Anemia Is a Strong Predictor of Wasting, Disease Severity, and Progression, in Clinical Tuberculosis (TB)

Incidence of anaemia and its predictors among HIV-infected children receiving highly active antiretroviral treatment in North-West Ethiopia: a multicentre retrospective follow-up study

BACKGROUND

Anaemia is one of the most common problems in HIV-infected patients associated with increased HIV progression, decreased functional capacity, survival and quality of life. For better interventions, up-to-date information concerning anaemia among HIV-infected children less than 5 years of age on antiretroviral therapy (ART) is vital. Thus, this study aims to determine the predictors of anaemia among HIV-infected children less than 5 years of age receiving ART in North-West Ethiopia.

DESIGN

An institution-based retrospective follow-up study was conducted.

STUDY SETTING

Amhara region Comprehensive Specialized Hospitals, North-West Ethiopia.

PARTICIPANTS

In total, we examined 460 HIV-infected children less than 5 years of age who had followed highly active antiretroviral treatment from 2010 to 2020.

OUTCOME MEASURES

The outcome measures were median time to detection of anaemia, the incidence and the effects of cotrimoxazole preventive therapy (CPT), ART adherence, tuberculosis (TB), WHO clinical stage and wasting on anaemia.

RESULTS

The overall follow-up time was 9234 person-months of observation. The incidence density of anaemia was 8.34 per 1000 person-months of observation (95% CI 6.67 to 10.43). The cumulative survival probability of children after the last months of follow-up was 0.54. The independent predictors of anaemia were not receiving CPT (adjusted HR (AHR)=4.44; 95% CI 2.48 to 7.93), poor adherence to ART (AHR=2.46; 95% CI 1.37 to 4.42), TB (AHR=3.40; 95% CI 1.72 to 6.72), severe WHO clinical stage (AHR=3.03; 95% CI 1.40 to 6.58) and severe wasting (AHR=1.98; 95% CI 1.08 to 3.64).

CONCLUSION AND RECOMMENDATION

The incidence rate of anaemia was high and it was provoked by predictors like CPT, ART adherence, TB, WHO clinical stage and wasting. Therefore, it is necessary to emphasise for these predictors.

Construction and Validation of a Nomogram to Identify the Risk of Cavitation in Pulmonary Tuberculosis

Background

The present study aimed to construct and validate a nomogram based on clinical metrics to identify CPTB.

Patients and Methods

The present study retrospectively recruited pulmonary tuberculosis (PTB) patients admitted to Jiashan County First People's Hospital in China from November 2018 to September 2023. PTB patients were classified into the CPTB group and the non-CPTB group based on chest computed tomography findings, and were randomly allocated to the training set (70%) and the validation cohort (30%). The training set and validation set were used to establish and validate nomogram, respectively. Multivariate logistic regression analysis (MLSA) was used to identify the independent risk factors for CPTB in patients with PTB. Statistically significant variables in the MLSA were then used to construct a nomogram predicting CPTB in patients with PTB. The receiver operating characteristic (ROC) curve, calibration curve analysis (CCA), and decision curve analysis (DCA) were used for the evaluation of the nomogram.

Results

A total of 293 PTB patients, including 208 in the training set (85 CPTB) and 85 in the validation set (33 CPTB\), were included in this study. Stepwise MLSA showed that sputum smear (≥2+), smoking(yes), glycosylated hemoglobin A1c(HbA1c), hemoglobin (HB), and systemic inflammatory response index (SIRI) were independent risk factors for the development of cavitation in patients with PTB. The nomogram identifying the high-risk CPTB patients was successfully established and showed a strong predictive capacity, with area under the curves (AUCs) of 0.875 (95% CI:0.806-0.909) and 0.848 (95% CI:0.751-0.946) in the training set and validation set respectively. In addition, the CCA and DCA corroborated the nomogram's high level of accuracy and clinical applicability within both the training and validation sets.

Conclusion

The constructed nomogram, consisting of sputum smear positivity, smoking, HbA1C, HB, and SIRI, serves as a practical and effective tool for early identification and personalized management of CPTB.

Correlation of tuberculosis-related anemia severity with tuberculosis-induced inflammation in children: a six-year retrospective study

BACKGROUND

Anemia is a common complication of tuberculosis (TB), and there is evidence that its prevalence is higher in patients with TB. Although TB is very important in epidemiology, careful investigation of TB-related anemia in children has not been carried out systematically. This study aimed to describe the details of anemia in children with TB and its association with clinical characteristics and the severity of inflammation.

METHODS

In this retrospective study, we explored Hb levels in 103 children with pulmonary TB (PTB) and they were divided into anemic or non-anemic groups. Logistics regression analysis was used to study the associations between anemia and demographic characteristics. Spearman correlations analysis was performed to analyse the associations between the biochemical parameters and hemoglobin levels in blood.

RESULTS

The prevalence of anemia in children with TB was 37.9% (48.7% showed microcytic hypochromic anemia, and 5.1% showed normal cell anemia). Compared with the anemia (n = 39) group, the non-anemic group (n = 64) had longer fever duration and increased respiratory rate (P < 0.05). In logistic regression analysis, anemia was associated with lower levels of Alb and higher levels of WBC, CRP, LDH, and ESR (P < 0.05). Spearman correlations analysis showed a significant negative correlation between hemoglobin (Hb) levels and inflammatory markers. After one month of antitubercular therapy (ATT), the Hb levels of 76.9% children returned to normal.

CONCLUSIONS

Anemia is common among children with TB at diagnosis. The majority of children with TB-related anemia are mild to moderate microcytic hypochromic anemia. There is a strong correlation between the severity of anemia and the inflammation induced by TB. This suggests that anemia is a biomarker of the severity of TB in clinical practice among children.

Comorbidity increases the risk of pulmonary tuberculosis: a nested case-control study using multi-source big data

BACKGROUND

Some medical conditions may increase the risk of developing pulmonary tuberculosis (PTB); however, no systematic study on PTB-associated comorbidities and comorbidity clusters has been undertaken.

METHODS

A nested case-control study was conducted from 2013 to 2017 using multi-source big data. We defined cases as patients with incident PTB, and we matched each case with four event-free controls using propensity score matching (PSM). Comorbidities diagnosed prior to PTB were defined with the International Classification of Diseases-10 (ICD-10). The longitudinal relationships between multimorbidity burden and PTB were analyzed using a generalized estimating equation. The associations between PTB and 30 comorbidities were examined using conditional logistic regression, and the comorbidity clusters were identified using network analysis.

RESULTS

A total of 4265 cases and 17,060 controls were enrolled during the study period. A total of 849 (19.91%) cases and 1141 (6.69%) controls were multimorbid before the index date. Having 1, 2, and ≥ 3 comorbidities was associated with an increased risk of PTB (aOR 2.85-5.16). Fourteen out of thirty comorbidities were significantly associated with PTB (aOR 1.28-7.27), and the associations differed by sex and age. Network analysis identified three major clusters, mainly in the respiratory, circulatory, and endocrine/metabolic systems, in PTB cases.

CONCLUSIONS

Certain comorbidities involving multiple systems may significantly increase the risk of PTB. Enhanced awareness and surveillance of comorbidity are warranted to ensure early prevention and timely control of PTB.

Inflammatory immune profiles associated with disease severity in pulmonary tuberculosis patients with moderate to severe clinical TB or anemia

Background

Immune control of Mycobacterium tuberculosis (Mtb) infection is largely influenced by the extensive disease heterogeneity that is typical for tuberculosis (TB). In this study, the peripheral inflammatory immune profile of different sub-groups of pulmonary TB patients was explored based on clinical disease severity, anemia of chronic disease, or the radiological extent of lung disease.

Methods

Plasma samples were obtained from n=107 patients with active pulmonary TB at the time of diagnosis and after start of standard chemotherapy. A composite clinical TB symptoms score, blood hemoglobin status and chest X-ray imaging were used to sub-group TB patients into 1.) mild and moderate-severe clinical TB, 2.) anemic and non-anemic TB, or 3.) limited and extensive lung involvement. Plasma levels of biomarkers associated with inflammation pathways were assessed using a Bio-Plex Magpix 37-multiplex assay. In parallel, Th1/Th2 cytokines were quantified with a 27-multiplex in matched plasma and cell culture supernatants from whole blood stimulated with M. tuberculosis-antigens using the QuantiFERON-TB Gold assay.

Results

Clinical TB disease severity correlated with low blood hemoglobin levels and anemia but not with radiological findings in this study cohort. Multiplex protein analyses revealed that distinct clusters of inflammation markers and cytokines separated the different TB disease sub-groups with variable efficacy. Several top-ranked markers overlapped, while other markers were unique with regards to their importance to differentiate the TB disease severity groups. A distinct immune response profile defined by elevated levels of BAFF, LIGHT, sTNF-R1 and 2, IP-10, osteopontin, chitinase-3-like protein 1, and IFNα2 and IL-8, were most effective in separating TB patients with different clinical disease severity and were also promising candidates for treatment monitoring. TB patients with mild disease displayed immune polarization towards mixed Th1/Th2 responses, while pro-inflammatory and B cell stimulating cytokines as well as immunomodulatory mediators predominated in moderate-severe TB disease and anemia of TB.

Conclusions

Our data demonstrated that clinical disease severity in TB is associated with anemia and distinct inflammatory immune profiles. These results contribute to the understanding of immunopathology in pulmonary TB and define top-ranked inflammatory mediators as biomarkers of disease severity and treatment prognosis.

A nomogram for predicting mortality of patients initially diagnosed with primary pulmonary tuberculosis in Hunan province, China: a retrospective study

Objective

According to the Global Tuberculosis Report for three consecutive years, tuberculosis (TB) is the second leading infectious killer. Primary pulmonary tuberculosis (PTB) leads to the highest mortality among TB diseases. Regretfully, no previous studies targeted the PTB of a specific type or in a specific course, so models established in previous studies cannot be accurately feasible for clinical treatments. This study aimed to construct a nomogram prognostic model to quickly recognize death-related risk factors in patients initially diagnosed with PTB to intervene and treat high-risk patients as early as possible in the clinic to reduce mortality.

Methods

We retrospectively analyzed the clinical data of 1,809 in-hospital patients initially diagnosed with primary PTB at Hunan Chest Hospital from January 1, 2019, to December 31, 2019. Binary logistic regression analysis was used to identify the risk factors. A nomogram prognostic model for mortality prediction was constructed using R software and was validated using a validation set.

Results

Univariate and multivariate logistic regression analyses revealed that drinking, hepatitis B virus (HBV), body mass index (BMI), age, albumin (ALB), and hemoglobin (Hb) were six independent predictors of death in in-hospital patients initially diagnosed with primary PTB. Based on these predictors, a nomogram prognostic model was established with high prediction accuracy, of which the area under the curve (AUC) was 0.881 (95% confidence interval [Cl]: 0.777-0.847), the sensitivity was 84.7%, and the specificity was 77.7%.Internal and external validations confirmed that the constructed model fit the real situation well.

Conclusion

The constructed nomogram prognostic model can recognize risk factors and accurately predict the mortality of patients initially diagnosed with primary PTB. This is expected to guide early clinical intervention and treatment for high-risk patients.