ABSTRACT
BACKGROUND: Latent tuberculosis infection (LTBI) is a mycobacterial infection defined on the basis of cellular immune response to mycobacterial antigens. The tuberculin skin test (TST) and the Interferon-Gamma Release Assay (IGRA) are the two tests currently used to establish the diagnosis of LTB. Literature suggests that a study regarding tuberculosis (TB) infection among women of reproductive age group is limited. METHODS: Female household contact, married, aged 18-49 years underwent written consent form and are screened for LTBI using the TST and IGRA. Participants are injected with TST [5 tuberculin unit (TU), purified protein derivative (PPD)] and IGRA [QuantiFERON®-TB Gold Plus kit (QFT-Plus)]. All the household contacts were followed-up for one year for incident TB cases. Statistical analysis was done using STATA version 14 (StataCorp., Texas, USA). Cohen's kappa test was used to determine the agreement between two tests. RESULTS: The prevalence of LTBI was found to be 69% (either TST or IGRA positive). Positivity rate of IGRA was higher when compared to that of TST. Out of 139 participants, 68 (49%) tested positive for TST, 80 (57.6%) tested positive for IGRA and 52 (37.4%) tested positive for both. Discordant results were observed in about two fifth of the study population and there was poor agreement between the two tests. CONCLUSION: Longitudinal studies are required to detect incident TB cases to evaluate the usefulness of these tests. The study was found that IGRA is more consistent to diagnosis of latent tuberculosis infection than the TST. Such studies can also be performed in varied settings among different populations which would help us to improve the diagnosis of LTBI and consequently help in TB control.
Subject(s)
Latent Tuberculosis , Tuberculosis , Humans , Female , Interferon-gamma Release Tests/methods , Latent Tuberculosis/diagnosis , Latent Tuberculosis/epidemiology , Tuberculin Test/methods , India/epidemiologyABSTRACT
BACKGROUND: Tuberculosis (TB) is well-known for causing wasting. Patients on treatment gain weight and weight loss is associated with unfavorable treatment outcomes. There is limited description of weight loss and its predictors during intensive treatment phase. The objective of this study was to assess the predictors of weight loss during intensive phase and to see if there is any association exists with sputum conversion at the end of intensive phase of treatment. METHODS: Data collected as a part of the prospective TB cohort (Regional Prospective Observational Research for TB India Phase 1) conducted in Pondicherry, Cuddalore and Viluppuram districts of Tamil Nadu were used for this study. Sputum smear and body weight comparison were made in the baseline and at the end of second month of treatment. RESULTS: In all, 726 participants had weight measurements at the two time points and 18.7% had weight loss; mean weight lost being 2.3 kg (SD 3.05). Mean weight loss was more among males (2.4 kg, SD 3.2), diabetics (2.8 kg, SD 3.9) and alcoholics (2.1 kg, SD 2.4). Alcohol consumption was the only predictor of weight loss after adjusting for age, diabetes, marital status and BMI (aRR 1.52, P 0.02). Weight loss was not associated with sputum conversion at the end of second month. CONCLUSIONS: Alcohol use emerged as the major predictor for weight loss during intensive phase.
Subject(s)
Diabetes Mellitus , Tuberculosis, Pulmonary , Tuberculosis , Male , Humans , Antitubercular Agents/therapeutic use , Prospective Studies , India/epidemiology , Tuberculosis, Pulmonary/drug therapy , Tuberculosis, Pulmonary/epidemiology , Tuberculosis/drug therapy , Treatment Outcome , Weight LossABSTRACT
BACKGROUND: Development of a prediction model using baseline characteristics of tuberculosis (TB) patients at the time of diagnosis will aid us in early identification of the high-risk groups and devise pertinent strategies accordingly. Hence, we did this study to develop a prognostic-scoring model for predicting the death among newly diagnosed drug sensitive pulmonary TB patients in South India. METHODS: We undertook a longitudinal analysis of cohort data under the Regional Prospective Observational Research for Tuberculosis India consortium. Multivariable cox regression using the stepwise backward elimination procedure was used to select variables for the model building and the nomogram-scoring system was developed with the final selected model. RESULTS: In total, 54 (4.6%) out of the 1181 patients had died during the 1-year follow-up period. The TB mortality rate was 0.20 per 1000 person-days. Eight variables (age, gender, functional limitation, anemia, leukopenia, thrombocytopenia, diabetes, neutrophil-lymphocyte ratio) were selected and a nomogram was built using these variables. The discriminatory power was 0.81 (95% confidence interval: 0.75-0.86) and this model was well-calibrated. Decision curve analysis showed that the model is beneficial at a threshold probability ~15-65%. CONCLUSIONS: This scoring system could help the clinicians and policy makers to devise targeted interventions and in turn reduce the TB mortality in India.
Subject(s)
Tuberculosis, Pulmonary , Tuberculosis , Humans , Prognosis , Nomograms , Probability , India/epidemiology , Retrospective StudiesABSTRACT
BACKGROUND: Timika scoring system is a radiographic grading tool, widely employed for grading the severity of tuberculosis (TB). We evaluated the predictive accuracy of this tool for adverse treatment outcomes among TB patients in Indian setting. METHODS: We undertook a longitudinal analysis of cohort data under the RePORT-India consortium. Cohort having participants with active pulmonary TB were included. CXRs were independently scored by chest physicians. Timika scoring system had a total score of 140. The predictive nature of the tool was assessed using the ROC analysis. RESULTS: Around 364 laboratory confirmed TB patients were enrolled. The mean (SD) of overall Timika score was 62.3 (24.9). Sputum conversion was achieved among 218/260 (83.8%) patients available at end of intensive phase. AUC for Timika score was 0.53 (95% CI: 0.43-0.63) and for percent lung affected, was 0.56 (95% CI: 0.46-0.65). Unfavorable treatment outcome was observed among 67/287 (23.3%) at the end of continuation phase. AUC for percent lung affected was 0.62 (95% CI: 0.54-0.70) and for Timika score was 0.59 (95% CI: 0.51-0.67). CONCLUSION: Both Timika scoring system and percent lung affected had poor predictive accuracy, highlighting the inability of a single CXR scoring system to predict the treatment outcome in Indian setting.
Subject(s)
Tuberculosis , Humans , X-Rays , Radiography , Treatment Outcome , India/epidemiologyABSTRACT
[This corrects the article DOI: 10.3389/fimmu.2022.1011166.].
ABSTRACT
Background: Most individuals exposed to Mycobacterium tuberculosis (Mtb) develop latent tuberculosis infection (LTBI) and remain at risk for progressing to active tuberculosis disease (TB). Malnutrition is an important risk factor driving progression from LTBI to TB. However, the performance of blood-based TB risk signatures in malnourished individuals with LTBI remains unexplored. The aim of this study was to determine if malnourished and control individuals had differences in gene expression, immune pathways and TB risk signatures. Methods: We utilized data from 50 tuberculin skin test positive household contacts of persons with TB - 18 malnourished participants (body mass index [BMI] < 18.5 kg/m2) and 32 controls (individuals with BMI ≥ 18.5 kg/m2). Whole blood RNA-sequencing was conducted to identify differentially expressed genes (DEGs). Ingenuity Pathway Analysis was applied to the DEGs to identify top canonical pathways and gene regulators. Gene enrichment methods were then employed to score the performance of published gene signatures associated with progression from LTBI to TB. Results: Malnourished individuals had increased activation of inflammatory pathways, including pathways involved in neutrophil activation, T-cell activation and proinflammatory IL-1 and IL-6 cytokine signaling. Consistent with known association of inflammatory pathway activation with progression to TB disease, we found significantly increased expression of the RISK4 (area under the curve [AUC] = 0.734) and PREDICT29 (AUC = 0.736) progression signatures in malnourished individuals. Conclusion: Malnourished individuals display a peripheral immune response profile reflective of increased inflammation and a concomitant increased expression of risk signatures predicting progression to TB. With validation in prospective clinical cohorts, TB risk biomarkers have the potential to identify malnourished LTBI for targeted therapy.
Subject(s)
Latent Tuberculosis , Malnutrition , Tuberculosis, Pulmonary , Tuberculosis , Biomarkers , Cytokines , Humans , Inflammation , Interleukin-1 , Interleukin-6 , Latent Tuberculosis/genetics , Malnutrition/complications , Prospective Studies , RNA , Tuberculosis/genetics , Tuberculosis, Pulmonary/geneticsABSTRACT
BACKGROUND: Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers. METHODS: The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker. RESULTS: Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB. CONCLUSIONS: The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.
Subject(s)
Latent Tuberculosis , Mycobacterium tuberculosis , Tuberculosis , Biomarkers , Humans , Latent Tuberculosis/diagnosis , Mycobacterium tuberculosis/genetics , RNA, Messenger/genetics , Tuberculosis/diagnosis , Tuberculosis/geneticsABSTRACT
India has made substantial advancements in reducing the burden of tuberculosis (TB), but persons living with active TB (PLWATB) still face myriad challenges in seeking and receiving care, including TB-related stigma. To meet the END TB targets, it is critical that PLWATB engage in care and are able to adhere to treatment. This qualitative study aimed to understand TB-related stigma (perceived, enacted, and internalised) and possible interventions to reduce stigma in Puducherry and Tamil Nadu, India. We conducted 47 in-depth interviews with PLWATB and household members and eight focus group discussions: two each with PLWATB, their household members, healthcare workers, and key informants. We found varying TB-related knowledge: the vast majority of interview participants reported incorrect modes of transmission, although most were also aware that TB is curable. Participants reported high levels of perceived stigma, with nearly two-thirds of PLWATB choosing to hide their disease to avoid being stigmatised in their community. Participants supported interventions including celebrity advocacy and school-based programming to increase community knowledge and reduce enacted stigma as well as support groups and counselling to reduce internalised stigma in PLWATB. This study has the potential to inform future interventions to reduce TB-related stigma in India.
Subject(s)
Social Stigma , Tuberculosis , Humans , India , Tuberculosis/therapy , Qualitative Research , Focus GroupsABSTRACT
OBJECTIVE: To determine the prevalence and determinants of diabetes mellitus (DM) among tuberculosis (TB) patients and to assess the additional yield and number needed to screen (NNS) to obtain a newly diagnosed DM among TB patients. DESIGN: We undertook a cross-sectional analysis of the cohort data under Regional Prospective Observational Research for Tuberculosis-India consortium. Newly diagnosed TB patients recruited into the cohort between 2014 and 2018 were included. Pretested standardised questionnaires and tools were used for data collection. Prevalence of DM among TB patients was summarised as proportion with 95% CI. Type II DM was diagnosed if random blood sugar level was >200 mg/dL or if the participant had a documented history of DM. NNS by blood glucose testing to diagnose one new DM case among TB patients was also calculated. SETTING: Three districts of South India: Puducherry, Cuddalore and Villupuram SUBJECTS: Newly diagnosed sputum smear positive pulmonary TB patients aged ≥16 years RESULTS: In total, 1188 TB patients were included. Prevalence of DM among TB patients was 39% (95% CI: 36.2% to 41.8%). In unadjusted analysis, elderly TB, marital status, caste, gender, higher education level, household income and obesity had a significant association with DM. However, in adjusted analysis, only marital status (currently married aPR; 3.77 (95 CI: 2.20 to 6.49), widowed/separated/divorced aPR; 3.66 (95 CI: 1.96 to 6.83)) and body mass index category (normal weight aPR; 3.26 (95 CI: 2.55 to 4.16), overweight aPR; 3.86 (95 CI: 2.69 to 5.52), obesity aPR; 4.08 (95 CI: 2.81 to 5.94)) were found to be significant determinants. The number of TB patients needed to be screened to find a new DM case was 12. CONCLUSION: We found that one in three TB patients had coexisting DM. The number of TB patients needed to be screened to obtain a newly diagnosed DM patients was also determined. The study supports and highlights the need of RNTCP's effort in bidirectional screening of TB and DM.
Subject(s)
Diabetes Mellitus , Tuberculosis, Pulmonary , Tuberculosis , Aged , Cross-Sectional Studies , Diabetes Mellitus/epidemiology , Humans , India/epidemiology , Prevalence , Tuberculosis/epidemiologyABSTRACT
OBJECTIVE: We aimed to determine the prevalence and find the risk factors associated with latent tuberculosis infection (LTBI) among the household contacts (HHC) of pulmonary TB patients. METHODS: This cohort study was conducted from 2014 to 2019. Pretested standardised questionnaires and tools were used for data collection. The prevalence of LTBI among HHCs of TB patients was summarised as proportion with 95% confidence interval (CI). Mixed-effects generalised linear modelling function (meglm) in STATA with family Poisson and log link was performed to find the factors associated with LTBI. RESULTS: In total, 1523 HHC of pulmonary TB patients were included in the study. Almost all HHC shared their residence with the index case (IC) for more than a year; 25% shared the same bed with the IC. The prevalence of LTBI among the HHC of TB patients was 52.6% (95% CI: 50.1-55.1%). In an adjusted model, we found that among HHC belonging to the age group of 19-64 years (aIRR = 1.2; 95% CI: 1.1-1.3; p-value: 0.02), to the age group >65 years (aIRR = 1.4, 95% CI: 1.1-1.9, p-value: 0.02) and sharing the same bed with the IC (aIRR = 1.2, 95% CI: 1.1-1.3, p value: 0.04) were independent determinants of LTBI among the HHC. CONCLUSION: One in two household contacts of TB patients have latent tuberculosis infection. This underscores the need of targeted contact screening strategies, effective contact tracing and testing using standardised methods in high TB burden settings.
Subject(s)
Latent Tuberculosis/diagnosis , Latent Tuberculosis/epidemiology , Tuberculosis, Pulmonary/diagnosis , Tuberculosis, Pulmonary/epidemiology , Adolescent , Adult , Aged , Cohort Studies , Contact Tracing , Family Characteristics , Female , Humans , India/epidemiology , Male , Middle Aged , Prevalence , Risk Factors , Young AdultABSTRACT
The rising geriatric population and the increased susceptibility of this age group to tuberculosis (TB), the deadliest single infectious agent, is bothersome for India. This study tried to explore the demographic and treatment outcome differences between the elderly (aged 60 years and above) and non-elderly TB (<60 years) patients from South India. This study was part of a large ongoing cohort study under the RePORT India consortium. Newly diagnosed TB patients recruited into the cohort between 2014 and 2018 were included in this study. Pretested and standardized questionnaire and tools were used to collect data and were stored securely for the entire cohort. Required demographic, anthropometric and treatment related variables were extracted from this database and analyzed using Stata version 14.0. Prevalence of elderly TB was summarized as percentage with 95% confidence interval (CI). Generalized linear modelling was attempted to find the factors associated with elderly TB. A total of 1,259 eligible TB patients were included into this present study. Mean (SD) of the participants in the elderly and non-elderly group was 65.8 (6.2) and 40.2 (12.0) respectively. Prevalence of elderly TB was 15.6% (95%CI: 13.6%-17.6%) with nearly 71% belonging to 60-69 age category. Male sex, OBC caste, poor education, unemployment, marriage, alcohol consumption and unable to work as per Karnofsky score were found to be significantly associated with an increased prevalence of elderly TB. Unfavorable outcomes (12% vs 6.5%, p value: 0.018), including death (9.3% vs 3.4%, p value: 0.001) were significantly higher among the elderly group when compared to their non-elderly counterparts. The current TB programme should have strategies to maintain follow up with due attention to adverse effects, social support and outcomes. Additional research should focus on predictors for unfavorable outcomes among the elderly TB group and explore ways to handle the same. Rendering adequate social support from the health system side and family side would be a good start.
Subject(s)
Antitubercular Agents/therapeutic use , Tuberculosis/drug therapy , Tuberculosis/epidemiology , Adult , Aged , Aged, 80 and over , Alcohol Drinking/adverse effects , Alcohol Drinking/epidemiology , Female , Humans , India/epidemiology , Male , Middle Aged , Risk Factors , Treatment Outcome , Tuberculosis/microbiologyABSTRACT
BACKGROUND: Undernutrition impairs immunity to Mycobacterium tuberculosis and is a risk factor for tuberculosis disease (TB). We aim to investigate if severe undernutrition affects the tuberculin skin test (TST) response among household contacts (HHCs) of pulmonary TB cases. METHODS: We analyzed data from HHCs (> five years) of pulmonary TB cases in Southern India. Undernutrition was defined as per World Health Organization based on body mass index (BMI) for adults (undernutrition 16-18.4 and severe undernutrition <16 kg/m2) and BMI relative to the mean for children (undernutrition 2SD-3SD and severe undernutrition < 3SDs below mean). Univariate and multivariate models of TST positivity (> five mm) were calculated using logistic regression with generalized estimating equations. RESULTS: Among 1189 HHCs, 342 were children (age 5-17 years) and 847 were adults. Prevalence of TST positivity in well-nourished, undernourished and severely undernourished children was 135/251 (53.8%), 32/68 (47.1%), and 7/23 (30.4%) respectively; among adults, prevalence of TST positivity was 304/708 (42.9%), 43/112 (38.4%) and 12/26 (46.2%), respectively. Severe undernutrition in children was associated with decreased odds of TST positivity (adjusted odds ratio 0.3; 95%CI 0.1-0.9). CONCLUSION: Severe undernutrition in children was associated with decreased odds of TST positivity. False-negative TSTs may result from undernutrition; caution is warranted when interpreting negative results in undernourished populations.
Subject(s)
Malnutrition , Tuberculin Test , Adolescent , Adult , Child , Child, Preschool , Humans , India , Infant , Prevalence , Risk FactorsABSTRACT
OBJECTIVE: Identifying the risk factors for deaths during tuberculosis (TB) treatment is important for achieving the vision of India's National Strategic Plan of 'Zero Deaths' by 2025. We aimed to determine the proportion of deaths during TB treatment and its risk factors among smear positive pulmonary TB patients aged more than 15 years. STUDY DESIGN: We performed a cohort study using data collected for RePORT India Consortium (Regional Prospective Observational Research in Tuberculosis). SETTING: Revised TB Control Program (RNTCP) in three districts of South India. PARTICIPANTS: The cohort consisted of newly diagnosed drug sensitive patients enrolled under the Revised National TB Control Program during 2014-2018 in three districts of southern India. Information on death was collected at homes by trained project staff. PRIMARY OUTCOME MEASURES: We calculated 'all-cause mortality' during TB treatment and expressed this as a proportion with 95% confidence interval (CI). Risk factors for death were assessed by calculating unadjusted and adjusted relative risks with 95% CI. RESULTS: The mean (SD) age was of the 1167 participants was 45 (14.5) years and 79% of them were males. Five participants (0.4%) were HIV infected. Among the males, 560 (61%) were tobacco users and 688 (75%) reported consuming alcohol. There were 47 deaths (4%; 95% CI 3.0-5.3) of which 28 deaths (60%) occurred during first two months of treatment. In a bi-variable analysis, age of more than 60 years (RR 2.27; 95%CI: 1.24-4.15), male gender (RR 3.98; 95% CI: 1.25-12.70), alcohol use in last 12 months (RR 2.03; 95%CI: 1.07-3.87), tobacco use (RR 1.87; 95%CI: 1.05-3.36) and severe anaemia (RR 3.53: 95%CI: 1.34-9.30) were associated with a higher risk of death. In adjusted analysis, participants with severe anaemia (<7gm/dl) had 2.4 times higher risk of death compared to their counterparts. CONCLUSION: Though deaths during TB treatment was not very high, early recognition of risk groups and targeted interventions are required to achieve zero TB deaths.
Subject(s)
Antitubercular Agents/therapeutic use , Tuberculosis, Pulmonary/drug therapy , Age Factors , Antitubercular Agents/administration & dosage , Cohort Studies , Databases, Factual , Female , Humans , India , Male , Middle Aged , Mortality/trends , Risk Factors , Sex Factors , Tuberculosis, Pulmonary/mortalityABSTRACT
BACKGROUND: Gene expression signatures have been used as biomarkers of tuberculosis (TB) risk and outcomes. Platforms are needed to simplify access to these signatures and determine their validity in the setting of comorbidities. We developed a computational profiling platform of TB signature gene sets and characterized the diagnostic ability of existing signature gene sets to differentiate active TB from LTBI in the setting of malnutrition. METHODS: We curated 45 existing TB-related signature gene sets and developed our TBSignatureProfiler software toolkit that estimates gene set activity using multiple enrichment methods and allows visualization of single- and multi-pathway results. The TBSignatureProfiler software is available through Bioconductor and on GitHub. For evaluation in malnutrition, we used whole blood gene expression profiling from 23 severely malnourished Indian individuals with TB and 15 severely malnourished household contacts with latent TB infection (LTBI). Severe malnutrition was defined as body mass index (BMI) < 16 kg/m2 in adults and based on weight-for-height Z scores in children < 18 years. Gene expression was measured using RNA-sequencing. RESULTS: The comparison and visualization functions from the TBSignatureProfiler showed that TB gene sets performed well in malnourished individuals; 40 gene sets had statistically significant discriminative power for differentiating TB from LTBI, with area under the curve ranging from 0.662-0.989. Three gene sets were not significantly predictive. CONCLUSION: Our TBSignatureProfiler is a highly effective and user-friendly platform for applying and comparing published TB signature gene sets. Using this platform, we found that existing gene sets for TB function effectively in the setting of malnutrition, although differences in gene set applicability exist. RNA-sequencing gene sets should consider comorbidities and potential effects on diagnostic performance.
Subject(s)
Gene Expression Profiling/methods , Malnutrition/genetics , Software , Tuberculosis/genetics , Adolescent , Adult , Aged , Area Under Curve , Biomarkers/blood , Child , Comorbidity , Female , Humans , Latent Tuberculosis/diagnosis , Latent Tuberculosis/epidemiology , Latent Tuberculosis/genetics , Male , Malnutrition/diagnosis , Malnutrition/epidemiology , Middle Aged , Mycobacterium tuberculosis , Transcriptome , Tuberculosis/diagnosis , Tuberculosis/epidemiology , Young AdultABSTRACT
SETTING: Alcohol use increases the risk of tuberculosis (TB) disease and is associated with worse outcomes. OBJECTIVE: To determine whether alcohol use affects TB severity at diagnosis in a high-burden setting. DESIGN: Participants were smear-positive people living with TB (PLWTB) in India. Disease severity was assessed as 1) high versus low smear grade, 2) time to positivity (TTP) on liquid culture, 3) chest radiograph cavitation, and 4) percent lung affected. Alcohol use and being at-risk for alcohol use disorders (AUD) were assessed using the AUDIT-C. Univariable and multivariable analyses were conducted. RESULTS: Of 1166 PLWTB, 691 (59.3%) were drinkers; of those, 518/691 (75.0%) were at-risk for AUD. Drinkers had more lung affected than non-drinkers (adjusted mean difference 10.8%, p<0.0001); this was not significant for those at-risk for AUD (adjusted mean difference 3.7%, p = 0.11). High smear grade (aOR 1.0, 95%CI: 0.7-1.4), cavitation (aOR 0.8, 95%CI 0.4-1.8), and TTP (mean difference 5.2 hours, p = 0.51) did not differ between drinkers and non-drinkers, nor between those at-risk and not at-risk for AUD. CONCLUSIONS: A large proportion of PLWTB were drinkers and were at-risk for AUD. Alcohol drinkers had more lung affected than non-drinkers. Studies are needed to explore mechanisms of this association.
Subject(s)
Alcohol Drinking/epidemiology , Alcoholism/epidemiology , Tuberculosis, Pulmonary/epidemiology , Adolescent , Adult , Alcohol Drinking/adverse effects , Alcoholism/complications , Female , Humans , India , Lung/diagnostic imaging , Male , Middle Aged , Mycobacterium tuberculosis/isolation & purification , Prospective Studies , Radiography , Risk Factors , Severity of Illness Index , Tuberculosis, Pulmonary/diagnosis , Tuberculosis, Pulmonary/microbiology , Young AdultABSTRACT
OBJECTIVES: Patients with Covid-19 and obesity have worse clinical outcomes which may be driven by increased inflammation. This study aimed to characterize the association between clinical outcomes in patients with obesity and inflammatory markers. METHODS: We analyzed data for patients aged ≥18 years admitted with a positive SARS-CoV-2 PCR test. We used multivariate logistic regression to determine the association between BMI and intensive care unit (ICU) transfer and all-cause mortality. Inflammatory markers (C-reactive protein [CRP], lactate dehydrogenase [LDH], ferritin, and D-dimer) were compared between patients with and without obesity (body mass index [BMI] ≥30 kg/m2). RESULTS: Of 791 patients with Covid-19, 361 (45.6%) had obesity. In multivariate analyses, BMI ≥35 was associated with a higher odds of ICU transfer (adjusted odds ratio [aOR] 2.388 (95% confidence interval [CI]: 1.074-5.310) and hospital mortality (aOR = 4.3, 95% CI: 1.69-10.82). Compared to those with BMI<30, patients with obesity had lower ferritin (444 vs 637 ng/mL; p<0.001) and lower D-dimer (293 vs 350 mcg/mL; p = 0.009), non-significant differences in CRP (72.8 vs 84.1 mg/L, p = 0.099), and higher LDH (375 vs 340, p = 0.009) on the first hospital day. CONCLUSIONS: Patients with obesity were more likely to have poor outcomes even without increased inflammation.
Subject(s)
Biomarkers/metabolism , COVID-19/pathology , Obesity/complications , Safety-net Providers , Adult , Aged , Biomarkers/analysis , Body Mass Index , COVID-19/complications , COVID-19/mortality , COVID-19/virology , Female , Hospital Mortality , Humans , Intensive Care Units , Logistic Models , Male , Middle Aged , Odds Ratio , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Treatment OutcomeABSTRACT
Identifying predictors of loss to follow-up (LTFU; treatment lapse ≥ 2 months) among people with tuberculosis (TB) may assist programmatic efforts in controlling the spread of TB. Newly diagnosed smear-positive TB patients were enrolled in the Regional Prospective Observational Research for TB study in Puducherry and Tamil Nadu, India. Treatment records were used to identify LTFU of those who were enrolled from May 2014 through December 2017. This nested case-control study evaluated male TB patients. Predictors were assessed using multivariable logistic regression. Of 425 men with TB, 82 (19%) were LTFU. In the adjusted analyses of males, divorced/separated marital status (adjusted odds ratio [aOR] 3.80; 95% CI: 1.39-10.38) and at-risk alcohol use (aOR 1.92; 95% CI: 1.12-3.27) were significant predictors for increased risk of LTFU, and diabetes was a significant predictor for decreased risk of LTFU (aOR 0.52; 95% CI: 0.29-0.92). Of 53 men with recorded date of last treatment visit, 23 (43%) and 43 (81%) had LTFU within the first 2 and first 4 months of treatment, respectively. Addressing at-risk alcohol use and providing more intensive follow-up could lead to improved treatment completion.
Subject(s)
Lost to Follow-Up , Mycobacterium tuberculosis/pathogenicity , Tuberculosis, Pulmonary/microbiology , Adult , Alcohol Drinking/physiopathology , Antitubercular Agents/therapeutic use , Case-Control Studies , Female , Follow-Up Studies , Humans , India , Logistic Models , Male , Marital Status , Middle Aged , Mycobacterium tuberculosis/isolation & purification , Risk Factors , Tuberculosis, Pulmonary/drug therapy , Tuberculosis, Pulmonary/pathologyABSTRACT
OBJECTIVES: Food insecurity is 'the limited or uncertain availability of nutritionally adequate, safe foods or inability to acquire foods in socially acceptable ways'. Majority of tuberculosis (TB) cases of resource-poor settings experience food insecurity, which impacts treatment adherence and outcomes. We aimed to determine level of household food insecurity (HFI) and its associated factors in patients with pulmonary TB. DESIGN: This is a cross-sectional analysis of data from an ongoing cohort study. SETTING: National Tuberculosis Programme (NTP) in three districts of South India. PARTICIPANTS: All newly diagnosed pulmonary TB cases of the cohort enrolled in the NTP at the Designated Microscopy Centres (DMCs) and Primary Health Centres (PHCs) from October 2015 to October 2018. PRIMARY OUTCOME MEASURES: The proportion of baseline HFI assessed using a validated HFI Access Scale was summarised as percentage with 95% CI. Possible association of sociodemographic, morbidity and behavioural characteristics with HFI was assessed using χ2 test, and unadjusted prevalence ratios with 95% CI were calculated. The characteristics with values of p<0.2 in the univariate model were included in the multivariable generalised linear model (binomial function, log link) to derive adjusted prevalence ratios (aPRs) with 95% CI. RESULT: Of a total of 765 patients, 261 had HFI and the proportion was 34.1% (95% CI 30.8% to 37.6%). Mild, moderate and severe food insecurity was found in 17 (2.2%), 67 (8.8%) and 177 (23.1%) TB cases, respectively. Patients with TB who had monthly family income less than rupees 3000 (aPR 2.0; 95% CI 1.3 to 3.0), Karnofsky Score of 60 or less (aPR 1.5; 95% CI 1.1 to 1.9) and those who were employed (aPR 1.4; 95% CI 1.0 to 2.0) were independently associated with HFI. CONCLUSIONS: A high level of food insecurity was seen in households with TB cases. Additional food or cash assistance for this subgroup might improve food insecurity and thereby nutritional status.
Subject(s)
Food Insecurity , Tuberculosis, Pulmonary , Adolescent , Adult , Cohort Studies , Cross-Sectional Studies , Female , Humans , India/epidemiology , Male , Middle Aged , Tuberculosis, Pulmonary/epidemiology , Young AdultABSTRACT
BACKGROUND: Malnutrition and diabetes are risk factors for active tuberculosis (TB), possible risk factors for latent TB infection (LTBI), and may interact to alter their effect on these outcomes. Studies to date have not investigated this interaction. METHODS: We enrolled 919 newly diagnosed active TB patients and 1113 household contacts at Primary Health Centres in Puducherry and Tamil Nadu, India from 2014 to 2018. In cross-sectional analyses, we used generalized estimating equations to measure additive and multiplicative interaction of body mass index (BMI) and diabetes on two outcomes, active TB and LTBI. RESULTS: Among overweight or obese adults, active TB prevalence was 12-times higher in diabetic compared to non-diabetic participants, 2.5-times higher among normal weight adults, and no different among underweight adults (P for interaction < 0.0001). Diabetes was associated with 50 additional active TB cases per 100 overweight or obese participants, 56 per 100 normal weight participants, and 17 per 100 underweight participants (P for interaction < 0.0001). Across BMI categories, screening 2.3-3.8 active TB patients yielded one hyperglycemic patient. LTBI prevalence did not differ by diabetes and BMI*diabetes interaction was not significant. CONCLUSIONS: BMI and diabetes are associated with newly diagnosed active TB, but not LTBI. Diabetes conferred the greatest risk of active TB in overweight and obese adults whereas the burden of active TB associated with diabetes was similar for normal and overweight or obese adults. Hyperglycemia was common among all active TB patients. These findings highlight the importance of bi-directional diabetes-active TB screening in India.