Abstract
Aim: Tuberculous meningitis (TBM) often causes cerebral infarction, but its predictive factors are not well understood. Methods: Patients aged ≥13 years admitted with TBM were enrolled prospectively. Cerebral infarction was diagnosed using magnetic resonance imaging. Results: Of 186 patients, 80 (43%) had infarction. Most infarctions were multiple and located in the cortical areas, basal ganglia and subcortical regions. Independent predictors of infarction at admission included high blood pressure, short illness duration, low Glasgow coma scale and hydrocephalus. Neuroimaging inflammation signs, cerebrospinal fluid analysis abnormalities and pre-existing cardiovascular risks did not predict infarction. In-hospital mortality was higher in TBM with infarction, particularly in those with advanced TBM (stage 3). Conclusion: Baseline parameters of raised intracranial pressure predict cerebral infarction in TBM.
Keywords: : cerebral infarction, mortality, predictor, prognosis, stroke, tuberculous meningitis
Plain language summary
Summary points.
Although tuberculous meningitis (TBM) is a major infectious cause of cerebral infarction in low-middle-income countries, its pathophysiology and predictive factors remain under-explored.
This prospective study aimed to identify baseline predictors of cerebral infarction in TBM and evaluate its impact on in-hospital outcomes.
Of the 186 patients enrolled (median age 33 years, 51.6% male), 43.0% (n = 80) had cerebral infarction.
The majority of infarctions (71.3%) were multiple, with the primary locations being cortical areas (30.3%), basal ganglia and thalamus (23.0%), other subcortical regions (22.4%), brainstem (13.2%), and cerebellum (11.2%).
Infarctions were predominantly associated with the perforators and cortical branches of the middle cerebral artery, superior cerebellar artery, and posterior cerebral artery.
Independent baseline predictors of infarction included elevated blood pressure at admission, shorter illness duration, low Glasgow coma scale, and hydrocephalus.
Neuroimaging features of inflammation (e.g., basal exudates, meningeal enhancement, or vasculitis), cerebrospinal fluid analysis abnormalities, and pre-existing cardiovascular risks did not predict infarction.
In-hospital mortality was higher in patients with infarction (20.0%) compared with those without (12.3%), with advanced TBM (stage 3) being a strong predictor of mortality among patients with infarction.
The study's major limitations include data from a single tertiary care center, absence of post-discharge follow-up, and limited utilization of magnetic resonance angiography and vessel wall imaging.
Our findings highlight the potential role of raised intracranial pressure in the pathogenesis of TBM-related infarction, as indicated by associations with elevated blood pressure at admission, hydrocephalus and low Glasgow coma scale.
1. Introduction
Tuberculous Meningitis (TBM) is the most severe form of tuberculosis (TB), contributing significantly to global morbidity and mortality, particularly in low- and middle-income countries (LMIC) [1,2]. It is a primary cause of intracranial infections in these regions, often leading to emergency department (ED) admissions [3]. The management of TBM is challenging due to its gradual onset, diagnostic complexities and frequent late-stage complications like hydrocephalus and cerebral infarction [1,4,5].
While many infectious pathogens are anecdotally linked to cerebral infarction, TBM presents a more robust association where causation is highly probable [3,6,7]. The incidence of infarction in TBM varies, reported between 13 and 57%, and is more common in advanced disease stages [7,8]. Unlike typical strokes, cerebral infarction in TBM often develops gradually and lacks typical focal neurological symptoms [8,9]. It primarily affects small- and medium-sized vessels (e.g., perforating arteries), leading to small or lacunar infarction, especially in the basal ganglia, thalamus and subcortical or deep white matter [10–12]. These strokes significantly contribute to the worse outcomes associated with TBM [7–9,13–18].
The pathophysiology of cerebral infarction in TBM is complex and not fully understood, involving factors such as vasculitis, intense inflammation, hypercoagulable states and direct infection of cerebral vessels [6,7,19]. This multifaceted nature contributes to the challenges in preventing and treating cerebrovascular complications in TBM. Currently, aspirin is the only known medication to reduce the incidence of new strokes in TBM; however, its efficacy in reducing overall mortality has not been established [20].
Despite its recognized importance, comprehensive studies on TBM-related infarction are particularly limited in LMIC, where TB is most prevalent, challenging the ability to conclude different population risks. Predicting stroke with readily available clinical and laboratory parameters at admission is crucial for patient triaging, guiding clinical decision-making and initiating appropriate interventions. Additionally, stratification of the TBM cases at high risk for stroke is essential for designing targeted trials for new treatments. The primary aim of our study was to identify baseline predictors of infarction in TBM patients at admission. Secondary objectives included determining the prevalence of cerebral infarction among TBM patients in North India and assessing its impact on short-term outcomes, specifically in-hospital mortality and length of hospital stay.
2. Methodology
2.1. Study design & oversight
This prospective cohort study was conducted from June 2022 to December 2023 at the medical ED, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India. Participants were eligible for enrolment if they were 13 years or older, diagnosed with TBM, and underwent magnetic resonance imaging (MRI) of the brain within 7 days of admission. Pregnant women and patients with co-infections involving TBM and other intracranial infections were excluded. Ethical approval was obtained from the Institutional Ethics Committee (intramural) of PGIMER, Chandigarh (no: INT/IEC/2022/SPL-1151). Informed consent was secured from all participants or their legally authorized representatives, with parental approval for participants under 18 years. The study did not receive any external financial support or funding.
2.2. Patient evaluation & data collection
Patients were comprehensively evaluated through detailed history-taking and clinical examination upon enrollment. Baseline computed tomography (CT) of the head was performed for all participants before lumbar puncture. Cerebrospinal fluid (CSF) analysis was extensive, including cell count and differentials, protein, glucose, Gram stain, bacterial culture, GeneXpert for TB with rifampicin sensitivity, India ink stain and cryptococcal antigen. Polymerase chain reaction testing for viral pathogens, malignant cytology and other CSF tests were conducted as indicated. Additional baseline investigations included complete blood counts, serum electrolytes, renal function tests, liver chemistry, human immunodeficiency virus (HIV) testing, chest X-ray, abdominal ultrasonography and electrocardiography.
All patients underwent MRI using 3T GE Discovery MR750w system, CT, USA, and 1.5T Siemens Healthcare Aera system, Erlangen, Germany, based on availability. The protocol included T1-weighted (without and with gadolinium contrast), T2-weighted, T2 fluid-attenuated inversion recovery (FLAIR), diffusion-weighted image (DWI), and susceptibility-weighted image sequences. Time-of-flight magnetic resonance angiography (3D TOF MRA) and high-resolution pre- and post-contrast T1 fat-saturated (3D T1 FS) vessel wall imaging sequences were acquired in addition to the routine pre- and post-contrast sequences as appropriate. In selected cases, a screening MRI of the whole spine was done to aid in TBM diagnosis.
Patients received treatment for TBM (four anti-tuberculosis drugs in the intensive phase and adjunctive dexamethasone) based on standard guidelines [21,22]. Follow-up continued until discharge or death during hospitalization. In-hospital outcomes were recorded as death or discharge and length of stay.
2.3. Definitions
According to national and World Health Organization guidelines for TB in India, the diagnosis of TBM (microbiologically confirmed or clinically diagnosed) was made [21,22]. Microbiologically confirmed cases were identified via CSF GeneXpert positivity. Clinically diagnosed TBM was based on compatible clinical and CSF features, characteristic neuroimaging findings, and/or evidence of active TB in other organs, with alternative diagnoses excluded [21]. A microbiologically confirmed diagnosis is considered a ‘definite case’ according to a proposed consensus TBM definition, while clinically diagnosed TBM is categorized as a ‘probable or possible diagnosis’ [23].
Cerebral infarction diagnosis via MRI involved identifying abnormal signal intensity in vascular territories, characterized by hypointensity on T1-weighted images and hyperintensity on T2-weighted/FLAIR sequences with diffusion restriction on DWI. Infarctions were categorized by location (cortical regions, basal ganglia, thalamus, subcortical regions, brainstem, cerebellum), number (single or multiple), size and vascular supply (e.g., perforating arteries, cortical branches). Cerebral vasculitis was diagnosed based on different patterns of gadolinium-enhanced MRA abnormalities, such as small segment narrowing or attenuated caliber of vessels, uniform narrowing of large segments, irregular beaded appearance of vessels or complete occlusion [24,25].
Older age was defined as ≥60 years, and adolescent age was defined as 12–19 years. Chronicity of TBM was categorized based on symptom duration at presentation: acute (<2 weeks), subacute (2–4 weeks) and chronic (>4 weeks). The British Medical Research Council (BMRC) staging system defined disease severity: Stage 1 – Glasgow coma scale (GCS) score of 15 with no deficits; Stage 2 – GCS score 9–14, minor deficits such as cranial nerve abnormalities; Stage 3 – GCS ≤8, seizures, major deficits such as paresis or stroke [26]. Coma was defined as GCS ≤8. Elevated or high blood pressure (BP) at admission was defined with systolic BP ≥130 mmHg and/or diastolic BP ≥80 mmHg [27]. CSF abnormalities were defined as pleocytosis (>10 cells/μl), neutrophilia (>50% neutrophils), hypoglycorrhachia (CSF glucose ≤45 mg/dl or CSF/plasma glucose ratio ≤0.5), and elevated protein (≥45 mg/dl). Laboratory abnormalities included anemia (hemoglobin <13 g/dl for males, <12 g/dl for females), thrombocytopenia (platelets <150,000/μl) and hyponatremia (sodium <135 mEq/l).
2.4. Statistical analysis
Statistical analyses were conducted using SPSS (version 25.0, IL, USA). Discrete variables were presented as frequency (n) and percentage (%). Continuous variables were described using mean and standard deviation (SD) or median and interquartile range (IQR) based on data normality. Categorical variables were compared using Chi-square or Fisher's exact test, while continuous variables were analyzed via unpaired Student t-test or Mann-Whitney U test. Multivariate logistic regression identified independent predictors of cerebral infarction in TBM, calculating odds ratio (OR) and 95% CI. Cox proportional hazard regression analyzed in-hospital mortality in patients with cerebral infarction, with hazard ratio (HR) and 95% CI calculated. All tests were two-sided, with p-value < 0.05 considered statistically significant.
3. Results
A total of 255 patients with suspected TBM were initially screened. Of these, 69 were excluded due to alternative diagnoses or the nonavailability of MRI, resulting in a study cohort of 186 (Supplementary Figure S1). The median age of patients was 33 years (range 13–85), with a balanced gender distribution of 96 males (51.6%) and 90 females (48.4%). Geographically, the majority were from Punjab (33.9%) and Haryana (26.9%), with others from Himachal Pradesh (12.4%), Uttar Pradesh (11.8%), Chandigarh (10.8%), Uttarakhand (3.2%) and Bihar (1.1%). Of 186 TBM cases, 126 (67.7%) were clinically diagnosed, and 60 (32.3%) were microbiologically confirmed. MRI of the brain was performed at a median of 3 days (IQR 2–5) of hospital admission.
3.1. Parameters of infarction
In our study, 80 patients (43.0%) were diagnosed with infarction. Bilateral cerebral involvement was slightly more prevalent (n = 43, 53.8%) than unilateral (n = 37, 46.3%). A majority, 71.3% (n = 57), had multiple infarctions, while 28.7% (n = 23) presented with a single infarction. Regarding location, 65.0% (n = 52) of infarctions occurred in the supratentorial area. The distribution of infarctions by major areas was as follows: cortical (30.3%, n = 46), basal ganglia and thalamus (23.0%, n = 35), other subcortical regions (22.4%, n = 34), brainstem (13.2%, n = 20), and cerebellum (11.2%, n = 17) (Table 1 & Figure 1). In the majority (87.5%, n = 75), acute or subacute infarctions were noted, and only five (12.5%) had chronic infarctions. Hemorrhagic transformation was documented in 11 infarctions.
Table 1. Locations of cerebral infarctions in tuberculous meningitis (n = 80).
| Infarction site | Frequency (%) |
|---|---|
| Basal ganglia | 23 (17.0%) |
| Frontal lobe | 19 (14.1%) |
| Temporal lobe | 19 (14.1%) |
| Thalamus | 17 (12.6%) |
| Cerebellum | 17 (12.6%) |
| Pons | 16 (11.9%) |
| Midbrain | 15 (11.1%) |
| Fronto-parietal area | 10 (7.4%) |
| Parieto-temporal area | 8 (5.9%) |
| Corpus callosum | 8 (5.9%) |
| Hippocampus | 7 (5.2%) |
| Internal capsule | 6 (4.4%) |
| Insular cortex | 5 (3.7%) |
| Parietal lobe | 5 (3.7%) |
| Occipital lobe | 4 (3.0%) |
| Centrum semiovale | 4 (3.0%) |
| Corona radiata | 3 (2.2%) |
| Periventricular area | 3 (2.2%) |
| Parieto-occipital area | 2 (1.5%) |
| Miscellaneous† | 10 (7.4) |
Miscellaneous sites (ten) included each one of the high posterior central gyrus, perisylvian area, basifrontal, basifrontal and medial temporal lobe, temporo-occipital area, external capsule, amygdala, uncus, fornix and medulla.
Figure 1.
The heatmap shows the distribution of infarctions in the five major cerebral areas, i.e., cortical, subcortical, basal ganglia and thalamus, brainstem and cerebellum. The diagonal cells represent the individual area frequency, and the off-diagonal cells represent the counts of the combinations of different areas.
All identified infarctions in our study were less than 3 cm in diameter. The majority of the infarctions were attributed to the involvement of perforating arteries (52.5%), followed by cortical branches (35.6%) and a combination of both perforating and cortical branches (11.9%). The middle cerebral artery (MCA) was the most common affected vessel (31.6%, n = 102), followed by the superior cerebellar artery (SCA) (22.6%, n = 73), the posterior cerebral artery (PCA) (19.5%, n = 63) and the anterior cerebral artery (12.1%, n = 39) (Table 2). Involvement of the anterior choroidal artery (7.4%, n = 24), basilar artery (4.9%, n = 16), anterior inferior cerebellar artery (1.2%, n = 4) and posterior inferior cerebellar artery (0.6%, n = 2) was observed less frequently. In terms of cerebral circulation territories, infarcts were predominantly located in the anterior circulation territory (41.3%, n = 33), posterior circulation (13.8%, n = 11) and areas supplied by both territories (45.0%, n = 36).
Table 2. The vascular involvement in cerebral infarction in tuberculous meningitis (n = 80).
| Vascular supply | Frequency (%) |
|---|---|
| Perforating arteries | 124 (52.5%) |
| MCA (M1 segment) | 22 (13.1%) |
| PCA (P1 segment) | 22 (13.1%) |
| Both PCA (P1 segment) and SCA | 21 (12.5%) |
| ACA | 17 (10.1%) |
| Basilar artery | 16 (9.5%) |
| SCA | 15 (8.9%) |
| Both MCA and ACA | 5 (3.0%) |
| Both SCA and AICA | 4 (2.4%) |
| Both PICA and SCA | 1 (0.6%) |
| PICA | 1 (0.6%) |
| Cortical branches | 84 (35.6%) |
| MCA | 37 (22.0%) |
| SCA | 20 (11.9%) |
| Both PCA and AChA | 11 (6.5%) |
| Both MCA and PCA | 7 (4.2%) |
| Both MCA and ACA | 4 (2.4%) |
| PCA | 2 (1.2%) |
| AChA | 2 (1.2%) |
| Both MCA and ACA | 1 (0.6%) |
| Combined cortical and perforator branches | 28 (11.9%) |
| MCA | 14 (8.3%) |
| SCA | 12 (7.1%) |
| ACA | 2 (1.2%) |
ACA: Anterior cerebral artery; AChA: Anterior choroidal artery; AICA: Anterior inferior cerebellar artery; MCA: Middle cerebral artery; PCA: Posterior cerebral artery; PICA: Posterior inferior cerebellar artery; SCA: Superior cerebellar artery.
3.2. Predictors of infarction
Tables 3 & 4 outline the baseline clinical and laboratory characteristics of our cohort, comparing TBM cases with and without infarction. Fever, altered mental status, and headache were the most common symptoms in both groups. The specific features of stroke, such as limb weakness, aphasia or cranial neuropathy, were less prevalent and did not predict infarction on MRI. Patients with infarction frequently had high BP at admission. However, only one out of 59 patients with elevated BP at admission had a history of pre-existing hypertension.
Table 3. Baseline clinical characteristics of the study cohort.
| Parameters | Total (n = 186) | TBM with infarction (n = 80) | TBM without infarction (n = 106) | P-value |
|---|---|---|---|---|
| Age (years) | 32.5 (23.75–47.25) | 33 (23.25–54.50) | 32 (23.75–44.25) | 0.406 |
| Older age | 23 (12.4%) | 12 (15.0%) | 11 (10.4%) | 0.343 |
| Adolescent age | 25 (13.4%) | 9 (11.3%) | 16 (15.1%) | 0.447 |
| Male gender | 96 (51.6%) | 45 (56.3%) | 51 (48.1%) | 0.272 |
| Pre-existing comorbidities | ||||
| Diabetes mellitus | 4 (2.2%) | 3 (3.8%) | 1 (0.9%) | 0.316 |
| Hypertension | 3 (1.6%)† | 1 (1.2%) | 2 (1.9%)† | 1.000 |
| Persons living with HIV | 12 (6.5%) | 4 (5.0%) | 8 (7.5%) | 0.484 |
| History of household contact with active TB case | 39 (21.0%) | 19 (23.8%) | 20 (18.9%) | 0.418 |
| Past history of TB | 7 (3.8%) | 3 (3.8%) | 4 (3.8%) | 1.000 |
| Tobacco smoking | 45 (24.2%) | 19 (23.8%) | 26 (24.5%) | 0.902 |
| Duration of smoking (years) | 10 (5–11.5) | 10 (5–13) | 10 (5–11.25) | 0.981 |
| Chronic alcohol consumption | 46 (24.7%) | 21 (26.3%) | 25 (23.6%) | 0.677 |
| Duration of alcohol consumption (years) | 10 (7.75–20) | 10 (7.5–20) | 10 (7.5–15) | 0.710 |
| Duration of illness before presentation (days) | 25 (12–30) | 20 (10–30) | 30 (15–30) | 0.029 |
| Acute TBM | 48 (25.8%) | 25 (31.3%) | 23 (21.7%) | 0.140 |
| Subacute TBM | 47 (25.3%) | 21 (26.3%) | 26 (24.5%) | 0.789 |
| Chronic TBM | 91 (48.9%) | 34 (42.5%) | 57 (53.8%) | 0.128 |
| Fever | 168 (90.3%) | 69 (86.3%) | 99 (93.4%) | 0.103 |
| Altered mental status | 137 (73.7%) | 66 (82.5%) | 71 (67.0) | 0.017 |
| Headache | 91 (48.9%) | 36 (45.0%) | 55 (51.9%) | 0.352 |
| Vomiting | 30 (16.1%) | 8 (10.0%) | 22 (20.8%) | 0.048 |
| Limb weakness or aphasia | 11 (5.9%) | 6 (7.5%) | 5 (4.7%) | 0.534 |
| Seizure | 10 (5.4%) | 3 (3.8%) | 7 (6.6%) | 0.519 |
| Cranial nerve abnormalities‡ | 7 (3.8%) | 2 (2.5%) | 5 (4.7%) | 0.701 |
| Neck rigidity | 160 (86.0%) | 69 (86.3%) | 91 (85.8%) | 0.938 |
| Systolic blood pressure (mmHg) | 115.4 ± 10.0 | 116.9 ± 12.2 | 114.2 ± 7.9 | 0.070 |
| Diastolic blood pressure (mmHg) | 73.2 ± 7.2 | 75.0 ± 8.0 | 71.9 ± 6.4 | 0.003 |
| Elevated blood pressure | 59 (31.7%) | 34 (42.5%) | 25 (23.6%) | 0.006 |
| Pulse rate (per min) | 94.3 ± 10.8 | 93.8 ± 10.5 | 94.6 ± 11.1 | 0.636 |
| Respiratory rate (per min) | 19.5 ± 1.4 | 19.5 ± 1.7 | 19.5 ± 1.2 | 0.941 |
| Glasgow coma scale | 11 (10–15) | 11 (9.25–13) | 12 (10–15) | 0.001 |
| Coma | 21 (11.3%) | 12 (15.0%) | 9 (8.5%) | 0.165 |
| BMRC stage 1 | 17 (9.1%) | 2 (2.5%) | 15 (14.2%) | 0.019 |
| BMRC stage 2 | 134 (72.0%) | 60 (75.0%) | 74 (69.8%) | |
| BMRC stage 3 | 35 (18.8%) | 18 (22.5%) | 17 (16.0%) |
Values are given as n (%), mean ± SD, or median (IQR).
One patient had chronic kidney disease.
Cranial nerve abnormalities included involvement of 3rd (n = 3), 6th (n = 2) and 7th (n = 1) cranial nerves.
BMRC: British Medical Research Council; HIV: Human immunodeficiency virus; TB: Tuberculosis; TBM: Tuberculous meningitis.
Table 4. Baseline laboratory parameters of the patients with tuberculous meningitis.
| Parameters | Total (n = 186) | TBM with infarction (n = 80) | TBM without infarction (n = 106) | P-value |
|---|---|---|---|---|
| Hemoglobin (g/dl) | 11.1 ± 1.8 | 11.1 ± 2.0 | 11.1 ± 1.7 | 0.919 |
| Anemia | 48 (25.8%) | 24 (30.0%) | 24 (22.6%) | 0.256 |
| Total leukocyte count (per μl) | 10200 (7275–13125) | 10155 (7200–12975) | 10250 (7275–13517.5) | 0.824 |
| Platelet count (×103 per μl) | 244.0 (166.25–318.0) | 240.0 (168.5–322.25) | 245.5 (163.75–315.25) | 0.724 |
| Thrombocytopenia | 37 (19.9%) | 17 (21.3%) | 20 (18.9%) | 0.687 |
| Serum sodium (mEq/l) | 133.4 ± 6.1 | 134.4 ± 6.5 | 132.7 ± 5.6 | 0.055 |
| Hyponatremia | 115 (61.8%) | 48 (60.0%) | 67 (63.2%) | 0.656 |
| Serum potassium (mEq/l) | 3.9 ± 0.6 | 3.9 ± 0.6 | 3.9 ± 0.6 | 0.836 |
| Serum urea (mg/dl) | 31 (22–49) | 32 (20.25–52.5) | 28 (22.75–46.5) | 0.956 |
| Serum creatinine (mg/dl) | 0.6 (0.5–0.9) | 0.6 (0.4–0.9) | 0.6 (0.5–0.9) | 0.809 |
| Total serum bilirubin (mg/dl) | 0.6 (0.4–0.9) | 0.6 (0.4–0.9) | 0.6 (0.4–0.9) | 0.751 |
| Conjugated bilirubin (mg/dl) | 0.2 (0.1–0.4) | 0.2 (0.1–0.5) | 0.2 (0.1–0.4) | 0.236 |
| Aspartate transaminase (U/l) | 39 (24–70) | 45 (29.25–72.75) | 36 (21.75–62.62) | 0.054 |
| Alanine transaminase (U/l) | 36 (20–74.25) | 41.5 (27–76.5) | 33 (19–71) | 0.164 |
| Chest X-ray findings suggestive of TB† | 40 (21.5%) | 18 (22.5%) | 22 (20.8%) | 0.774 |
| Cerebrospinal fluid analysis | ||||
| Total cell count (per μl) | 164 (65.75–352.75) | 167 (80.75–368) | 160.5 (47.75–352) | 0.499 |
| Pleocytosis | 176 (94.6%) | 74 (92.5%) | 102 (96.2%) | 0.265 |
| Lymphocyte (%) | 80 (60–90) | 80 (52.3–91.5) | 80 (62.3–90.0) | 0.589 |
| Neutrophils (%) | 20 (10–40.25) | 25 (10 –50) | 20 (9.87–37.87) | 0.293 |
| Neutrophilic pleocytosis | 39 (21.0%) | 21 (26.3%) | 18 (17.0%) | 0.124 |
| Protein (mg/dl) | 190.0 (125.0–287.0) | 194.0 (131.0–284.95) | 190.0 (124.75–294.25) | 0.856 |
| Elevated protein | 184 (98.9%) | 80 (100.0%) | 104 (98.1%) | 0.217 |
| Glucose (mg/dl) | 35.5 (20.0–60.0) | 36.0 (20.2–62.0) | 35.0 (19.0–57.0) | 0.569 |
| Hypoglycorrhachia | 128 (68.8%) | 52 (65.0%) | 76 (71.1%) | 0.329 |
| GeneXpert positivity‡ | 60 (32.3%) | 28 (35.0%) | 32 (30.2%) | 0.487 |
Values are given as n (%), mean ± SD, or median (IQR).
Chest X-ray abnormalities (40) included miliary mottling (13), diffuse reticulonodular opacities in both lungs (12), upper lobe consolidation or cavitation (11) and middle or lower lobe consolidation or cavitation (four).
GeneXpert rifampicin sensitivity results were sensitive (57), resistance (one) and indeterminant (two).
TBM: Tuberculous meningitis.
In our study, MRI brain was abnormal in 97.3% (n = 181), with meningeal enhancement, tuberculoma, and hydrocephalus being more common than infarction (Table 5 & Supplementary Figure S2). Infarctions occurred more frequently in patients with hydrocephalus; however, the presence of basal exudates, pachymeningitis, meningeal enhancement, and tuberculoma were not associated with cerebral infarction. Out of 97 cases of tuberculoma, 92 (94.8%) had multiple (>1) lesions. In five cases, there was an associated tuberculous abscess, and four cases had associated calcified granuloma. Among the 54 patients who underwent MRA, vasculitis was detected in 22. Vessel wall imaging, available in six cases, indicated circumferential vessel wall enhancement in four. Baseline CT head showed abnormalities in 57 cases (30.6%), predominantly hydrocephalus (n = 45, 24.2%), followed by infarction (n = 8, 4.3%) and tuberculoma (n = 4, 2.2%). Hydrocephalus on CT was associated with infarction on MRI.
Table 5. Neuroimaging features of tuberculous meningitis with and without infarction.
| Parameters | Total (n = 186) | TBM with infarction (n = 80) | TBM without infarction (n = 106) | p-value |
|---|---|---|---|---|
| MRI brain | ||||
| Meningeal enhancement | 155 (83.3%) | 68 (85.0%) | 87 (82.1%) | 0.596 |
| Pachymeningitis | 51 (27.4%) | 24 (30.0%) | 27 (25.5%) | 0.493 |
| Basal exudates | 19 (10.2%) | 10 (12.5%) | 9 (8.5%) | 0.371 |
| Tuberculoma | 97 (53.3%) | 42 (53.2%) | 55 (53.4%) | 0.975 |
| Hydrocephalus | 81 (43.5%) | 43 (53.8%) | 38 (35.8%) | 0.015 |
| Non-communicating | 68 (84.0%) | 35 (81.4%) | 33 (86.8%) | 0.505 |
| Communicating | 13 (16.0%) | 8 (18.6%) | 5 (13.2%) | |
| Magnetic resonance angiography (n = 54) | ||||
| Vasculitis† | 22/54 (40.7%) | 13/29 (44.8%) | 9/25 (36.0%) | 0.510 |
| Vessel wall imaging (n = 6) | ||||
| Circumferential vessel wall enhancement‡ | 4/6 (66.7%) | 2/3 (66.7%) | 2/3 (66.7%) | 1.000 |
| MRI spine (n = 76) | ||||
| Spinal tuberculosis§ | 41/76 (53.9%) | 17/31 (54.8%) | 24/45 (53.3%) | 0.897 |
| Computed tomography head at admission | ||||
| Hydrocephalous | 45 (24.2%) | 27 (33.8%) | 18 (17.0%) | 0.008 |
Vascular involvement included middle cerebral artery (18; bilateral 16, unilateral 2), bilateral posterior cerebral artery (8), anterior cerebral artery (7; bilateral 6, unilateral 1) and bilateral supra-clinoid internal carotid artery (5).
Vascular involvement included middle cerebral artery (4; bilateral 3, unilateral 1), bilateral posterior cerebral artery (1), bilateral anterior cerebral artery (1) and bilateral supra-clinoid internal carotid artery (1).
Spinal tuberculosis (41) features included arachnoiditis (25, 43.9%), leptomeningeal enhancement (14, 24.6%), spondylodiscitis (10, 17.5%), tuberculoma (4, 7.0%) and myelitis (4, 7.0%).
MRI: Magnetic resonance imaging; TBM: Tuberculous meningitis.
The independent predictors for cerebral infarction on multivariate regression analysis were elevated BP at presentation, shorter duration of illness, low GCS scores and hydrocephalus (Table 6).
Table 6. Multivariate logistic regression for predicting cerebral infarction in patients with tuberculous meningitis at admission.
| Parameter | OR (95% CI) | p-value |
|---|---|---|
| High blood pressure | 2.303 (1.160–4.570) | 0.017 |
| Shorter duration of illness | 0.987 (0.975–0.999) | 0.031 |
| Glasgow coma scale | 0.862 (0.763–0.973) | 0.017 |
| Hydrocephalous | 0.470 (0.249–0.888) | 0.020 |
| BMRC stage 3 | 1.409 (0.544–3.646) | 0.480 |
BMRC: British Medical Research Council.
3.3. In-hospital outcomes
In-hospital mortality was 15.6% (n = 29), which was higher in patients with infarction (n = 16, 20.0%) compared with those without (n = 13, 12.3%), although this was not statistically significant (p = 0.150). The median hospital stay of the study patients was 9 days (IQR 5.75–14) and was similar in patients with and without infarction, i.e., nine (IQR 6–13.5) vs nine (IQR 5–15), p = 0.787. Among TBM patients with infarction, BMRC stage 3 and low GCS at admission predicted in-hospital mortality on univariate Cox-regression analysis (Table 7). However, multivariate Cox-regression analysis identified only BMRC stage 3 as an independent predictor of mortality (HR: 2.622, 95% CI: 1.114–6.172; p = 0.027).
Table 7. Univariate Cox-regression analysis of baseline factors predicting in-hospital mortality in patients with tuberculous meningitis and cerebral infarction.
| Parameters | Survived (n = 64) | Died (n = 16) | HR (95% Cl) | P-value |
|---|---|---|---|---|
| Age (years) | 31 (23–49.5) | 47.5 (24.25–60) | 0.990 (0.976–1.004) | 0.168 |
| Duration of illness (days) | 20 (7–30) | 30 (16.25–30) | 0.998 (0.988–1.007) | 0.625 |
| Fever | 55 (85.9%) | 14 (87.5%) | 0.843 (0.413–1.720) | 0.639 |
| Altered mental status | 55 (85.9%) | 11(68.8%) | 0.940 (0.462–1.911) | 0.864 |
| Glasgow coma scale | 11 (10–13) | 10 (7.25–11.75) | 1.092 (1.009–1.182) | 0.028 |
| Elevated blood pressure | 25 (39.1%) | 9 (56.3%) | 0.906 (0.544–1.510) | 0.704 |
| British Medical Research Council stage 3 | 11 (17.2%) | 7 (43.8%) | 2.827 (1.425–5.608) | 0.003 |
| Cerebrospinal fluid analysis | ||||
| Total cell count (per μl) | 161 (72.75–444) | 195.5 (103.5–296) | 1.000 (1.000–1.001) | 0.142 |
| Neutrophils (%) | 25 (11.25–51.5) | 20 (6.25–39.75) | 0.999 (0.988–1.010) | 0.814 |
| Protein (mg/dl) | 201.5 (131–284.1) | 180 (119–294) | 1.000 (1.000–1.001) | 0.184 |
| Glucose (mg/dl) | 36 (22–62) | 34 (17.5–66) | 1.004 (0.995–1.013) | 0.397 |
| GeneXpert positivity | 20 (31.3%) | 8 (50.0%) | 1.247 (0.732–2.124) | 0.418 |
| Magnetic resonance imaging brain | ||||
| Meningeal enhancement | 55 (85.9%) | 13 (81.3%) | 0.595 (0.290–1.219) | 0.156 |
| Basal exudates | 9 (14.1%) | 1 (6.3%) | 0.874 (0.430–1.778) | 0.710 |
| Tuberculoma | 32 (50.0%) | 11 (68.8%) | 0.825 (0.501–1.361) | 0.452 |
| Hydrocephalus | 35 (54.7%) | 8 (50.0%) | 0.807 (0.489–1.333) | 0.403 |
| Location of infarction | ||||
| Cortical area | 36 (56.3%) | 10 (62.5%) | 1.420 (0.856–2.354) | 0.174 |
| Basal ganglia and thalamus | 27 (42.2%) | 8 (50.0%) | 1.014 (0.612–1.680) | 0.957 |
| Subcortical area | 25 (39.1%) | 9 (56.3%) | 1.214 (0.729–2.021) | 0.456 |
| Brainstem | 17 (26.6%) | 3 (18.8%) | 1.025 (0.579–1.814) | 0.933 |
| Cerebellum | 16 (25.0%) | 1 (6.3%) | 0.940 (0.524–1.686) | 0.836 |
| Supratentorial area | 39 (60.9%) | 13 (81.3%) | 1.162 (0.694–1.945) | 0.568 |
| Bilateral cerebral involvement | 33 (51.6%) | 10 (62.5%) | 1.150 (0.697–1.897) | 0.584 |
| Both anterior and posterior circulation involvement | 12 (48.0%) | 1 (25.0%) | 1.126 (0.676–1.878) | 0.648 |
| Multiple infarct | 45 (70.3%) | 12 (75.0%) | 1.268 (0.737–2.181) | 0.391 |
| Vasculitis on magnetic resonance angiography | 12/25 (18.8%) | 1/4 (6.3%) | 1.295 (0.556–3.016) | 0.549 |
Values are given as n (%) or median (IQR).
4. Discussion
This extensive prospective study underscores the significant prevalence of cerebral infarction in patients with TBM in India. Infarctions were predominantly located in the cortical areas, basal ganglia, thalamus and subcortical areas, with the perforating arteries and cortical branches of the MCA, SCA and PCA being commonly affected. Key baseline predictors of cerebral infarction included elevated BP at admission, shorter duration of illness, low GCS, and the presence of hydrocephalus. The in-hospital mortality rate was higher in patients with infarction.
TBM is a leading infectious cause of cerebral infarction in LMIC, reflected by a high incidence of 43% in our study. The infarctions were predominantly acute or subacute, indicating their development during the active phase of TBM. Correlating with recent observations, infractions were typically small, resulting from the involvement of perforating or terminal cortical branches of major cerebral arteries such as the MCA, SCA and PCA [10–12,28,29]. Our findings align with the vascular supply classification for TBM-related infarcts, diverging from earlier studies that adhered to a zonal classification and primarily identified infarctions in the TB zone (i.e., basal ganglia, internal capsule and thalamus) [30]. These earlier studies, often based on CT scans, offered less sensitivity and specificity compared with more recent MRI-based research, which shows a broader distribution of infarction locations in variable frequencies [10–12,28,29].
Contrary to previous studies, we did not find a significant correlation between infarction and basal exudates, pachymeningitis, meningeal enhancement or granuloma formation [1,12,16,17,21–33]. This observation suggests that the presence of these inflammatory signs may not be directly associated with the risk of infarction in TBM. Furthermore, while vasculitis has been traditionally considered as a potential factor in TBM-related infarction in the previous reports, including neuropathological autopsy series, our data align with recent findings that do not support this association [10,11,28,34]. However, given that MRA was available in only 29% of cases, our study cannot fully exclude the role of vasculitis in the pathogenesis of infarction in TBM, highlighting the need for further research. Overall, our results suggest alternative mechanisms for cerebral infarction in TBM, possibly a non-inflammatory ischemic process.
In our cohort, the presence of elevated BP at admission was a strong predictor of infarction. This clinical sign might indicate increased intracranial pressure (ICP), a common complication in TBM stages 2 and 3, leading to reduced cerebral perfusion pressure and subsequent ischemic damage. The perforating arteries and terminal cortical branches, which are primarily involved in TBM-related infarctions, are particularly susceptible to the effects of increased ICP. Moreover, elevated BP at presentation may also reflect a systemic response to the severe infection, potentially exacerbating cerebrovascular stress and increasing the risk of infarction. It is important to note that elevated BP measurements at admission may not necessarily indicate chronic hypertension but rather an acute physiological response to the underlying disease process. The role of ICP is further highlighted by the association between hydrocephalus and infarction in our cohort. This finding is consistent with prior studies suggesting that the stretching of vessels caused by hydrocephalus is a contributing factor to infarction in TBM [16,17,31]. Additionally, a lower GCS at admission strongly predicted infarction, possibly indicating raised ICP or advanced disease stages with preexisting cerebral complications.
Advanced MRI techniques such as arterial spin labeling (ASL) and diffusion tensor imaging (DTI) can offer valuable insights into the pathogenesis of infarction in TBM, particularly in relation to raised ICP [35,36]. ASL perfusion imaging quantifies cerebral blood flow, a key factor in determining cerebral perfusion pressure and ICP. This functional MRI modality has been effective in identifying areas of reduced cerebral perfusion in regions prone to infarction in TBM [35]. On the other hand, DTI evaluates the microstructural integrity of brain tissue, enabling the detection and monitoring of the presence and evolution of infarcts in TBM [35]. Future studies combining ASL and DTI with conventional MRI might further delineate the complex interplay between cerebral perfusion and raised ICP in TBM and enhance our understanding of the mechanisms underlying infarction.
The association between a shorter duration of illness before admission and a higher risk of infarction suggests that rapid disease progression may predispose to severe complications. Alternatively, it might indicate that patients with more aggressive disease presentations are brought to ED earlier due to the severity of their symptoms, which could be associated with infarctions. Overall, this observation highlights the importance of early diagnosis and management of TBM, as well as increased vigilance for infarction to improve outcomes in such cases.
We observed that preexisting cardiovascular risk factors did not show a significant correlation with infarction, in contrast with previous studies that proposed atherosclerosis as an essential contributing cause of TBM-related infarction [10,17,18,33,37]. Additionally, unlike earlier studies, laboratory abnormalities like neutrophilic pleocytosis and hyponatremia did not indicate infarction in our cohort [32,33,38,39]. Notably, while TBM is recognized as a significant cause of stroke in people living with HIV, our findings, consistent with several other studies, indicate that the incidence of infarction in TBM patients is similar, irrespective of HIV status [10,17,40,41].
Cerebral infarction in TBM is a serious complication, often leading to reduced survival and increased neurological disability. While our study suggested higher mortality rates in patients with infarction, this was not statistically significant, possibly due to limited follow-up duration. A key finding was the strong association of BMRC stage 3 with mortality in patients with infarction, echoing past studies [29]. This underscores the urgent need for intensive neurocritical care in patients with advanced TBM and high risk of infarction admitted to the ED. Notably, infarction-specific factors like location or number did not predict mortality.
Our study has several limitations. First, being conducted at a single academic institution, our findings may not fully represent the broader TBM population. Second, we did not assess dyslipidemia, a known risk factor for stroke. Third, MRA and vessel wall imaging could only be performed in a limited number of patients due to logistic and technical challenges in the ED setting. Consequently, the association between cerebral infarction and vasculitis requires further exploration with a larger sample size. Fourth, patients were scanned in 3T and 1.5T MRI scanners, based on availability of imaging slots in the ED setting. While 3T MRIs can potentially provide more detailed images, the clinical relevance of this additional detail in diagnosing TBM and identifying infarction is not significant. Fifth, the number of hydrocephalus cases detected on initial CT scans at admission was lower compared with MRI performed within 7 days. This discrepancy is primarily due to MRI being a more sensitive diagnostic tool, and it is possible that in some cases, hydrocephalus developed within the first 7 days after admission [42]. Sixth, while CSF GeneXpert showed adequate sensitivity, the absence of mycobacterial culture might have resulted in fewer confirmed TBM cases. Finally, the lack of post-discharge follow-up limited our ability to evaluate long-term neurological outcomes and survival.
5. Conclusion
TBM is commonly associated with infarction, which manifests as small and multiple infarcts, predominantly in the cortical areas, basal ganglia, thalamus, and subcortical areas. Our study highlights that baseline parameters indicative of raised ICP, such as elevated BP at admission, low GCS, and the presence of hydrocephalous, are predictive of TBM-related infarction. Notably, neuroimaging or CSF features of inflammation or pre-existing cardiovascular risks may not strongly predict infarction. The presence of infarction in advanced TBM is associated with high mortality.
Supplementary Material
Acknowledgments
Authors thank Mrs Sunaina Verma for her help in statistics.
Supplemental material
Supplemental data for this article can be accessed at https://doi.org/10.1080/17520363.2024.2347194
Author contributions
A Aggrohiaa: data curation (main), drafted the manuscript (supporting). V Bhatia: data curation (supporting), revised the manuscript (supporting). A Saroch: data curation (supporting). AK Pannu: conceived the idea (main), data curation (supporting), methodology (main), drafted the manuscript (main), revised the manuscript (main), supervised the project (main).
Financial disclosure
The authors have no financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Competing interests disclosure
The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, stock ownership or options and expert testimony.
Writing disclosure
No writing assistance was utilized in the production of this manuscript.
Ethical conduct of research
The authors state that they have obtained appropriate institutional review board approval (No.: INT/IEC/2022/SPL-1151) and/or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations.
In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.
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