-TB drugs is isoniazid, streptomycin, rifampicin and ethambutol, while the results of PAN YP et al. [27] in Northeast China showed that the order of drug resistance is rifampicin, isoniazid, streptomycin and ethambutol. The analysis reveals that the different drug resistance trends of MTB in different regions are due to different genetic backgrounds, clinical drug use and other factors [28]. Therefore, it is necessary to understand the drug-resistance spectrum of MTB in this area. Furthermore, the drug resistance spectra of patients in the DM and non-DM groups were compared and analysed. No significant difference in MR-TB, PDR-TB or MDR-TB was found between the two groups, similar to that of WU Q et al. [29], however, SONG WM et al. [30] came to a different conclusion, presumably due to the difference in study design and sample size. This study analysed the data of drug-resistant tuberculosis-designated hospitals in Wenzhou between 2018 and 2022, which had good consistency and provided a reference point for follow-up researchers.

The study found that from 2018 to 2022, MDR-TB showed a downward trend in patients with and without DM, but the downward trend was not statistically significant (P > 0.05). This means that although, according to the requirements of the National Health Commission, two-way screening for TB and DM has been carried out in this region, more patients can be diagnosed and treated in time, and the spread of DR-TB is reduced [31], but the effect is not satisfactory. In particular, it is worth noting that from 2020 to 2021, the drug resistance rate of MDR-TB decreased slowly, while from 2021 to 2022, it showed an upward trend. This outcome is correlated with the negative impact of the COVID-19 pandemic on TB prevention and control [32]. To put an end to TB, it still needs the continuous efforts of the majority of TB prevention and control personnel.

In non-DM patients living in rural areas, retreatment of TB, pulmonary cavity and UA ≥ 346 µmol/L are independent risk factors for MDR-TB. At the same time, emaciation and CRP ≥ 37.3 mg/L are protective factors for MDR-TB. Such outcomes are due to: a relative lack of medical resources in rural areas, relatively low awareness of TB prevention and treatment among rural residents, easy development into MDR-TB due to misdiagnosis and delayed treatment [33], retreatment in patients due to initial treatment failure or random interruption of treatment so that MTB can not be eradicated, then mutating into MDR-MTB [34]. The appearance of pulmonary cavities often means that patients have a weak clearance ability to MTB, which is prone to persistent infection and drug resistance to MTB [35]. The common side effect of anti-TB drugs is increased UA [36]. Patients with high UA levels may have intolerable side effects of interrupting treatment, thus increasing the risk of multi-drug resistance [37]. Emaciation and elevated CRP considerations can indicate the possibility of TB in clinicians, thus timely diagnosis and treatment, reducing the risk of MDR-TB. Among patients with DM, living in rural areas, retreatment of TB, pulmonary cavity, and HbA1c ≥ 9.8% are independent risk factors for the development of MDR-TB. HbA1c is an index to reflect the blood glucose control of patients with DM. The higher its value is, the less ideal the blood glucose control is [38]. Hyperglycemia weakens the immune system, weakens the body’s ability to clear MTB and increases the risk of multi-drug resistance. Previous studies have also confirmed that high HbA1c levels are significantly associated with the occurrence of MDR-TB [39, 40].

This study has the following limitations. First of all, because the patients in the study used BD’s liquid drug susceptibility testing, and BD did not have commercial reagents for second-line anti-TB drugs [41], the second-line drug susceptibility testing was not carried out routinely, and the study only analysed the resistance spectrum of first-line anti-TB drugs. Secondly, although the study collected all cases of DM complicated with DR-TB in designated hospitals of drug-resistant tuberculosis in Wenzhou from 2018 to 2022, the number of cases is still limited, and further research is needed to expand the number of cases in the future.

Conclusion

In DR-TB patients with or without DM, isoniazid is the most resistant drug. There is no significant difference in the drug resistance profile between patients with DM and patients without DM. Some progress has been made in the prevention and treatment of DR-TB with or without combined DM, but the effect is not very significant. To achieve the goal of ending TB, TB prevention and control personnel still need to make continuous efforts. In non-DM patients, living in rural areas, TB treatment type of retreatment, pulmonary cavity, and UA ≥ 346 µmol / L are independent risk factors for MDR-TB. Among DM patients, residing in rural areas, TB treatment type of retreatment, pulmonary cavity, and HbA1c ≥ 9.8% are independent risk factors for MDR-TB. For DR-TB patients with or without DM, taking targeted measures will be beneficial for controlling DR-TB.

Data availability

All data generated or analyzed during this study are available to the corresponding author upon reasonable request.

References

  1. Naidoo K, Perumal R. Advances in tuberculosis control during the past decade. Lancet Respir Med. 2023;11(4):311–13.

    Article  PubMed  PubMed Central  Google Scholar 

  2. WHO. Global tuberculosis report 2023. In Geneva. World Health Organization; 2023.

  3. Raviglione M, Sulis G. Tuberculosis 2015: Burden, challenges and Strategy for Control and Elimination. Infect Dis Rep. 2016;8(2):6570.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119.

    Article  PubMed  Google Scholar 

  5. Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9(th) edition. Diabetes Res Clin Pract. 2019;157:107843.

    Article  PubMed  Google Scholar 

  6. Chen X, He G, Wang S, Lin S, Chen J, Zhang W. Evaluation of whole-genome sequence method to Diagnose Resistance of 13 anti-tuberculosis drugs and characterize resistance genes in clinical Multi-drug Resistance Mycobacterium tuberculosis isolates from China. Front Microbiol. 2019;10:1741.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Yang N, Masingboon K, Samartkit N. Factors influencing diabetes self-management among adults with type 2 diabetes mellitus in China. Belitung Nurs J. 2022;8(5):389–95.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Pérez-Navarro LM, Fuentes-Domínguez FJ, Zenteno-Cuevas R. Type 2 diabetes mellitus and its influence in the development of multidrug resistance tuberculosis in patients from southeastern Mexico. J Diabetes Complications. 2015;29(1):77–82.

    Article  PubMed  Google Scholar 

  9. Mi F, Jiang G, Du J, Li L, Yue W, Harries AD, et al. Is resistance to anti-tuberculosis drugs associated with type 2 diabetes mellitus? A register review in Beijing, China. Glob Health Action. 2014;7:24022.

    Article  PubMed  Google Scholar 

  10. Li B, Liu D, Wan Q, Sheng C, Wang X, Leng F, et al. Differences in treatment for Alzheimer’s disease between urban and rural areas in China. Front Neurol. 2022;13:996093.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Canan A, Batra K, Saboo SS, Landay M, Kandathil A. Radiological approach to cavitary lung lesions. Postgrad Med J. 2021;97(1150):521–31.

    Article  PubMed  Google Scholar 

  12. Falzon D, Schünemann HJ, Harausz E, González-Angulo L, Lienhardt C, Jaramillo E et al. World Health Organization treatment guidelines for drug-resistant tuberculosis, 2016 update. Eur Respir J. 2017;49(3).

  13. Xie YL, Eichberg C, Hapeela N, Nakabugo E, Anyango I, Arora K, et al. Xpert MTB/RIF Ultra versus mycobacterial growth indicator tube liquid culture for detection of Mycobacterium tuberculosis in symptomatic adults: a diagnostic accuracy study. Lancet Microbe. 2024;5(6):e520–28.

    Article  PubMed  Google Scholar 

  14. Koh WJ, Ko Y, Kim CK, Park KS, Lee NY. Rapid diagnosis of tuberculosis and multidrug resistance using a MGIT 960 system. Ann Lab Med. 2012;32(4):264–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Rawshani A, Rawshani A, Franzén S, Sattar N, Eliasson B, Svensson AM, et al. Risk factors, mortality, and Cardiovascular outcomes in patients with type 2 diabetes. N Engl J Med. 2018;379(7):633–44.

    Article  PubMed  Google Scholar 

  16. Xue L, Wang H, He Y, Sui M, Li H, Mei L, et al. Incidence and risk factors of diabetes mellitus in the Chinese population: a dynamic cohort study. BMJ Open. 2022;12(11):e060730.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Kautzky-Willer A, Harreiter J, Pacini G. Sex and gender differences in risk, pathophysiology and complications of type 2 diabetes Mellitus. Endocr Rev. 2016;37(3):278–316.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Hamada Y, Quartagno M, Law I, Malik F, Bonsu FA, Adetifa IMO, et al. Association of diabetes, smoking, and alcohol use with subclinical-to-symptomatic spectrum of tuberculosis in 16 countries: an individual participant data meta-analysis of national tuberculosis prevalence surveys. EClinicalMedicine. 2023;63:102191.

    Article  PubMed  PubMed Central  Google Scholar 

  19. McQuaid CF, Horton KC, Dean AS, Knight GM, White RG. The risk of multidrug- or rifampicin-resistance in males versus females with tuberculosis. Eur Respir J. 2020;56(3).

  20. Gil-Santana L, Almeida-Junior JL, Oliveira CA, Hickson LS, Daltro C, Castro S, et al. Diabetes is Associated with worse clinical presentation in tuberculosis patients from Brazil: a retrospective cohort study. PLoS ONE. 2016;11(1):e0146876.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Wei R, Li P, Xue Y, Liu Y, Gong W, Zhao W. Impact of diabetes Mellitus on the immunity of tuberculosis patients: a Retrospective, cross-sectional study. Risk Manag Healthc Policy. 2022;15:611–27.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Liu H, Wang X, Gao H, Yang C, Xie C. Physiological and pathological characteristics of vascular endothelial injury in diabetes and the regulatory mechanism of autophagy. Front Endocrinol (Lausanne). 2023;14:1191426.

    Article  PubMed  Google Scholar 

  23. Luciani L, Pedrelli M, Parini P. Modification of lipoprotein metabolism and function driving atherogenesis in diabetes. Atherosclerosis. 2024;394:117545.

    Article  CAS  PubMed  Google Scholar 

  24. Jefferson LS, Liao WS, Peavy DE, Miller TB, Appel MC, Taylor JM. Diabetes-induced alterations in liver protein synthesis. Changes in the relative abundance of mRNAs for albumin and other plasma proteins. J Biol Chem. 1983;258(2):1369–75.

    Article  CAS  PubMed  Google Scholar 

  25. Mohamed J, Nazratun Nafizah AH, Zariyantey AH, Budin SB. Mechanisms of Diabetes-Induced Liver damage: the role of oxidative stress and inflammation. Sultan Qaboos Univ Med J. 2016;16(2):e132–41.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Terán G, Li H, Catrina SB, Liu R, Brighenti S, Zheng X, et al. High glucose and carbonyl stress impair HIF-1-Regulated responses and the control of Mycobacterium tuberculosis in macrophages. mBio. 2022;13(5):e0108622.

    Article  PubMed  Google Scholar 

  27. Pan Y, Yu Y, Yi Y, Dou X, Lu J, Zhou L. The differences in drug resistance between drug-resistant tuberculosis patients with and without diabetes mellitus in northeast China: a retrospective study. BMC Infect Dis. 2023;23(1):162.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Liang D, Song Z, Liang X, Qin H, Huang L, Ye J, et al. Whole genomic analysis revealed high genetic diversity and drug-resistant characteristics of Mycobacterium tuberculosis in Guangxi, China. Infect Drug Resist. 2023;16:5021–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Wu Q, Wang M, Zhang Y, Wang W, Ye TF, Liu K, et al. Epidemiological characteristics and their influencing factors among pulmonary tuberculosis patients with and without diabetes Mellitus: a Survey Study from Drug Resistance Surveillance in East China. Front Public Health. 2021;9:777000.

    Article  PubMed  Google Scholar 

  30. Song WM, Shao Y, Liu JY, Tao NN, Liu Y, Zhang QY, et al. Primary drug resistance among tuberculosis patients with diabetes mellitus: a retrospective study among 7223 cases in China. Infect Drug Resist. 2019;12:2397–407.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Cheng J, Zhang H, Zhao YL, Wang LX, Chen MT. Mutual impact of diabetes Mellitus and Tuberculosis in China. Biomed Environ Sci. 2017;30(5):384–89.

    CAS  PubMed  Google Scholar 

  32. Falzon D, Zignol M, Bastard M, Floyd K, Kasaeva T. The impact of the COVID-19 pandemic on the global tuberculosis epidemic. Front Immunol. 2023;14:1234785.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Hutchison C, Khan MS, Yoong J, Lin X, Coker RJ. Financial barriers and coping strategies: a qualitative study of accessing multidrug-resistant tuberculosis and tuberculosis care in Yunnan, China. BMC Public Health. 2017;17(1):221.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Liang L, Wu Q, Gao L, Hao Y, Liu C, Xie Y, et al. Factors contributing to the high prevalence of multidrug-resistant tuberculosis: a study from China. Thorax. 2012;67(7):632–8.

    Article  PubMed  Google Scholar 

  35. Wei SS, Gao Q, Cao YX, Han LY, Du J, Li L, et al. [A meta-analysis of risk factors for multidrug-resistant tuberculosis in China]. Zhonghua Jie He He Hu Xi Za Zhi. 2022;45(12):1221–30.

    CAS  PubMed  Google Scholar 

  36. Shin HJ, Yoon JY, Na YO, Lee JK, Kho BG, Kim TO, et al. Major adverse cardiovascular events and hyperuricemia during tuberculosis treatment. PLoS ONE. 2023;18(11):e0294490.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Thumamo Pokam BD, Enoh JE, Eyo AO, Umoh NO, Guemdjom PW. Uric acid levels in patients on antituberculosis drugs in the southwest region of Cameroon. Int J Mycobacteriol. 2018;7(1):89–91.

    Article  PubMed  Google Scholar 

  38. O’Keeffe DT, Maraka S, Rizza RA. HbA1c in the evaluation of diabetes Mellitus. JAMA. 2016;315(6):605–6.

    Article  PubMed  Google Scholar 

  39. Li S, Liang Y, Hu X. Risk factors for multidrug resistance in tuberculosis patients with diabetes mellitus. BMC Infect Dis. 2022;22(1):835.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Lyu M, Wang D, Zhao J, Yang Z, Chong W, Zhao Z, et al. A novel risk factor for predicting anti-tuberculosis drug resistance in patients with tuberculosis complicated with type 2 diabetes mellitus. Int J Infect Dis. 2020;97:69–77.

    Article  CAS  PubMed  Google Scholar 

  41. Duque A, Lin SY, Desmond E, Rienthong S, Rienthong D, Boonin C. Evaluation of the BD Bactec MGIT 320 system for detection of mycobacteria and drug susceptibility testing of Mycobacterium tuberculosis. J Clin Microbiol. 2013;51(10):3403–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This study was supported by Key Laboratory of Diagnosis and Treatment of New and Recurrent Infectious Diseases of Wenzhou (grant. No. 2021HZSY0067) and Wenzhou Central Hospital Ding Li Talent Project.

Author information

Authors and Affiliations

  1. Department of Clinical Laboratory Medicine, Wenzhou People’s Hospital, Wenzhou, 325000, China

    Xiaoxiao Cai

  2. Department of Clinical Laboratory Medicine, Wenzhou Central Hospital, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou, 325000, China

    Xueqin Xu & Lianpeng Wu

  3. Key Laboratory of Diagnosis and Treatment of New and Recurrent Infectious Diseases of Wenzhou, Wenzhou Central Hospital, The Dingli Clinical College of Wenzhou Medical University, No. 252 Baili east road, Lucheng district, Wenzhou, 325000, China

    Guiqing He, Xiangao Jiang & Lianpeng Wu

  4. Department of Infectious Diseases, The Ding Li Clinical College of Wenzhou Medical University, Wenzhou Central Hospital, Wenzhou, 325000, China

    Guiqing He & Xiangao Jiang

Authors
  1. Xiaoxiao Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xueqin Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guiqing He
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiangao Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lianpeng Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CXX and WLP contributed to design this study. CXX and WLP contributed to collect data. CXX and XXQ analyzed the results and wrote the manuscript. HGQ and JXG provided overall supervision and critically revised the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Xiangao Jiang or Lianpeng Wu.

Ethics declarations

Ethics approval and consent to participate

The study was approved by the Ethics Committee of Wenzhou Central Hospital (batch No. L2023-04-163).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

The data used in this study was anonymised before its use. Permission to use the data were obtained from the hospital administration. As this study used secondary data, informed consent was not obtained from patients.

The approval for waiver of informed consent was provided by the Ethics Committee of Wenzhou Central Hospital. This study was conducted in accordance with the Declaration of Helsinki.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cai, X., Xu, X., He, G. et al. Drug resistance in drug-resistant tuberculosis patients with and without diabetes mellitus: a comparative analysis. BMC Infect Dis 24, 807 (2024). https://doi.org/10.1186/s12879-024-09712-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12879-024-09712-3

Keywords

BMC Infectious Diseases

ISSN: 1471-2334

Contact us