Dietary glycemic index and glycemic load predict longitudinal change in glycemic and cardio-metabolic biomarkers among old diabetic adults living in a resource-poor country.

This study aims to investigate longitudinal associations between the dietary glycemic index (GI) and glycemic load (GL) and changes in glycemic and cardio-metabolic outcomes. A 28-month retrospective cohort study included 110 Vietnamese diabetic patients, collecting their dietary GI and GL values along with blood biochemical data from baseline 24-h dietary recall and medical records. Latent class growth modelling identified three distinct HbA1c trajectories during the follow-up period, with 51% of patients achieving good glycemic control. The adjusted linear mixed-effect model showed that 1 unit increase in logarithms in dietary GL was associated with a 0.14% increase in the log-HbA1c. Among poorly controlled diabetic patients, baseline GL values were positively correlated with increases in HbA1c; GI showed effects on changes in fasting plasma glucose and the triglyceride-glucose (TyG) index. No significant association was observed in patients with good glycemic control.

The effects of dietary macronutrient composition on resting energy expenditure following active weight loss: A systematic review and meta-analysis.

A systematic review and meta-analysis was conducted to evaluate the relative effectiveness of different dietary macronutrient patterns on changes in resting energy expenditure (REE) in relation to weight loss, categorized as minimal (<5%) and moderate to high (>5%). Changes in REE were assessed using a DerSimonian and Laird random-effects meta-analysis. A diet lower in carbohydrates (CHO) or higher in fat and protein was associated with smaller reductions in REE, with these trends being more pronounced among participants who experienced moderate to high weight loss. Adjusted meta-regression analysis indicated that, within the participants who experienced moderate to high weight loss, each 1% increase in CHO intake was associated with a reduction of 2.30 kcal/day in REE (95% CI: -4.11 to -0.47, p = 0.013). In contrast, a 1% increase in protein and fat intake was correlated with an increase in REE by 3.00 (95% confidence interval [CI] [1.02, 5.07], p = 0.003) and 0.5 (95% CI [-2.43, 3.41], p = 0.740) kcal/day, respectively. No significant associations were found among participants who experienced minimal weight loss. These findings indicate that, under a caloric deficit, the impact of dietary macronutrient composition on REE may vary depending on the degree of weight loss and individual metabolic responses.

Multiple Complicated Concurrent Hernias in a Single Patient: A Case Report.

Multiple complicated concurrent hernias with obturator hernia and paraesophageal hernia unusually occur in clinical settings. The obturator hernias belong to a rare pelvic hernia that accounts for a minority of all abdominal hernias. Besides, paraesophageal hernias occur commonly in elderly female patients. Clinical manifestations of these hernias are usually unspecific and the diagnosis is based on computed tomography (CT). In this paper, we presented a case of multiple complicated hernias in an 81-year-old woman. She was admitted to our hospital due to intestinal obstruction that was caused by a simultaneous obturator and paraesophageal hernia. She was successfully treated by laparoscopic hernia repair. Postoperative progression was favorable. She was then discharged from the hospital after four hospital days.

Pituitary Suppression with Gonadotropin-Releasing Hormone Agonist Prior to Artificial Endometrial Preparation in Frozen-Thawed Embryo Transfer Cycles: A Systematic Review and Meta-Analysis of Different Protocols and Infertile Populations.

This study investigates the effect of GnRHa pretreatment on pregnancy outcomes in artificial endometrial preparation for frozen-thawed embryo transfer (AC-FET) cycles. A systematic review of English language studies published before 1 September 2022, was conducted, excluding conference papers and preprints. Forty-one studies involving 43,021 participants were analyzed using meta-analysis, with a sensitivity analysis ensuring result robustness. The study found that GnRHa pretreatment generally improved the clinical pregnancy rate (CPR), implantation rate (IR), and live birth rate (LBR). However, discrepancies existed between randomized controlled trials (RCTs) and observational studies; RCTs showed no significant differences in outcomes for GnRHa-treated cycles. Depot GnRHa protocols outperformed daily regimens in LBR. Extended GnRHa pretreatment (two to five cycles) significantly improved CPR and IR compared to shorter treatment. Women with polycystic ovary syndrome (PCOS) saw substantial benefits from GnRHa pretreatment, including improved CPR and LBR and reduced miscarriage rates. In contrast, no significant benefits were observed in women with regular menstruation. More rigorous research is needed to solidify these findings.

Distinctive antibody responses to Mycobacterium tuberculosis in pulmonary and brain infection.

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), remains a global health burden. While Mtb is primarily a respiratory pathogen, it can spread to other organs, including the brain and meninges, causing TB meningitis (TBM). However, little is known about the immunological mechanisms that leads to differential disease across organs. Attention has focused on differences in T cell responses in the control of Mtb in the lungs, but emerging data point to a role for antibodies, as both biomarkers of disease control and as antimicrobial molecules. Given an increasing appreciation for compartmentalized antibody responses across the blood brain barrier, here we characterized the antibody profiles across the blood and brain compartments during TBM, and determined whether Mtb-specific humoral immune responses differed between Mtb infection of the lung (pulmonary TB) and TBM. Using a high throughput systems serology approach, we deeply profiled the antibody responses against 10 different Mtb antigens, including lipoarabinomannan (LAM) and purified protein derivative (PPD), in HIV-negative adults with pulmonary TB (n=10) vs TBM (n=60). Antibody studies included analysis of immunoglobulin isotypes (IgG, IgM, IgA) and subclass levels (IgG1-4), the capacity of Mtb-specific antibodies to bind to Fc receptors or C1q, and to activate innate immune effectors functions (complement and NK cells activation, monocyte or neutrophil phagocytosis). Machine learning methods were applied to characterize serum and CSF responses in TBM, identify prognostic factors associated with disease severity, and define the key antibody features that distinguish TBM from pulmonary TB. In individuals with TBM, we identified CSF-specific antibody profiles that marked a unique and compartmentalized humoral response against Mtb, characterized by an enrichment of Mtb-specific antibodies able to robustly activate complement and drive phagocytosis by monocytes and neutrophils, all of which were associated with milder TBM severity at presentation. Moreover, individuals with TBM exhibited Mtb-specific antibodies in the serum with an increased capacity to activate phagocytosis by monocytes, compared to individuals with pulmonary TB, despite having lower IgG titers and Fcγ receptors (FcγR)-binding capacity. Collectively, these data point to functionally divergent humoral responses depending on the site of infection (i.e. lungs vs brain), and demonstrate a highly compartmentalized Mtb-specific antibody response within the CSF during TBM. Moreover, our results suggest that phagocytosis- and complement-mediating antibodies may promote attenuated neuropathology and milder TBM disease.

A novel diagnostic model for tuberculous meningitis using Bayesian latent class analysis.

BACKGROUND: Diagnosis of tuberculous meningitis (TBM) is hampered by the lack of a gold standard. Current microbiological tests lack sensitivity and clinical diagnostic approaches are subjective. We therefore built a diagnostic model that can be used before microbiological test results are known. METHODS: We included 659 individuals aged [Formula: see text] years with suspected brain infections from a prospective observational study conducted in Vietnam. We fitted a logistic regression diagnostic model for TBM status, with unknown values estimated via a latent class model on three mycobacterial tests: Ziehl-Neelsen smear, Mycobacterial culture, and GeneXpert. We additionally re-evaluated mycobacterial test performance, estimated individual mycobacillary burden, and quantified the reduction in TBM risk after confirmatory tests were negative. We also fitted a simplified model and developed a scoring table for early screening. All models were compared and validated internally. RESULTS: Participants with HIV, miliary TB, long symptom duration, and high cerebrospinal fluid (CSF) lymphocyte count were more likely to have TBM. HIV and higher CSF protein were associated with higher mycobacillary burden. In the simplified model, HIV infection, clinical symptoms with long duration, and clinical or radiological evidence of extra-neural TB were associated with TBM At the cutpoints based on Youden's Index, the sensitivity and specificity in diagnosing TBM for our full and simplified models were 86.0% and 79.0%, and 88.0% and 75.0% respectively. CONCLUSION: Our diagnostic model shows reliable performance and can be developed as a decision assistant for clinicians to detect patients at high risk of TBM. Diagnosis of tuberculous meningitis is hampered by the lack of gold standard. We developed a diagnostic model using latent class analysis, combining confirmatory test results and risk factors. Models were accurate, well-calibrated, and can support both clinical practice and research.

Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Using Artificial Intelligence: A Systematic Review and Meta-Analysis.

RATIONALE AND OBJECTIVES: Recent advancements in artificial intelligence (AI) render a substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction in non-small cell lung cancer (NSCLC). We aimed to evaluate the performance and quality of AI algorithms that use radiomics features in predicting EGFR mutation status in patient with NSCLC. MATERIALS AND METHODS: We searched PubMed (Medline), EMBASE, Web of Science, and IEEExplore for studies published up to February 28, 2022. Studies utilizing an AI algorithm (either conventional machine learning [cML] and deep learning [DL]) for predicting EGFR mutations in patients with NSLCL were included. We extracted binary diagnostic accuracy data and constructed a bivariate random-effects model to obtain pooled sensitivity, specificity, and 95% confidence interval. This study is registered with PROSPERO, CRD42021278738. RESULTS: Our search identified 460 studies, of which 42 were included. Thirty-five studies were included in the meta-analysis. The AI algorithms exhibited an overall area under the curve (AUC) value of 0.789 and pooled sensitivity and specificity levels of 72.2% and 73.3%, respectively. The DL algorithms outperformed cML in terms of AUC (0.822 vs. 0.775) and sensitivity (80.1% vs. 71.1%), but had lower specificity (70.0% vs. 73.8%, p-value < 0.001) compared to cML. Subgroup analysis revealed that the use of positron-emission tomography/computed tomography, additional clinical information, deep feature extraction, and manual segmentation can improve diagnostic performance. CONCLUSION: DL algorithms can serve as a novel method for increasing predictive accuracy and thus have considerable potential for use in predicting EGFR mutation status in patient with NSCLC. We also suggest that guidelines on using AI algorithms in medical image analysis should be developed with a focus on oncologic radiomics.

Consistency and Accuracy of Artificial Intelligence for Providing Nutritional Information.

This cross-sectional study analyzes the accuracy of nutrition information from artificial intelligence (AI) in comparison with a nutritionist.

Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app.

OBJECTIVE: Mobile nutrition applications (apps) provide a simple way for individuals to record their diet, but the validity and inherent errors need to be carefully evaluated. The aim of this study was to assess the validity and clarify the sources of measurement errors of image-assisted mobile nutrition apps. METHODS: This was a cross-sectional study with 98 students recruited from School of Nutrition and Health Sciences, Taipei Medical University. A 3-d nutrient intake record by Formosa Food and Nutrient Recording App (FoodApp) was compared with a 24-h dietary recall (24-HDR). A two-stage data modification process, manual data cleaning, and reanalyzing of prepackaged foods were employed to address inherent errors. Nutrient intake levels obtained by the two methods were compared with the recommended daily intake (DRI), Taiwan. Paired t test, Spearman's correlation coefficients, and Bland-Altman plots were used to assess agreement between the FoodApp and 24-HDR. RESULTS: Manual data cleaning identified 166 food coding errors (12%; stage 1), and 426 food codes with missing micronutrients (32%) were reanalyzed (stage 2). Positive linear trends were observed for total energy and micronutrient intake (all Ptrend < 0.05) after the two stages of data modification, but not for dietary fat, carbohydrates, or vitamin D. There were no statistical differences in mean energy and macronutrient intake between the FoodApp and 24-HDR, and this agreement was confirmed by Bland-Altman plots. Spearman's correlation analyses showed strong to moderate correlations (r = 0.834 ∼ 0.386) between the two methods. Participants' nutrient intake tended to be lower than the DRI, but no differences in proportions of adequacy/inadequacy for DRI values were observed between the two methods. CONCLUSIONS: Mitigating errors significantly improved the accuracy of the Formosa FoodApp, indicating its validity and reliability as a self-reporting mobile-based dietary assessment tool. Dietitians and health professionals should be mindful of potential errors associated with self-reporting nutrition apps, and manual data cleaning is vital to obtain reliable nutrient intake data.

Automated pupillometry and optic nerve sheath diameter ultrasound to define tuberculous meningitis disease severity and prognosis.

BACKGROUND: Tuberculous meningitis (TBM) causes high mortality and morbidity, in part due to raised intracranial pressure (ICP). Automated pupillometry (NPi) and optic nerve sheath diameter (ONSD) are both low-cost, easy-to-use and non-invasive techniques that correlate with ICP and neurological status. However, it is uncertain how to apply these techniques in the management of TBM. METHODS: We conducted a pilot study enrolling 20 adults with TBM in the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam. Our objective was to investigate the relationships between baseline and serial measurements of NPi and ONSD and disease severity and outcome. Serial NPi and ONSD were performed for 30 days, at discharge, and at 3-months, with measurements correlated with clinical progression and outcomes. RESULTS: ONSD and NPi measurements had an inverse relationship. Higher ONSD and lower NPi values were associated with lower Glasgow coma score. Baseline NPi was a strong predictor 3-month outcome (median NPi 4.55, interquartile range 4.35-4.65 for good outcomes versus 2.60, IQR 0.65-3.95 for poor outcomes, p = 0.002). Pupil inequality (NPi ≥0.7) was also strongly associated with poor 3-month outcomes (p = 0.006). Individual participants' serial NPi and ONSD were variable during initial treatment and correlated with clinical condition and outcome. CONCLUSION: Pupillometry and ONSD may be used to predict clinical deterioration and outcome from TBM. Future, larger studies are need explore the optimal timing of measurements and to define how they might be used to optimise treatments and improve outcomes from TBM.

Global prevalence of post-COVID-19 sleep disturbances in adults at different follow-up time points: A systematic review and meta-analysis.

Our systematic review and meta-analysis estimated the prevalence of post-COVID sleep disturbances in adult population. We systematically searched relevant studies from four databases that reported post-COVID sleep disturbances prevalence with a mean or median follow-up duration of ≥28 days. We identified 153 eligible papers, with a total COVID-19 population of 252437. Employing multilevel mixed-effects meta-analyses, we estimated the overall pooled prevalence of post-COVID sleep disturbances being 28.98% (25.73-32.34), with the highest prevalence reported in Europe and the lowest in Southeast Asia. Poor sleep quality was the most prevalent definition of sleep disturbances, followed by excessive daytime sleepiness, insomnia, sleep apnea. Prevalence estimates were notably higher when measured with Epworth sleepiness scale, or Pittsburgh sleep quality index compared to symptom questionnaires, self-reports, or personal interviews. Female sex (Odds ratio, OR = 1.59, 1.38-1.83) and severe/critical acute COVID-19 (OR = 1.36, 1.09-1.69) emerged as substantial risk factors. Our review underscore the persistent prevalence of sleep disturbances among COVID-19 survivors, and the importance of factors such as geography, definition, measures of sleep disorders, sex, and severity of acute COVID-19 infection. These findings highlight the urgent need for further investigation into the underlying molecular mechanisms driving these sleep disturbances to develop effective therapeutic strategies.

Association of diabetes mellitus with early-onset colorectal cancer: A systematic review and meta-analysis of 19 studies including 10 million individuals and 30,000 events.

BACKGROUND AND AIMS: Early-onset colorectal cancer (EoCRC) constitutes 2%-10% of all colorectal cancers and is becoming more common globally. Diabetes mellitus (DM) has increased substantially in younger adults; however, its involvement in EoCRC remains unclear. We conducted a systematic review and meta-analysis of observational studies to (1) explore the prevalence of DM in individuals with EoCRC and (2) investigate the association between DM and EoCRC. METHODS: A systematic literature search was conducted to identify studies published before May 2022 that evaluated the association between DM and EoCRC risk in four databases, including Medline (PubMed), Embase, Web of Science, and the Cochrane Central Register of Controlled Trials. Results from the studies were summarized in meta-analyses using random effects models. RESULTS: Nineteen eligible studies were included. A total of 33,359 EoCRC cases and 14,259,289 controls in 12 studies were included in the meta-analysis. The pooled odds ratio [OR] of 1.43 (95% confidence interval [CI]: 1.08-1.8) indicated significant positive association between DM and increased risk of EoCRC. Subgroup analysis demonstrated that diabetes severity was significantly associated with unmanaged DM (OR = 1.28, 95% CI: 1.02-1.6), but not with managed DM (OR = 1.04, 95% CI: 0.84-1.28). CONCLUSION: Our results suggest that DM is a risk factor for EoCRC, and the higher prevalence of DM among younger adults may contribute to the increasing incidence of EoCRC. Interventions to reduce this bidirectional risk should be further investigated for the development of effective prevention and treatment strategies. PROSPERO registration: CRD42022306347.

Comparative genomics of two Vietnamese Helicobacter pylori strains, CHC155 from a non-cardia gastric cancer patient and VN1291 from a duodenal ulcer patient.

Helicobacter pylori is involved in the etiology and severity of several gastroduodenal diseases; however, plasticity of the H. pylori genome makes complete genome assembly difficult. We report here the full genomes of H. pylori strains CHC155 and VN1291 isolated from a non-cardia gastric cancer patient and a duodenal ulcer patient, respectively, and their virulence demonstrated by in vitro infection. Whole-genome sequences were obtained by combining long- and short-reads with a hybrid-assembly approach. Both CHC155 and VN1291 genome possessed four kinds of genomic island: a cag pathogenicity island (cagPAI), two type 4 secretion system islands within an integrative and conjugative element (tfs ICE), and prophage. CHC155 and VN1291 carried East Asian-type cagA and vacA s1m1, and outer membrane protein genes, including two copies of oipA. Corresponded to genetic determinants of antibiotic resistance, chromosomal mutations were identified in CHC155 (rdxA, gyrA, and 23S rRNA) and VN1291 (rdxA, 23S rRNA, and pbp1A). In vitro infection of AGS cells by both strains induced the cell scattering phenotype, tyrosine phosphorylation of CagA, and promoted high levels of IL8 secretion, indicating fully intact phenotypes of the cagPAI. Virulence genes in CHC155 and VN1291 genomes are crucial for H. pylori pathogenesis and are risk factors in the development of gastric cancer and duodenal ulcer. Our in vitro studies indicate that the strains CHC155 and VN1291 carry the pathogenic potential.

Support of deep learning to classify vocal fold images in flexible laryngoscopy.

PURPOSE: To collect a dataset with adequate laryngoscopy images and identify the appearance of vocal folds and their lesions in flexible laryngoscopy images by objective deep learning models. METHODS: We adopted a number of novel deep learning models to train and classify 4549 flexible laryngoscopy images as no vocal fold, normal vocal folds, and abnormal vocal folds. This could help these models recognize vocal folds and their lesions within these images. Ultimately, we made a comparison between the results of the state-of-the-art deep learning models, and another comparison of the results between the computer-aided classification system and ENT doctors. RESULTS: This study exhibited the performance of the deep learning models by evaluating laryngoscopy images collected from 876 patients. The efficiency of the Xception model was higher and steadier than almost the rest of the models. The accuracy of no vocal fold, normal vocal folds, and vocal fold abnormalities on this model were 98.90 %, 97.36 %, and 96.26 %, respectively. Compared to our ENT doctors, the Xception model produced better results than a junior doctor and was near an expert. CONCLUSION: Our results show that current deep learning models can classify vocal fold images well and effectively assist physicians in vocal fold identification and classification of normal or abnormal vocal folds.

Urinary catecholamine excretion, cardiovascular variability, and outcomes in tetanus.

Severe tetanus is characterized by muscle spasm and cardiovascular system disturbance. The pathophysiology of muscle spasm is relatively well understood and involves inhibition of central inhibitory synapses by tetanus toxin. That of cardiovascular disturbance is less clear, but is believed to relate to disinhibition of the autonomic nervous system. The clinical syndrome of autonomic nervous system dysfunction (ANSD) seen in severe tetanus is characterized principally by changes in heart rate and blood pressure which have been linked to increased circulating catecholamines. Previous studies have described varying relationships between catecholamines and signs of ANSD in tetanus, but are limited by confounders and assays used. In this study, we aimed to perform detailed characterization of the relationship between catecholamines (adrenaline and noradrenaline), cardiovascular parameters (heart rate and blood pressure) and clinical outcomes (ANSD, mechanical ventilation required, and length of intensive care unit stay) in adults with tetanus, as well as examine whether intrathecal antitoxin administration affected subsequent catecholamine excretion. Noradrenaline and adrenaline were measured by ELISA from 24-h urine collections taken on day 5 of hospitalization in 272 patients enrolled in a 2 × 2 factorial-blinded randomized controlled trial in a Vietnamese hospital. Catecholamine results measured from 263 patients were available for analysis. After adjustment for potential confounders (i.e., age, sex, intervention treatment, and medications), there were indications of non-linear relationships between urinary catecholamines and heart rate. Adrenaline and noradrenaline were associated with subsequent development of ANSD, and length of ICU stay.

Aetiology and Potential Animal Exposure in Central Nervous System Infections in Vietnam.

An estimated 73% of emerging infections are zoonotic in origin, with animal contact and encroachment on their habitats increasing the risk of spill-over events. In Vietnam, close exposure to a wide range of animals and animal products can lead to acquisition of zoonotic pathogens, a number of which cause central nervous system (CNS) infections. However, studies show the aetiology of CNS infections remains unknown in around half of cases. We used samples and data from hospitalised patients with CNS infections, enrolled into the Vietnam Initiative on Zoonotic Infections multicentre study, to determine the association between aetiology and animal contact including those in whom the cause was unknown. Among 933 patients, a pathogen or an antibody response to it was identified in 291 (31.2%, 95% CI 28.3-34.3%). The most common pathogens were Streptococcus suis (n = 91 (9.8%, 8.0-11.9%)) and Japanese encephalitis virus (JEV) (n = 72 (7.7%, 6.1-9.7%)). Commonly reported animal contact included keeping, raising or handling (n = 364 (39.0%, 35.9-42.2%)) and handling, cooking or consuming raw meat, blood or viscera in the 2 weeks prior to symptom onset (n = 371 (39.8%, 36.6-43.0%)), with the latter most commonly from pigs (n = 343 (36.9%, 33.8-40.1%). There was no association between an unknown aetiology and exposure to animals in a multivariate logistic regression. Further testing for unknown or undetected pathogens may increase diagnostic yield, however, given the high proportion of zoonotic pathogens and the presence of risk factors, increasing public awareness about zoonoses and preventive measures can be considered.

COVID-19 and Virtual Nutrition: A Pilot Study of Integrating Digital Food Models for Interactive Portion Size Education.

Background and aims: Digital food viewing is a vital skill for connecting dieticians to e-health. The aim of this study was to integrate a novel pedagogical framework that combines interactive three- (3-D) and two-dimensional (2-D) food models into a formal dietetic training course. The level of agreement between the digital food models (first semester) and the effectiveness of educational integration of digital food models during the school closure due to coronavirus disease 2019 (COVID-19) (second semester) were evaluated. Method: In total, 65 second-year undergraduate dietetic students were enrolled in a nutritional practicum course at the School of Nutrition and Health Sciences, Taipei Medical University (Taipei, Taiwan). A 3-D food model was created using Agisoft Metashape. Students' digital food viewing skills and receptiveness towards integrating digital food models were evaluated. Results: In the first semester, no statistical differences were observed between 2-D and 3-D food viewing skills in food identification (2-D: 89% vs. 3-D: 85%) and quantification (within ±10% difference in total calories) (2-D: 19.4% vs. 3-D: 19.3%). A Spearman correlation analysis showed moderate to strong correlations of estimated total calories (0.69~0.93; all p values < 0.05) between the 3-D and 2-D models. Further analysis showed that students who struggled to master both 2-D and 3-D food viewing skills had lower estimation accuracies than those who did not (equal performers: 28% vs. unequal performers:16%, p = 0.041), and interactive 3-D models may help them perform better than 2-D models. In the second semester, the digital food viewing skills significantly improved (food identification: 91.5% and quantification: 42.9%) even for those students who struggled to perform digital food viewing skills equally in the first semester (equal performers: 44% vs. unequal performers: 40%). Conclusion: Although repeated training greatly enhanced students' digital food viewing skills, a tailored training program may be needed to master 2-D and 3-D digital food viewing skills. Future study is needed to evaluate the effectiveness of digital food models for future "eHealth" care.

Human versus equine intramuscular antitoxin, with or without human intrathecal antitoxin, for the treatment of adults with tetanus: a 2 × 2 factorial randomised controlled trial.

BACKGROUND: Intramuscular antitoxin is recommended in tetanus treatment, but there are few data comparing human and equine preparations. Tetanus toxin acts within the CNS, where there is limited penetration of peripherally administered antitoxin; thus, intrathecal antitoxin administration might improve clinical outcomes compared with intramuscular injection. METHODS: In a 2  × 2 factorial trial, all patients aged 16 years or older with a clinical diagnosis of generalised tetanus admitted to the intensive care unit of the Hospital for Tropical Diseases, Ho Chi Minh City, Vietnam, were eligible for study entry. Participants were randomly assigned first to 3000 IU human or 21 000 U equine intramuscular antitoxin, then to either 500 IU intrathecal human antitoxin or sham procedure. Interventions were delivered by independent clinicians, with attending clinicians and study staff masked to treatment allocations. The primary outcome was requirement for mechanical ventilation. The analysis was done in the intention-to-treat population. The study is registered at ClinicalTrials.gov, NCT02999815; recruitment is completed. FINDINGS: 272 adults were randomly assigned to interventions between Jan 8, 2017, and Sept 29, 2019, and followed up until May, 2020. In the intrathecal allocation, 136 individuals were randomly assigned to sham procedure and 136 to antitoxin; in the intramuscular allocation, 109 individuals were randomly assigned to equine antitoxin and 109 to human antitoxin. 54 patients received antitoxin at a previous hospital, excluding them from the intramuscular antitoxin groups. Mechanical ventilation was given to 56 (43%) of 130 patients allocated to intrathecal antitoxin and 65 (50%) of 131 allocated to sham procedure (relative risk [RR] 0·87, 95% CI 0·66-1·13; p=0·29). For the intramuscular allocation, 48 (45%) of 107 patients allocated to human antitoxin received mechanical ventilation compared with 48 (44%) of 108 patients allocated to equine antitoxin (RR 1·01, 95% CI 0·75-1·36, p=0·95). No clinically relevant difference in adverse events was reported. 22 (16%) of 136 individuals allocated to the intrathecal group and 22 (11%) of 136 allocated to the sham procedure experienced adverse events related or possibly related to the intervention. 16 (15%) of 108 individuals allocated to equine intramuscular antitoxin and 17 (16%) of 109 allocated to human antitoxin experienced adverse events related or possibly related to the intervention. There were no intervention-related deaths. INTERPRETATION: We found no advantage of intramuscular human antitoxin over intramuscular equine antitoxin in tetanus treatment. Intrathecal antitoxin administration was safe, but did not provide overall benefit in addition to intramuscular antitoxin administration. FUNDING: The Wellcome Trust.