A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis

Mortality among registered tuberculosis patients in Pune Municipal Corporation area, India

BACKGROUND

Deaths among tuberculosis patients due to varied causes are frequently reported. Usually, the death rate is high during the first six to eight months, i.e., the intensive phase of treatment. The healthcare personnel working under National Tuberculosis Elimination Program are reluctant to ascribe death to tuberculosis and may prefer to attribute the death to other causes. On the other hand, in hospitals, most death are attributed to tuberculosis without careful death audits and reasonable investigations. Comorbidities like diabetes, HIV, drug resistance, and drug-induced toxicity consequent to administering secondary lines of drugs need due consideration while ascertaining the cause of death. The study aimed to measure mortality within one year and a maximum of two years after registration. We also determined the cause of death by conducting a verbal autopsy by medico-social workers using the WHO modified autopsy tool. Two pairs of physicians ascertained cause of death by reviewing the collected information. We obtained the consensus opinion of a pair of physicians. In case of disputed opinion, opinion of senior physician from the other group was considered final.

MATERIAL AND METHODS

We obtained the list of registered tuberculosis patients in 2019-2020 in Pune Municipal Corporation. The authors conducted the study in 2021-22. The authors prepared a verbal autopsy tool based on the WHO tool. We trained the experienced medical social workers. They called registered phone numbers to know the patient's present status. The social workers paid home visits and confirmed the present status if the phone was not connected even after repeated calls. They collected all the required details, reviewed information and decided the cause of death. The collected detailed information was shared with pairs of senior physicians who ascertained the cause of death. We calculated standardized mortality ratio and Kaplan-Meier survival analysis.

RESULTS

The eligible patients were 7461, and there were 506 deaths. The death rate among males was higher (8.29%) compared to females (5.02%) [χ2 (with Yates correction) = 30.73; p < 0.00001]. The mean age of deceased and living patients was 42.77 (S.D. = 18.07) and 38.46 (S.D. = 17.54) years, respectively (t = 5.33; p < 0.0001). The death rate was 3.88 per 1000 person-months. More than 60% of patients died within six months of initiation of treatment. The overall standardized mortality ratio was 9.61; it decreased as the age advanced. Kaplan-Meier survival analysis showed that the overall survival for two years was 92.7%. The common causes were pneumonia, pulmonary tuberculosis, acute coronary syndrome, and some liver injury/disease.

CONCLUSIONS

The standardized mortality ratio due to tuberculosis is high. The common causes of death are pneumonia and acute coronary syndrome.

A predictive score for early in-patient tuberculosis mortality: A case-control study

Introduction

In-hospital mortality rates for tuberculosis (TB) patients are high within the first seven days of admission. This study sought to identify predictors of early inpatient mortality and assess the performance of a predictive score for early mortality in a Ugandan tertiary hospital.

Materials and methods

A case-control study was conducted at Kiruddu National Referral Hospital in Kampala, Uganda. Cases included patients admitted with TB who died within seven days of admission, while controls survived beyond this period. Logistic regression was utilized to identify early mortality predictors. The performance of an adapted predictive score (PROS score) was evaluated, assigning scores based on the following criteria: Pulse rate >100 beats/min (1 point), Respiratory rate >20 breaths/min (2 points), Oxygen saturation <92 % (4 points), and Systolic blood pressure <90 mmHg (2 points).

Results

Of 602 hospitalized TB patients, 187 (31.0 %) died during admission. Among these, 78 (41.7 %) died within seven days. Wasting (adjusted odds ratio [aOR] = 5.76, 95 % confidence interval [CI] 2.12-15.63, p = 0.001) and respiratory rate >20 breaths/min (aOR = 2.89, 95 % CI 1.19-7.00, p = 0.019) predicted early mortality. PROS score of ≥1 demonstrated a sensitivity of 87.8 % and negative predictive value of 90.0 %. The ultimate TB treatment success rate of all hospitalized patients (n = 599) was 47.4 % with 275 (45.9 %) dying during TB treatment.

Conclusion

Early and long term mortality rates among hospitalized TB patients are high. Wasting and tachypnea predict early inpatient mortality. The PROS score could be useful in ruling out low-risk patients in low-resource settings.

Clinical profile, laboratory characteristics and prognostic factors in patients with miliary tuberculosis

BACKGROUND

Miliary tuberculosis (TB) is a severe form of pulmonary TB. It is uncommon in immunocompetent patients. In this study, we aimed to investigate features of miliary TB (clinical, biological, and radiological) and to determine factors associated with unfavorable outcomes in a population of patients in the South East Tunisia where TB remains endemic.

METHODS

This is a retrospective study including patients diagnosed with miliary TB between 2006 and 2023. Factors independently associated with poor prognosis were determined by multivariate logistic regression analysis.

RESULTS

Miliary tuberculosis (TB) accounted for 1.8% (n = 36) of all TB cases diagnosed during the study period. A notable female predominance was observed, comprising 66.6% of the cohort. The median age of patients was 47.5 ± 11.33 years. The predominant clinical manifestations included cough (88.8%), loss of appetite (77.7%), and fever (58.3%). Radiologically, a typical miliary pattern was present in 83.3% of patients, although only 36.1% had positive sputum samples on direct smear microscopy. Notably, all patients tested negative for HIV serology. Extrapulmonary TB involvement was documented in 55.5% of cases. All patients were treated with first-line anti-TB medications, and the outcome was favorable in 77.7% (n = 28) of patients. However, 16.6% (n = 6) of patients succumbed to the disease. Factors significantly associated with unfavorable outcomes included age ≥65 years (odds ratio (OR) = 0.39; p = 0.03), diabetes (OR = 0.13; p = 0.046), presence of fever (OR = 2.89; p = 0.01), and oxygen saturation ≤92% at admission (OR = 3.2; p = 0.001).

CONCLUSION

Our study identified advanced age, diabetes, fever at baseline, and low oxygen saturation on admission as significant predictors of poor prognosis in patients with miliary tuberculosis. These findings highlight the need for early identification and targeted management of high-risk individuals to improve clinical outcomes.

Activities of Daily Living, Hypoxemia, and Lymphocytes Score for Predicting Mortality Risk in Patients With Pulmonary TB

BACKGROUND

A clinically applicable mortality risk prediction system for pulmonary TB may improve treatment outcomes, but no easy-to-calculate and accurate score has yet been reported. The aim of this study was to construct a simple and objective disease severity score for patients with pulmonary TB.

RESEARCH QUESTION

Does a clinical score consisting of simple objective factors predict the mortality risk of patients with pulmonary TB?

STUDY DESIGN AND METHODS

The data set from our previous prospective study that recruited patients newly diagnosed with pulmonary TB was used for the development cohort. Patients for the validation cohort were prospectively recruited between March 2021 and September 2022. The primary end point was all-cause in-hospital mortality. Using Cox proportional hazards regression, a mortality risk prediction model was optimized in the development cohort. The disease severity score was developed by assigning integral points to each variate.

RESULTS

The data from 252 patients in the development cohort and 165 patients in the validation cohort were analyzed, of whom 39 (15.5%) and 17 (10.3%), respectively, died in the hospital. The disease severity score (named the AHL score) included three clinical parameters: activities of daily living (semi-dependent, 1 point; totally dependent, 2 points); hypoxemia (1 point), and lymphocytes (< 720/μL, 1 point). This score showed good discrimination with a C statistic of 0.902 in the development cohort and 0.842 in the validation cohort. We stratified the score into three groups (scores of 0, 1-2, and 3-4), which clearly corresponded to low (0% and 1.3%), intermediate (13.5% and 8.9%), and high (55.8% and 39.3%) mortality risk in the development and validation cohorts.

INTERPRETATION

The easy-to-calculate AHL disease severity score for patients with pulmonary TB was able to categorize patients into three mortality risk groups with great accuracy.

CLINICAL TRIAL REGISTRATION

University Hospital Medical Information Network Center; No. UMIN000012727 and No. UMIN000043849; URL: www.umin.ac.jp.

Development of prognostic scoring system for predicting 1-year mortality among pulmonary tuberculosis patients in South India

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.

Screening adults with tuberculosis for severe illness at notification: programme experience from Gujarat, India

BACKGROUND

National tuberculosis (TB) programmes in high-burden countries do not systematically assess severity at diagnosis followed by referral for inpatient care. Due to limited capacity, comprehensive assessment of all TB patients is not practical. In three districts of Gujarat (West India) in June 2021, we determined the feasibility of screening for severe illness by paramedical staff of public facilities and the burden of 'high risk for severe illness' at notification among adults (≥15 y of age) with TB.

METHODS

In this cross-sectional study, the screening criteria for high risk for severe illness was the presence of any one of the following: body mass index (BMI) ≤14.0 kg/m2, BMI ≤16.0 kg/m2 with bilateral leg swelling, respiratory rate >24/min, oxygen saturation <94% or inability to stand without support. We summarized the feasibility indicators and burden using proportion (95% confidence interval [CI]) and median, as applicable.

RESULTS

Of 626 notified adults, 87% were screened. The median time interval for screening was 3 d from notification and all indicators were collected in 97% of patients. The burden of high risk for severe illness was high, at 41.6% (95% CI 37.5 to 45.8).

CONCLUSIONS

High burden and feasibility (high coverage, acceptable time interval and minimal missing data) makes a strong case for routine screening of severe illness.

The impact of single-cell genomics on the field of mycobacterial infection

Genome sequencing projects of humans and other organisms reinforced that the complexity of biological systems is largely attributed to the tight regulation of gene expression at the epigenome and RNA levels. As a consequence, plenty of technological developments arose to increase the sequencing resolution to the cell dimension creating the single-cell genomics research field. Single-cell RNA sequencing (scRNA-seq) is leading the advances in this topic and comprises a vast array of different methodologies. scRNA-seq and its variants are more and more used in life science and biomedical research since they provide unbiased transcriptomic sequencing of large populations of individual cells. These methods go beyond the previous “bulk” methodologies and sculpt the biological understanding of cellular heterogeneity and dynamic transcriptomic states of cellular populations in immunology, oncology, and developmental biology fields. Despite the large burden caused by mycobacterial infections, advances in this field obtained via single-cell genomics had been comparatively modest. Nonetheless, seminal research publications using single-cell transcriptomics to study host cells infected by mycobacteria have become recently available. Here, we review these works summarizing the most impactful findings and emphasizing the different and recent single-cell methodologies used, potential issues, and problems. In addition, we aim at providing insights into current research gaps and potential future developments related to the use of single-cell genomics to study mycobacterial infection.

Screening for Severe Illness at Diagnosis Has the Potential to Prevent Early TB Deaths: Programmatic Experience From Karnataka, India

Despite TB being a potentially fatal disease, severity is not systematically assessed at the start of drug-susceptible TB treatment. We document our experience screening people for severe illness at diagnosis/notification in program settings and the potential impact on reducing early TB deaths.

Due to the coronavirus disease (COVID-19) pandemic and its associated response, TB deaths increased for the first time in a decade. In any potentially fatal illness, an assessment of severity is essential. This is not systematically done for adults with TB, mostly due to a lack of policy and/or limited availability of diagnostic and clinical capacity. We developed a screening tool using simple and easily measurable indicators that can be used by paramedical TB program staff to quickly identify people with severe illness. During October–November 2020 in Karnataka, India, the paramedical program staff from 16 districts screened people with TB (aged ≥15 years) notified by public facilities for “high risk of severe illness,” which was defined as the presence of any of the following indicators: (1) body mass index (BMI) ≤14.0 kg/m²; (2) BMI ≤16.0 kg/m² with bilateral leg swelling; (3) respiratory rate >24/minute; (4) oxygen saturation <94%; (5) inability to stand without support. In this cohort study, we determined the incidence of program-recorded early deaths (within 2 months) and its association with high risk of severe illness. Of 3,010 people with TB, 1,529 (50.8%) were screened at diagnosis/notification, of whom 537 (35.1%) had a high risk of severe illness. There were 195 (6.5%, 95% CI=5.7, 7.4) early deaths: 59 (30.2%) within a week and 100 (51.3%) within 2 weeks of treatment initiation. The incidence of early deaths was significantly higher among those with high risk of severe illness (8.9%) at diagnosis compared to those without (3.8%) [adjusted relative risk: 2.36 (95% confidence interval=1.57, 3.55)]. To conclude, early deaths were especially high during the first 2 weeks and strongly associated with a high risk of severe illness at diagnosis/notification. Screening for severe illness should be explored as a potential strategy to end TB deaths.

The Neglected Contribution of Streptomycin to the Tuberculosis Drug Resistance Problem

The airborne pathogen Mycobacterium tuberculosis is responsible for a present major public health problem worsened by the emergence of drug resistance. M. tuberculosis has acquired and developed streptomycin (STR) resistance mechanisms that have been maintained and transmitted in the population over the last decades. Indeed, STR resistant mutations are frequently identified across the main M. tuberculosis lineages that cause tuberculosis outbreaks worldwide. The spread of STR resistance is likely related to the low impact of the most frequent underlying mutations on the fitness of the bacteria. The withdrawal of STR from the first-line treatment of tuberculosis potentially lowered the importance of studying STR resistance. However, the prevalence of STR resistance remains very high, could be underestimated by current genotypic methods, and was found in outbreaks of multi-drug (MDR) and extensively drug (XDR) strains in different geographic regions. Therefore, the contribution of STR resistance to the problem of tuberculosis drug resistance should not be neglected. Here, we review the impact of STR resistance and detail well-known and novel candidate STR resistance mechanisms, genes, and mutations. In addition, we aim to provide insights into the possible role of STR resistance in the development of multi-drug resistant tuberculosis.

Risk factors for mortality and multidrug resistance in pulmonary tuberculosis in Guatemala: A retrospective analysis of mandatory reporting

•

National TB cohort analyzing risk factors associated with MDR-TB and mortality in Guatemala.

•

Indigenous ethnicity and prior TB treatment were associated with increased risk of mortality and MDR-TB.

•

HIV/Unknown HIV status were associated with increased mortality and diabetes with risk for MDR-TB.

Background

Risk factors for mortality and MDR-TB in Guatemala are poorly understood. We aimed to identify risk factors to assist in targeting public health interventions.

Methods

We performed a retrospective study of adults with pulmonary TB reported to the Guatemalan TB Program between January 1, 2016 and December 31, 2017. The primary objective was to determine risk factors for mortality in pulmonary TB. The secondary objective was to determine risk factors associated with MDR-TB.

Results

Among 3,945 patients with pulmonary TB, median age was 39 years (IQR 25–54), 59% were male, 25% of indigenous ethnicity, 1.1% had MDR-TB and 3.9% died. On multivariable analysis, previous TB treatment (odds ratio [OR] 3.57, CI 2.24–5.68 [p < 0.001]), living with HIV (OR 3.98, CI 2.4–6.17 [p < 0.001]), unknown HIV diagnosis (OR 2.65, CI 1.68–4.18 [p < 0.001]), indigenous ethnicity (OR 1.79, CI 1.18–2.7 [p = 0.005]), malnutrition (OR 7.33, CI 3.24–16.59 [p < 0.001]), and lower educational attainment (OR 2.86, CI 1.43–5.88 [p = 0.003]) were associated with mortality. Prior treatment (OR 53.76, CI 25.04–115.43 [p < 0.001]), diabetes (OR 4.13, CI 2.04–8.35 [p < 0.001]), and indigenous ethnicity (OR 11.83, CI 1.46–95.73 [p = 0.02]) were associated with MDR-TB.

Conclusions

In Guatemala, both previous TB treatment and indigenous ethnicity were associated with higher TB mortality and MDR-TB risk among patients with pulmonary TB.

Screening People with Tuberculosis for High Risk of Severe Illness at Notification: Programmatic Experience from Karnataka, India

Due to limited availability of diagnostics and capacity, people with tuberculosis do not always undergo systematic assessment for severe illness (requiring inpatient care). In Karnataka (south India), para-medical programme staff used a screening tool to identify people at 'high risk of severe illness', defined using indicators of very severe undernutrition, abnormal vital signs and poor performance status (any one): (i) body mass index (BMI) ≤ 14.0 kg/m² (ii) BMI ≤ 16.0 kg/m² with bilateral leg swelling (iii) respiratory rate > 24/min (iv) oxygen saturation < 94% (v) inability to stand without support. Of 3020 adults notified from public facilities (15 October to 30 November 2020) in 16 districts, 1531 (51%) were screened (district-wise range: 13-90%) and of them, 538 (35%) were classified as 'high risk of severe illness'. Short median delays in screening from notification (five days), and all five indicators being collected for 88% of patients, suggests the feasibility of using this tool in programme settings. However, districts with poor screening coverage require further attention. To end tuberculosis deaths, screening should be followed by referral to higher facilities for comprehensive clinical evaluation, to assess the need for inpatient care. Future studies should assess the validity (especially sensitivity in picking severely ill patients) of this screening tool.

Heterogeneous Streptomycin Resistance Level Among Mycobacterium tuberculosis Strains From the Same Transmission Cluster

Widespread and frequent resistance to the second-line tuberculosis (TB) medicine streptomycin, suggests ongoing transmission of low fitness cost streptomycin resistance mutations. To investigate this hypothesis, we studied a cohort of 681 individuals from a TB epidemic in Portugal. Whole-genome sequencing (WGS) analyses were combined with phenotypic growth studies in culture media and in mouse bone marrow derived macrophages. Streptomycin resistance was the most frequent resistance in the cohort accounting for 82.7% (n = 67) of the resistant Mycobacterium tuberculosis isolates. WGS of 149 clinical isolates identified 13 transmission clusters, including three clusters containing only streptomycin resistant isolates. The biggest cluster was formed by eight streptomycin resistant isolates with a maximum of five pairwise single nucleotide polymorphisms of difference. Interestingly, despite their genetic similarity, these isolates displayed different resistance levels to streptomycin, as measured both in culture media and in infected mouse bone marrow derived macrophages. The genetic bases underlying this phenotype are a combination of mutations in gid and other genes. This study suggests that specific streptomycin resistance mutations were transmitted in the cohort, with the resistant isolates evolving at the cluster level to allow low-to-high streptomycin resistance levels without a significative fitness cost. This is relevant not only to better understand transmission of streptomycin resistance in a clinical setting dominated by Lineage 4 M. tuberculosis infections, but mainly because it opens new prospects for the investigation of selection and spread of drug resistance in general.

Clinical and epidemiological features of tuberculosis isolated from critically ill patients

Human tuberculosis is still a major world health concern. In Uruguay, contrary to the world trend, an increase in cases has been observed since 2006. Although the incidence of MDR-resistant strains is low and no cases of XDR-TB were registered, an increase in the number of patients with severe tuberculosis requiring critical care admission was observed. As a first aim, we performed the analysis of the genetic structure of strains isolated from patients with severe tuberculosis admitted to an intensive care unit. We compared these results with those corresponding to the general population observing a statistically significant increase in the Haarlem genotypes among ICU patients (53.3% vs 34.7%; p<0.05). In addition, we investigated the association of clinical outcomes with the genotype observing a major incidence of hepatic dysfunctions among patients infected with the Haarlem strain (p<0.05). The cohort presented is one of the largest studied series of critically ill patients with tuberculosis.

In-hospital mortality of pulmonary tuberculosis with acute respiratory failure and related clinical risk factors

Background/objective

Data on acute respiratory failure (ARF) in pulmonary tuberculosis (PTB) patients is limited. This study aims to investigate in-hospital mortality, its clinical risk factors and the accuracy of the existing scoring system in predicting in-hospital mortality.

Methods

An observational prospective cohort study involving PTB patients with ARF in tertiary hospital, between January 2017 and December 2018, was conducted. The in-hospital mortality was predicted using the National Early Warning Score 2 (NEWS2), quick Sequential Organ Failure Assessment (qSOFA) and CRB-65. Regression models were run to analyze the clinical risk factors for in-hospital Mortality. Sensitivity and specificity of scoring systems were calculated using a Wilson score interval.

Results

A total of 111 subjects were included. Most of subjects were hypoxemic type respiratory failure (68.5%), advanced lesions (62.2%), new cases (70.3%) and pneumonia co-infection (72.1%) patients. Invasive mechanical ventilation was utilized for 29.73% of cases. There were 53 (47.75%) in-hospital mortality cases and its risk factors were intensive phase treatment (3.34 OR; CI95% 1.27-8.78), P/F ratio < 100 (OR 4.30; CI 95% 1.75-10.59) and renal insufficiency (4.09 OR; CI95% 1.46-11.49). The sensitivity and specificity of NEWS2 ≥ 6, qSOFA ≥ 2 and CRB-65 ≥ 2 were 62.26% and 67.24%; 60.38% and 72.41%; 41.51% and 84.48% respectively.

Conclusions

Most of PTB with ARF were new cases, advanced lesion and hypoxemic type respiratory failure. Intensive phase treatment, severe hypoxemia and renal insufficiency are independent predictors of in-hospital mortality in PTB patients with ARF. NEWS2, qSOFA and CRB-65 scores were poor to predict the in-hospital mortality.

Benchmarking Machine Learning Models to Assist in the Prognosis of Tuberculosis

Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed with TB, it is critical that healthcare workers make the most appropriate treatment decision given the individual conditions of the patient and the likely course of the disease based on medical experience. Depending on the prognosis, delayed or inappropriate treatment can result in unsatisfactory results including the exacerbation of clinical symptoms, poor quality of life, and increased risk of death. This work benchmarks machine learning models to aid TB prognosis using a Brazilian health database of confirmed cases and deaths related to TB in the State of Amazonas. The goal is to predict the probability of death by TB thus aiding the prognosis of TB and associated treatment decision making process. In its original form, the data set comprised 36,228 records and 130 fields but suffered from missing, incomplete, or incorrect data. Following data cleaning and preprocessing, a revised data set was generated comprising 24,015 records and 38 fields, including 22,876 reported cured TB patients and 1139 deaths by TB. To explore how the data imbalance impacts model performance, two controlled experiments were designed using (1) imbalanced and (2) balanced data sets. The best result is achieved by the Gradient Boosting (GB) model using the balanced data set to predict TB-mortality, and the ensemble model composed by the Random Forest (RF), GB and Multi-Layer Perceptron (MLP) models is the best model to predict the cure class.

Systematic review of prediction models for pulmonary tuberculosis treatment outcomes in adults

OBJECTIVE

To systematically review and critically evaluate prediction models developed to predict tuberculosis (TB) treatment outcomes among adults with pulmonary TB.

DESIGN

Systematic review.

DATA SOURCES

PubMed, Embase, Web of Science and Google Scholar were searched for studies published from 1 January 1995 to 9 January 2020.

STUDY SELECTION AND DATA EXTRACTION

Studies that developed a model to predict pulmonary TB treatment outcomes were included. Study screening, data extraction and quality assessment were conducted independently by two reviewers. Study quality was evaluated using the Prediction model Risk Of Bias Assessment Tool. Data were synthesised with narrative review and in tables and figures.

RESULTS

14 739 articles were identified, 536 underwent full-text review and 33 studies presenting 37 prediction models were included. Model outcomes included death (n=16, 43%), treatment failure (n=6, 16%), default (n=6, 16%) or a composite outcome (n=9, 25%). Most models (n=30, 81%) measured discrimination (median c-statistic=0.75; IQR: 0.68-0.84), and 17 (46%) reported calibration, often the Hosmer-Lemeshow test (n=13). Nineteen (51%) models were internally validated, and six (16%) were externally validated. Eighteen (54%) studies mentioned missing data, and of those, half (n=9) used complete case analysis. The most common predictors included age, sex, extrapulmonary TB, body mass index, chest X-ray results, previous TB and HIV. Risk of bias varied across studies, but all studies had high risk of bias in their analysis.

CONCLUSIONS

TB outcome prediction models are heterogeneous with disparate outcome definitions, predictors and methodology. We do not recommend applying any in clinical settings without external validation, and encourage future researchers adhere to guidelines for developing and reporting of prediction models.

TRIAL REGISTRATION

The study was registered on the international prospective register of systematic reviews PROSPERO (CRD42020155782).

Mycobacterium tuberculosis associated with severe tuberculosis evades cytosolic surveillance systems and modulates IL-1β production

Genetic diversity of Mycobacterium tuberculosis affects immune responses and clinical outcomes of tuberculosis (TB). However, how bacterial diversity orchestrates immune responses to direct distinct TB severities is unknown. Here we study 681 patients with pulmonary TB and show that M. tuberculosis isolates from cases with mild disease consistently induce robust cytokine responses in macrophages across multiple donors. By contrast, bacteria from patients with severe TB do not do so. Secretion of IL-1β is a good surrogate of the differences observed, and thus to classify strains as probable drivers of different TB severities. Furthermore, we demonstrate that M. tuberculosis isolates that induce low levels of IL-1β production can evade macrophage cytosolic surveillance systems, including cGAS and the inflammasome. Isolates exhibiting this evasion strategy carry candidate mutations, generating sigA recognition boxes or affecting components of the ESX-1 secretion system. Therefore, we provide evidence that M. tuberculosis strains manipulate host-pathogen interactions to drive variable TB severities.

Risk factors for early mortality in patients with pulmonary tuberculosis admitted to the emergency room

BACKGROUND AND OBJECTIVES

Mortality of patients with pulmonary tuberculosis (TB) admitted to emergency departments is high. This study was aimed at analysing the risk factors associated with early mortality and designing a risk score based on simple parameters.

METHODS

This prospective case-control study enrolled patients admitted to the emergency department of a referral TB hospital. Clinical, radiological, biochemical and microbiological risk factors associated with death were compared among patients dying within one week from admission (cases) and those surviving (controls).

RESULTS

Forty-nine of 250 patients (19.6%) experienced early mortality. Multiple logistic regression analysis showed that oxygen saturation (SaO₂) ≤90%, severe malnutrition, tachypnoea, tachycardia, hypotension, advanced disease at chest radiography, severe anaemia, hyponatremia, hypoproteinemia and hypercapnia were independently and significantly associated with early mortality. A clinical scoring system was further designed to stratify the risk of death by selecting five simple parameters (SpO₂ ≤ 90%, tachypnoea, hypotension, advanced disease at chest radiography and tachycardia). This model predicted early mortality with a positive predictive value of 94.88% and a negative predictive value of 19.90%.

CONCLUSIONS

The scoring system based on simple parameters may help to refer severely ill patients early to a higher level to reduce mortality, improve success rates, minimise the need for pulmonary rehabilitation and prevent post-treatment sequelae.

Tuberculosis deaths are predictable and preventable: Comprehensive assessment and clinical care is the key

The goal of reducing tuberculosis (TB) mortality in the END TB Strategy can be achieved if TB deaths are considered predictable and preventable. This will require programs to examine and address some key gaps in the understanding of the distribution and determinants of TB mortality and the current model of assessment and care in high burden countries.

Most deaths in high-burden countries occur in the first eight weeks of treatment and in those belonging to the age group of 15–49 years, living in poverty, with HIV infection and/or low body mass index (BMI). Deaths result from extensive disease, comorbidities like advanced HIV disease complicated with other infections (bacterial, fungal, bloodstream), and moderate-severe undernutrition. Most early deaths in patients with TB, even with TB-HIV co-infection, are due to TB itself.

Comprehensive assessment and clinical care are a prerequisite of patient-centered care. Simple independent predictors of death like unstable vital signs, BMI, mid-upper arm circumference, or inability to stand or walk unaided can be used by programs for risk assessment. Programs need to define criteria for referral for inpatient care, address the paucity of hospital beds and develop and implement guidelines for the clinical management of seriously ill patients with TB, advanced HIV disease and severe undernutrition as co-morbidities. Programs should also consider notification and audit of all TB deaths, similar to audit of maternal deaths, and address the issues in delays in diagnosis, treatment, and quality of care.

Risk score for predicting mortality including urine lipoarabinomannan detection in hospital inpatients with HIV-associated tuberculosis in sub-Saharan Africa: Derivation and external validation cohort study

BACKGROUND

The prevalence of and mortality from HIV-associated tuberculosis (HIV/TB) in hospital inpatients in Africa remains unacceptably high. Currently, there is a lack of tools to identify those at high risk of early mortality who may benefit from adjunctive interventions. We therefore aimed to develop and validate a simple clinical risk score to predict mortality in high-burden, low-resource settings.

METHODS AND FINDINGS

A cohort of HIV-positive adults with laboratory-confirmed TB from the STAMP TB screening trial (Malawi and South Africa) was used to derive a clinical risk score using multivariable predictive modelling, considering factors at hospital admission (including urine lipoarabinomannan [LAM] detection) thought to be associated with 2-month mortality. Performance was evaluated internally and then externally validated using independent cohorts from 2 other studies (LAM-RCT and a Médecins Sans Frontières [MSF] cohort) from South Africa, Zambia, Zimbabwe, Tanzania, and Kenya. The derivation cohort included 315 patients enrolled from October 2015 and September 2017. Their median age was 36 years (IQR 30-43), 45.4% were female, median CD4 cell count at admission was 76 cells/μl (IQR 23-206), and 80.2% (210/262) of those who knew they were HIV-positive at hospital admission were taking antiretroviral therapy (ART). Two-month mortality was 30% (94/315), and mortality was associated with the following factors included in the score: age 55 years or older, male sex, being ART experienced, having severe anaemia (haemoglobin < 80 g/l), being unable to walk unaided, and having a positive urinary Determine TB LAM Ag test (Alere). The score identified patients with a 46.4% (95% CI 37.8%-55.2%) mortality risk in the high-risk group compared to 12.5% (95% CI 5.7%-25.4%) in the low-risk group (p < 0.001). The odds ratio (OR) for mortality was 6.1 (95% CI 2.4-15.2) in high-risk patients compared to low-risk patients (p < 0.001). Discrimination (c-statistic 0.70, 95% CI 0.63-0.76) and calibration (Hosmer-Lemeshow statistic, p = 0.78) were good in the derivation cohort, and similar in the external validation cohort (complete cases n = 372, c-statistic 0.68 [95% CI 0.61-0.74]). The validation cohort included 644 patients between January 2013 and August 2015. Median age was 36 years, 48.9% were female, and median CD4 count at admission was 61 (IQR 21-145). OR for mortality was 5.3 (95% CI 2.2-9.5) for high compared to low-risk patients (complete cases n = 372, p < 0.001). The score also predicted patients at higher risk of death both pre- and post-discharge. A simplified score (any 3 or more of the predictors) performed equally well. The main limitations of the scores were their imperfect accuracy, the need for access to urine LAM testing, modest study size, and not measuring all potential predictors of mortality (e.g., tuberculosis drug resistance).

CONCLUSIONS

This risk score is capable of identifying patients who could benefit from enhanced clinical care, follow-up, and/or adjunctive interventions, although further prospective validation studies are necessary. Given the scale of HIV/TB morbidity and mortality in African hospitals, better prognostic tools along with interventions could contribute towards global targets to reduce tuberculosis mortality.

Predictors and outcomes of disseminated tuberculosis in an intermediate burden setting

SETTING

University-affiliated hospital located in Porto, North Portugal, an area with a low to intermediate incidence of tuberculosis (TB).

OBJECTIVE

To identify predictors and outcomes of disseminated TB (dTB).

DESIGN

A cohort of patients diagnosed with TB between 2007 and 2013 was retrospectively analysed. Patients with dTB criteria were characterized and compared to single organ TB cases. Factors independently associated with dTB were determined by multivariate logistic regression analysis.

RESULTS

A total of 744 patients were analysed, including 145 with dTB. Independent risk factors for dTB were pharmacological immunosuppression (OR 5.6, 95% CI 2.8-11.3), HIV infection (OR 5.1, 95% CI 3.1-8.3), chronic liver failure or cirrhosis (OR 2.3, 95% CI 1.4-4.1) and duration of symptoms (OR 2.3, 95% CI 1.4-3.8). Compared to single organ TB, the clinical presentation of dTB patients differed by the absence of haemoptysis (OR 3.2, 95% CI 1.3-8.4) and of dyspnoea (OR 1.9, 95% CI 1.2-3.1), presence of weight loss (OR 1.8, 95% CI 1.1-2.9), night sweats (OR 1.7, 95% CI 1.1-2.7) and bilateral lung involvement (OR 4.4, 95% CI 2.8-7.1). Mortality and time until culture conversion were higher for dTB patients, although not reaching statistical significance.

CONCLUSION

Immunosuppressive conditions and chronic liver failure or cirrhosis were associated with increased risk of dTB. The haematogenous spread may be dependent on longer symptomatic disease and usually progresses with bilateral lung involvement.

Development and validation of a risk score to predict mortality during TB treatment in patients with TB-diabetes comorbidity

BACKGROUND

Making an accurate prognosis for mortality during tuberculosis (TB) treatment in TB-diabetes (TB-DM) comorbid patients remains a challenge for health professionals, especially in low TB prevalent populations, due to the lack of a standardized prognostic model.

METHODS

Using de-identified data from TB-DM patients from Texas, who received TB treatment had a treatment outcome of completed treatment or died before completion, reported to the National TB Surveillance System from January 2010-December 2016, we developed and internally validated a mortality scoring system, based on the regression coefficients.

RESULTS

Of 1227 included TB-DM patients, 112 (9.1%) died during treatment. The score used nine characteristics routinely collected by most TB programs. Patients were divided into three groups based on their score: low-risk (< 12 points), medium-risk (12-21 points) and high-risk (≥22 points). The model had good performance (with an area under the receiver operating characteristic (ROC) curve of 0.83 in development and 0.82 in validation), and good calibration. A practical mobile calculator app was also created ( https://oaa.app.link/Isqia5rN6K ).

CONCLUSION

Using demographic and clinical characteristics which are available from most TB programs at the patient's initial visits, our simple scoring system had good performance and may be a practical clinical tool for TB health professionals in identifying TB-DM comorbid patients with a high mortality risk.

Tuberculosis Mortality in the United States: Epidemiology and Prevention Opportunities

Rationale: More information on risk factors for death from tuberculosis in the United States could help reduce the tuberculosis mortality rate, which has remained steady for more than a decade.Objective: To identify risk factors for tuberculosis-related death in adults.Methods: We performed a retrospective study of 1,304 adults with tuberculosis who died before treatment completion and 1,039 frequency-matched control subjects who completed tuberculosis treatment in 2005 to 2006 in 13 states reporting 65% of U.S. tuberculosis cases. We used in-depth record abstractions and a standard algorithm to classify deaths in persons with tuberculosis as tuberculosis-related or not. We then compared these classifications to causes of death as coded in death certificates. We used multivariable logistic regression to calculate adjusted odds ratios for predictors of tuberculosis-related death among adults compared with those who completed tuberculosis treatment.Results: Of 1,304 adult deaths, 942 (72%) were tuberculosis related, 272 (21%) were not, and 90 (7%) could not be classified. Of 847 tuberculosis-related deaths with death certificates available, 378 (45%) did not list tuberculosis as a cause of death. Adjusting for known risks, we identified new risks for tuberculosis-related death during treatment: absence of pyrazinamide in the initial regimen (adjusted odds ratio, 3.4; 95% confidence interval, 1.9-6.0); immunosuppressive medications (adjusted odds ratio, 2.5; 95% confidence interval, 1.1-5.6); incomplete tuberculosis diagnostic evaluation (adjusted odds ratio, 2.2; 95% confidence interval, 1.5-3.3), and an alternative nontuberculosis diagnosis before tuberculosis diagnosis (adjusted odds ratio, 1.6; 95% confidence interval, 1.2-2.2).Conclusions: Most persons who died with tuberculosis had a tuberculosis-related death. Intensive record review revealed tuberculosis as a cause of death more often than did death certificate diagnoses. New tools, such as a tuberculosis mortality risk score based on our study findings, may identify patients with tuberculosis for in-hospital interventions to prevent death.

Prognostic score to predict mortality during TB treatment in TB/HIV co-infected patients

Background

Estimating mortality risk during TB treatment in HIV co-infected patients is challenging for health professionals, especially in a low TB prevalence population, due to the lack of a standardized prognostic system. The current study aimed to develop and validate a simple mortality prognostic scoring system for TB/HIV co-infected patients.

Methods

Using data from the CDC’s Tuberculosis Genotyping Information Management System of TB patients in Texas reported from 01/2010 through 12/2016, age ≥15 years, HIV(+), and outcome being “completed” or “died”, we developed and internally validated a mortality prognostic score using multiple logistic regression. Model discrimination was determined by the area under the receiver operating characteristic (ROC) curve (AUC). The model’s good calibration was determined by a non-significant Hosmer-Lemeshow’s goodness of fit test.

Results

Among the 450 patients included in the analysis, 57 (12.7%) died during TB treatment. The final prognostic score used six characteristics (age, residence in long-term care facility, meningeal TB, chest x-ray, culture positive, and culture not converted/unknown), which are routinely collected by TB programs. Prognostic scores were categorized into three groups that predicted mortality: low-risk (<20 points), medium-risk (20–25 points) and high-risk (>25 points). The model had good discrimination and calibration (AUC = 0.82; 0.80 in bootstrap validation), and a non-significant Hosmer-Lemeshow test p = 0.71.

Conclusion

Our simple validated mortality prognostic scoring system can be a practical tool for health professionals in identifying TB/HIV co-infected patients with high mortality risk.

A complex scenario of tuberculosis transmission is revealed through genetic and epidemiological surveys in Porto

Background

Tuberculosis (TB) incidence is decreasing worldwide and eradication is becoming plausible. In low-incidence countries, intervention on migrant populations is considered one of the most important strategies for elimination. However, such measures are inappropriate in European areas where TB is largely endemic, such as Porto in Portugal. We aim to understand transmission chains in Porto through a genetic characterization of Mycobacterium tuberculosis strains and through a detailed epidemiological evaluation of cases.

Methods

We genotyped the M. tuberculosis strains using the MIRU-VNTR system. We performed an evolutionary reconstruction of the genotypes with median networks, used in this context for the first time. TB cases from a period of two years were evaluated combining genetic, epidemiological and georeferencing information.

Results

The data reveal a unique complex scenario in Porto where the autochthonous population acts as a genetic reservoir of M. tuberculosis diversity with discreet episodes of transmission, mostly undetected using classical epidemiology alone.

Conclusions

Although control policies have been successful in decreasing incidence in Porto, the discerned complexity suggests that, for elimination to be a realistic goal, strategies need to be adjusted and coupled with a continuous genetic characterization of strains and detailed epidemiological evaluation, in order to successfully identify and interrupt transmission chains.

The Troika Host-Pathogen-Extrinsic Factors in Tuberculosis: Modulating Inflammation and Clinical Outcomes

The already enormous burden caused by tuberculosis (TB) will be further aggravated by the association of this disease with modern epidemics, as human immunodeficiency virus and diabetes. Furthermore, the increasingly aging population and the wider use of suppressive immune therapies hold the potential to enhance the incidence of TB. New preventive and therapeutic strategies based on recent advances on our understanding of TB are thus needed. In particular, understanding the intricate network of events modulating inflammation in TB will help to build more effective vaccines and host-directed therapies to stop TB. This review integrates the impact of host, pathogen, and extrinsic factors on inflammation and the almost scientifically unexplored complexity emerging from the interactions between these three factors. We highlight the exciting data showing a contribution of this troika for the clinical outcome of TB and the need of incorporating it when developing novel strategies to rewire the immune response in TB.