{"id":53882,"date":"2025-07-08T10:00:49","date_gmt":"2025-07-08T04:30:49","guid":{"rendered":"https:\/\/vajiramandravi.com\/current-affairs\/?p=53882"},"modified":"2025-07-08T11:12:30","modified_gmt":"2025-07-08T05:42:30","slug":"tamil-nadu-leads-with-ai-based-tb-death-prediction-model","status":"publish","type":"post","link":"https:\/\/vajiramandravi.com\/current-affairs\/tamil-nadu-leads-with-ai-based-tb-death-prediction-model\/","title":{"rendered":"Tamil Nadu Leads with AI-Based TB Death Prediction Model"},"content":{"rendered":"<h2 style=\"text-align: justify;\"><span style=\"font-weight: 400;\">TB Death Prediction Model Latest News<\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Tamil Nadu has become the first Indian state to integrate a TB death prediction model into its State TB Elimination Programme, enabling early identification and hospitalisation of high-risk patients to reduce tuberculosis-related mortality.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Introduction<\/span><\/h2>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">In a landmark step towards eliminating <\/span><a href=\"https:\/\/vajiramandravi.com\/current-affairs\/tuberculosis-in-india-cases-challenges-national-eradication-plan\/\" target=\"_blank\"><span style=\"font-weight: 400;\">tuberculosis<\/span><\/a><span style=\"font-weight: 400;\"> (TB), Tamil Nadu has become the first state in India to deploy a predictive model that estimates the likelihood of death in TB patients.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Integrated with the state\u2019s existing digital triage platform TB SeWA, this model is designed to enable faster hospital admissions for severely ill patients, ultimately reducing TB-related mortality.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">This innovation is a collaborative outcome of the Indian Council of Medical Research\u2019s National Institute of Epidemiology (ICMR-NIE) and the Tamil Nadu State Health Department under the larger framework of Tamil Nadu Kasanoi Erappila Thittam (TN-KET).<\/span><\/li>\n<\/ul>\n<h2><span style=\"font-weight: 400;\">The Predictive Model and How It Works<\/span><\/h2>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The newly launched predictive model uses five clinical indicators at the time of TB diagnosis:<\/span>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Body Mass Index (BMI)<\/b><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Presence of pedal oedema (swelling of feet)<\/b><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Respiratory rate<\/b><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Oxygen saturation levels<\/b><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Ability to stand without support<\/b><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Healthcare workers input these variables into the TB SeWA application. Based on this input, the model calculates the probability of death ranging from <\/span><b>10% to 50%<\/b><span style=\"font-weight: 400;\"> for severely ill patients.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">For those not flagged as severely ill, the predicted mortality risk remains between <\/span><b>1% and 4%<\/b><span style=\"font-weight: 400;\">.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">This sharp differentiation in risk estimation helps frontline healthcare staff prioritise admissions and initiate early treatment, which is especially crucial given that over <\/span><b>70% of TB deaths occur within the first two months<\/b><span style=\"font-weight: 400;\"> of treatment.<\/span><\/li>\n<\/ul>\n<h2 style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Significance of the Integration<\/span><\/h2>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Prior to this model, Tamil Nadu&#8217;s TB SeWA system helped identify severely ill patients using the five indicators, enabling timely inpatient care.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The integration of a quantified probability of death now offers an <\/span><i><span style=\"font-weight: 400;\">objective assessment<\/span><\/i><span style=\"font-weight: 400;\"> of risk, improving decision-making at the primary health level.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The team at ICMR-NIE noted that while the average time from diagnosis to hospital admission is one day in Tamil Nadu, <\/span><b>about 25% of severely ill patients face delays of 3\u20136 days<\/b><span style=\"font-weight: 400;\">. The new model is expected to reduce such delays.<\/span><\/li>\n<\/ul>\n<h2 style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Development and Validation of the Model<\/span><\/h2>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The model was developed using <\/span><b>data from nearly 56,000 TB patients<\/b><span style=\"font-weight: 400;\"> diagnosed across Tamil Nadu between July 2022 and June 2023.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">It was observed that <\/span><b>10\u201315%<\/b><span style=\"font-weight: 400;\"> of adults diagnosed with TB were classified as severely ill at the time of diagnosis.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The model&#8217;s validation has demonstrated that the five triage variables used in TN-KET are just as predictive of mortality risk as the comprehensive baseline variables in the national Ni-kshay TB portal.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">However, Ni-kshay variables typically take <\/span><b>up to three weeks<\/b><span style=\"font-weight: 400;\"> to populate, too late to act upon for high-risk patients. In contrast, the TN-KET system captures triage data within a day, ensuring faster action.<\/span><\/li>\n<\/ul>\n<h2 style=\"text-align: justify;\">Broader Public Health Impact<\/h2>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">All <\/span><b>2,800 public health facilities<\/b><span style=\"font-weight: 400;\"> in Tamil Nadu, from Primary Health Centres to Medical Colleges, currently use the TB SeWA application. The model supports:<\/span>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Real-time triaging<\/b><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Objective risk stratification<\/b><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><b>Timely hospital referrals<\/b><\/li>\n<\/ul>\n<\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The success of TN-KET and its associated tools has already contributed to <\/span><b>reduced loss in the TB care cascade<\/b><span style=\"font-weight: 400;\"> across two-thirds of Tamil Nadu\u2019s districts.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">This innovation serves as a replicable model for other Indian states, where early TB deaths remain a significant challenge despite free diagnosis and treatment.<\/span><\/li>\n<\/ul>\n<h2 style=\"text-align: justify;\">Global and National Context<\/h2>\n<ul>\n<li style=\"font-weight: 400; text-align: justify;\" aria-level=\"1\"><span style=\"font-weight: 400;\">According to the World Health Organisation, TB remains one of the top causes of death globally.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400; text-align: justify;\" aria-level=\"1\"><span style=\"font-weight: 400;\">India bears the <\/span><b>highest burden of TB in the world<\/b><span style=\"font-weight: 400;\">, with <\/span><b>two deaths every three minutes<\/b><span style=\"font-weight: 400;\">.<\/span><\/li>\n<li style=\"font-weight: 400; text-align: justify;\" aria-level=\"1\"><span style=\"font-weight: 400;\">A recent study titled <\/span><i><span style=\"font-weight: 400;\">\u201cTime to Death and Associated Factors among Tuberculosis Patients in Dangila Woreda, Ethiopia\u201d<\/span><\/i><span style=\"font-weight: 400;\"> identifies old age, low body weight, and TB\/HIV co-infection as significant predictors of early mortality.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400; text-align: justify;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Tamil Nadu\u2019s model, by addressing similar risk factors early, aligns with global recommendations for reducing TB deaths.<\/span><\/li>\n<\/ul>\n<p><b>Source:<\/b> <a href=\"https:\/\/www.thehindu.com\/sci-tech\/health\/tamil-nadu-first-to-integrate-predicted-possibility-of-tb-deaths-in-patients-to-its-state-tb-elimination-programme\/article69782992.ece\" target=\"_blank\" rel=\"nofollow noopener\"><span style=\"font-weight: 400;\">TH<\/span><\/a><span style=\"font-weight: 400;\"> | <\/span><a href=\"https:\/\/www.theweek.in\/wire-updates\/national\/2025\/07\/07\/lst2-health-tb-death-prediction-model.html\" target=\"_blank\" rel=\"nofollow noopener\"><span style=\"font-weight: 400;\">Week<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tamil Nadu becomes the first Indian state to implement a TB Death Prediction Model, integrated with its TB elimination programme to enhance early interventions and reduce mortality.<\/p>\n","protected":false},"author":21,"featured_media":53899,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[18],"tags":[60,1392,22,59],"class_list":{"0":"post-53882","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-upsc-mains-current-affairs","8":"tag-mains-articles","9":"tag-tb-death-prediction-model","10":"tag-upsc-current-affairs","11":"tag-upsc-mains-current-affairs","12":"no-featured-image-padding"},"acf":[],"_links":{"self":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/53882","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/users\/21"}],"replies":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/comments?post=53882"}],"version-history":[{"count":0,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/53882\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media\/53899"}],"wp:attachment":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media?parent=53882"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/categories?post=53882"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/tags?post=53882"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}