Malnutrition assessment methods in adult patients with tuberculosis: a systematic review

Cachexia in tuberculosis in South-East Asian and African regions: knowledge gaps and untapped opportunities

Tuberculosis (TB) and cachexia are clinical entities that have a defined relationship, making them often found together. TB can lead to cachexia, while cachexia is a risk factor for TB. This article reviews cachexia in Tuberculosis patients in Southeast Asian and African regions by conducting a comprehensive literature search across electronic databases such as PubMed, Google Scholar, and Research Gate between 2013 and 2024 using keywords including 'Africa', 'cachexia', 'prevalence', 'implications', 'tuberculosis', and 'Southeast Asia. This article utilized only studies that satisfied the inclusion criteria, revealing knowledge gaps and untapped opportunities for cachexia in TB across Southeast Asian and African regions. Many Southeast Asian and Western Pacific patients initially receive a tuberculosis diagnosis. Sub-Saharan African countries are among the 30 high TB burden nations, according to the WHO. Food inadequacy and heightened energy expenditure can impair the immune system, leading to latent TB and subsequently, active infection. Symptoms needing attention: shortness of breath, productive cough, hyponatremia at 131 mmol/l, hypoalbuminemia at 2.1 g/dl, elevated aspartate transaminase at 75 U/l, increased lactate dehydrogenase at 654, and normocytic anemia. Comorbidities, such as kidney disease, cardiovascular disease, and asthma, can influence the nutritional status of individuals with TB. While efforts like screening, contact tracing, and utilizing gene Xpert to detect TB cases were implemented, only a few proved effective. It is essential to conduct further studies, including RCTs, in Southeast Asia and Africa to evaluate and manage cachexia in TB patients.

A time-to-event modelling of sputum conversion within two months after antituberculosis initiation among drug-susceptible smear positive pulmonary tuberculosis patients: Implementation of internal and external validation

Delayed sputum conversion has been associated with a higher risk of treatment failure or relapse among drug susceptible smear-positive pulmonary tuberculosis patients. Several contributing factors have been identified in many studies, but the results varied across regions and countries. Therefore, the current study aimed to develop a predictive model that explained the factors affecting time to sputum conversion within two months after initiating antituberculosis agents among Malaysian with drug-susceptible smear-positive pulmonary tuberculosis patients. Retrospective data of pulmonary tuberculosis patients followed up at a tertiary hospital in the Northern region of Malaysia from 2013 until 2018 were collected and analysed. Nonlinear mixed-effect modelling software (NONMEM 7.3.0) was used to develop parametric survival models. The final model was further validated using Kaplan-Meier-visual predictive check (KM-VPC) approach, kernel-based hazard rate estimation method and sampling-importance resampling (SIR) method. A total of 224 patients were included in the study, with 34.4 % (77/224) of the patients remained positive at the end of 2 months of the intensive phase. Gompertz hazard function best described the data. The hazard of sputum conversion decreased by 39 % and 33 % for moderate and advanced lesions as compared to minimal baseline of chest X-ray severity, respectively (adjusted hazard ratio (aHR), 0.61; 95 % confidence intervals (95 % CI), (0.44-0.84) and 0.67, 95 % CI (0.53-0.84)). Meanwhile, the hazard also decreased by 59 % (aHR, 0.41; 95 % CI, (0.23-0.73)) and 48 % (aHR, 0.52; 95 % CI, (0.35-0.79)) between active and former drug abusers as compared to non-drug abuser, respectively. The successful development of the internally and externally validated final model allows a better estimation of the time to sputum conversion and provides a better understanding of the relationship with its predictors.

Explainable deep-neural-network supported scheme for tuberculosis detection from chest radiographs

Chest radiographs are examined in typical clinical settings by competent physicians for tuberculosis diagnosis. However, this procedure is time consuming and subjective. Due to the growing usage of machine learning techniques in applied sciences, researchers have begun applying comparable concepts to medical diagnostics, such as tuberculosis screening. In the period of extremely deep neural nets which comprised of hundreds of convolution layers for feature extraction, we create a shallow-CNN for screening of TB condition from Chest X-rays so that the model is able to offer appropriate interpretation for right diagnosis. The suggested model consists of four convolution-maxpooling layers with various hyperparameters that were optimized for optimal performance using a Bayesian optimization technique. The model was reported with a peak classification accuracy, F1-score, sensitivity and specificity of 0.95. In addition, the receiver operating characteristic (ROC) curve for the proposed shallow-CNN showed a peak area under the curve value of 0.976. Moreover, we have employed class activation maps (CAM) and Local Interpretable Model-agnostic Explanations (LIME), explainer systems for assessing the transparency and explainability of the model in comparison to a state-of-the-art pre-trained neural net such as the DenseNet.

Analysis on the Risk Factors of Malnutrition in Type 2 Diabetes Mellitus Patients with Pulmonary Tuberculosis

Objective

To explore the risk factors of malnutrition in type 2 diabetes mellitus combined with pulmonary tuberculosis (PTB-T2DM) patients and further to provide a clinical research basis for the identification and prevention of malnutrition.

Methods

From January 2020 to February 2022, 307 adult patients diagnosed with PTB-T2DM were enrolled in this retrospective study. According to whether malnutrition occurred after 6 months of treatment, patients were divided into malnutrition group (n = 123) and non-malnutrition group (n = 184). The nutritional status of patients was evaluated according to the Micro-Nutrition Assessment Scale (MNA). Evaluation of indicators was performed, including general information, disease characteristics of PTB-T2DM and laboratory indicators.

Results

Univariate logistic regression analysis showed that drinking, divorced, BMI <18.5kg/m2, weight <45kg, waist circumference <79cm, hip circumference <88cm, waist-to-hip ratio <69.99, calf circumference <26kg, grip strength <28kg, NRS score ≥3, Hb <106g/L, Alb <29.00g/L, PA <48.00μmol/L, GHB <3.40%, serum transferrin <1.37 mmol/L, serum potassium <3.18mmol/L, serum sodium <142.95 mmol/L, FEV1 ≥67.90% and RV <2.89% were risk factors for malnutrition in PTB-T2DM patients (all P < 0.05). The results of multivariate logistic regression analysis showed that drinking, divorced, weight <45kg, BMI <18.5kg/m2, NRS score ≥3, Hb <106g/L, Alb <29.00g/L, PA <48.00μmol/L, serum transferrin <1.37mmol/L, FEV1 ≥67.90% and RV <2.89% were independent risk factors for malnutrition in PTB-T2DM patients (all P < 0.05).

Conclusion

Drinking, divorced, weight <45kg, BMI <18.5kg/m2, NRS score ≥3, Hb <106g/L, Alb <29.00g/L, PA <48.00μmol/L, serum transferrin <1.37mmol/L, FEV1 ≥67.90% and RV <2.89% may be independent risk factors for malnutrition in PTB-T2DM patients, and timely identification of high-risk groups could improve the prognosis of PTB-T2DM patients.

Prevalence and prognostic significance of malnutrition risk in patients with pulmonary tuberculosis: A hospital-based cohort study

Background

The prevalence and prognostic significance of malnutrition risk remain unclear in Chinese patients with pulmonary tuberculosis. Therefore, we aimed to investigate the malnutrition risk in Chinese patients and explore the relationship between malnutrition risk and follow-up outcomes.

Methods

We conducted a hospital-based cohort study from January 2020 to December 2020. Malnutrition risks were evaluated using nutritional scales, including the Nutritional Risk Screening 2002 (NRS-2002), the controlling nutritional status score (CONUT), the geriatric nutritional risk index (GNRI), and the prognostic nutritional index (PNI). The primary outcome was all-cause mortality at a one-year follow-up. Malnutrition risk was calculated, and the relationship between malnutrition and follow-up outcomes was analyzed. We assessed the performance of malnutrition risks to predict clinical outcomes in prognostic models.

Results

A total of 1,075 patients were included. According to NRS-2002, CONUT, GNRI, and PNI, 818 (76.09%), 954 (88.74%), 682 (63.44%), and 364 (33.86%) patients were at risk of malnutrition, respectively. Before 1-year follow-up, a total of 99 patients (9.2%) had died. After adjustment for risk factors, the association between severe malnutrition in CONUT (HR = 4.78, 95% CI: 1.14-20.11, P = 0.033), GNRI (HR = 3.53, 95% CI: 1.70-7.34, P = 0.001), or PNI (HR = 2.94, 95% CI: 1.76-4.88, P < 0.001) and death before 1-year follow-up remained significant. The addition of the nutritional scales to prognostic models improved death prediction, as validated by the integrated discrimination index (all P-values of <0.05).

Conclusion

Malnutrition in patients with pulmonary tuberculosis was associated with an increased risk of all-cause death in the long-term follow-up. Our findings provided evidence for the use of admission nutrition screening in patients with pulmonary tuberculosis.

Clinical standards for drug-susceptible pulmonary TB

BACKGROUND: The aim of these clinical standards is to provide guidance on 'best practice´ for diagnosis, treatment and management of drug-susceptible pulmonary TB (PTB).METHODS: A panel of 54 global experts in the field of TB care, public health, microbiology, and pharmacology were identified; 46 participated in a Delphi process. A 5-point Likert scale was used to score draft standards. The final document represents the broad consensus and was approved by all 46 participants.RESULTS: Seven clinical standards were defined: Standard 1, all patients (adult or child) who have symptoms and signs compatible with PTB should undergo investigations to reach a diagnosis; Standard 2, adequate bacteriological tests should be conducted to exclude drug-resistant TB; Standard 3, an appropriate regimen recommended by WHO and national guidelines for the treatment of PTB should be identified; Standard 4, health education and counselling should be provided for each patient starting treatment; Standard 5, treatment monitoring should be conducted to assess adherence, follow patient progress, identify and manage adverse events, and detect development of resistance; Standard 6, a recommended series of patient examinations should be performed at the end of treatment; Standard 7, necessary public health actions should be conducted for each patient. We also identified priorities for future research into PTB.CONCLUSION: These consensus-based clinical standards will help to improve patient care by guiding clinicians and programme managers in planning and implementation of locally appropriate measures for optimal person-centred treatment for PTB.