RESUMEN

The exact aetiology of the cause of death (COD) remains unknown for a high proportion of deaths caused by infectious diseases. Complete diagnostic autopsy (CDA) is considered the gold standard to determine COD, but it is often not used in low and middle-income countries (LMIC), including Vietnam, for a variety of reasons. One alternative is minimally invasive tissue sampling (MITS). This study was part of a larger project to explore the perceptions of MITS in Vietnam to provide recommendations for its potential implementation. We collected in-depth interviews and focus group discussions that explored MITS acceptability from 96 participants, including key informants, healthcare workers, community stakeholders, and people who had family members pass away recently. Participants highlighted the minimally invasive nature as the most considerable strength of MITS that could make it acceptable in Vietnam compared with CDA. However, participants still had concerns including the accuracy of the technique, the potential damage on the body, and the potential conflicts MITS results could have with original clinical diagnoses. Overall, the hypothetical acceptability of MITS was not clear-cut. It is imperative to consider acceptability before implementing new medical procedures into a given context, especially when it revolves around death, dying and the body.

Asunto(s)

RESUMEN

Obstetric ultrasound is an important tool in managing pregnancies and its use is increasing globally. However, the status of the pregnant woman and the fetus may vary in terms of clinical management, views in the community and legislation. To investigate the views and experiences of Vietnamese health professionals on maternal and fetal health interests, priority setting and potential conflicts, we conducted a cross-sectional study using a structured questionnaire. Obstetricians/gynecologists, midwives and sonographers who manage pregnant women in maternity wards were invited to participate. We purposively chose public health facilities in the Hanoi region of Vietnam to obtain a representative sample. The final sample included 882 health professionals, of which 32.7% (n = 289) were obstetricians/gynecologists, 60.7% (n = 535) midwives and 6.6% (n = 58) sonographers. The majority of participants (60.3%) agreed that "The fetus is a person from the time of conception" and that maternal health interests should always be prioritised over fetal health interests in care provided (54.4%). 19.7% agreed that the fetus is never a patient, only the pregnant woman can be the patient, while 60.5% disagreed. Participants who performed ultrasounds were more likely to agree that fetal health interests are being given more weight in decision-making the further the gestation advances compared to those who did not perform ultrasounds (cOR 2.47, CI 1.27-4.79: n = 811). A significant proportion of health professionals in Vietnam assign the fetus the status of being a person, where personhood gradually evolves during pregnancy. While the fetus is often considered a patient with its own health interests, a majority of participants did give priority to maternal health interests. Health professionals appear to favour increased legal protection of the fetus. Strengthening the legal status of the fetus might have adverse implications for maternal autonomy. Measures to restrict maternal autonomy might require close observation to ensure that maternal reproductive rights are protected.

Asunto(s)

RESUMEN

Background: Controlling saturated fat and cholesterol intake is important for the prevention of cardiovascular diseases. Although the use of mobile diet-tracking apps has been increasing, the reliability of nutrition apps in tracking saturated fats and cholesterol across different nations remains underexplored. Objective: This study aimed to examine the reliability and consistency of nutrition apps focusing on saturated fat and cholesterol intake across different national contexts. The study focused on 3 key concerns: data omission, inconsistency (variability) of saturated fat and cholesterol values within an app, and the reliability of commercial apps across different national contexts. Methods: Nutrient data from 4 consumer-grade apps (COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!) and an academic app (Formosa FoodApp) were compared against 2 national reference databases (US Department of Agriculture [USDA]-Food and Nutrient Database for Dietary Studies [FNDDS] and Taiwan Food Composition Database [FCD]). Percentages of missing nutrients were recorded, and coefficients of variation were used to compute data inconsistencies. One-way ANOVAs were used to examine differences among apps, and paired 2-tailed t tests were used to compare the apps to national reference data. The reliability across different national contexts was investigated by comparing the Chinese and English versions of MyFitnessPal with the USDA-FNDDS and Taiwan FCD. Results: Across the 5 apps, 836 food codes from 42 items were analyzed. Four apps, including COFIT, MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!, significantly underestimated saturated fats, with errors ranging from -13.8% to -40.3% (all P<.05). All apps underestimated cholesterol, with errors ranging from -26.3% to -60.3% (all P<.05). COFIT omitted 47% of saturated fat data, and MyFitnessPal-Chinese missed 62% of cholesterol data. The coefficients of variation of beef, chicken, and seafood ranged from 78% to 145%, from 74% to 112%, and from 97% to 124% across MyFitnessPal-Chinese, MyFitnessPal-English, and LoseIt!, respectively, indicating a high variability in saturated fats across different food groups. Similarly, cholesterol variability was consistently high in dairy (71%-118%) and prepackaged foods (84%-118%) across all selected apps. When examining the reliability of MyFitnessPal across different national contexts, errors in MyFitnessPal were consistent across different national FCDs (USDA-FNDSS and Taiwan FCD). Regardless of the FCDs used as a reference, these errors persisted to be statistically significant, indicating that the app's core database is the source of the problems rather than just mismatches or variances in external FCDs. Conclusions: The findings reveal substantial inaccuracies and inconsistencies in diet-tracking apps' reporting of saturated fats and cholesterol. These issues raise concerns for the effectiveness of using consumer-grade nutrition apps in cardiovascular disease prevention across different national contexts and within the apps themselves.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

RESUMEN

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.

RESUMEN

Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), remains a global health burden. While M. tuberculosis 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 lead to differential disease across organs. Attention has focused on differences in T cell responses in the control of M. tuberculosis 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 in TBM and determined whether M. tuberculosis-specific humoral immune responses differed between M. tuberculosis infection of the lung (pulmonary TB) and TBM. Using a high throughput systems serology approach, we deeply profiled the antibody responses against 10 different M. tuberculosis antigens, including lipoarabinomannan (LAM) and purified protein derivative (PPD), in HIV-negative adults with pulmonary TB (n = 10) versus TBM (n = 60). Antibody studies included analysis of immunoglobulin isotypes (IgG, IgM, IgA) and subclass levels (IgG1-4) and the capacity of M. tuberculosis-specific antibodies to bind to Fc receptors or C1q and to activate innate immune effector functions (complement and natural killer cell 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 M. tuberculosis, characterized by an enrichment of M. tuberculosis-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 M. tuberculosis-specific antibodies in the serum with an increased capacity to activate phagocytosis by monocytes, compared with individuals with pulmonary TB, despite having lower IgG titres and Fcγ receptor-binding capacity. Collectively, these data point to functionally divergent humoral responses depending on the site of infection (i.e. lungs versus brain) and demonstrate a highly compartmentalized M. tuberculosis-specific antibody response within the CSF in TBM. Moreover, our results suggest that phagocytosis- and complement-mediating antibodies may promote attenuated neuropathology and milder TBM disease.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

BACKGROUND: Tuberculous meningitis (TBM) is difficult to diagnose. We investigated whether a 3-gene host response signature in blood can distinguish TBM from other brain infections. METHODS: The expression of 3 genes (dual specificity phosphatase 3 [DUSP3], guanylate-binding protein [GBP5], krupple-like factor 2 [KLF2]) was analyzed by RNA sequencing of archived whole blood from 4 cohorts of Vietnamese adults: 281 with TBM, 279 with pulmonary tuberculosis, 50 with other brain infections, and 30 healthy controls. Tuberculosis scores (combined 3-gene expression) were calculated following published methodology and discriminatory performance compared using area under a receiver operator characteristic curve (AUC). RESULTS: GBP5 was upregulated in TBM compared to other brain infections (P < .001), with no difference in DUSP3 and KLF2 expression. The diagnostic performance of GBP5 alone (AUC, 0.74; 95% confidence interval [CI], .67-.81) was slightly better than the 3-gene tuberculosis score (AUC, 0.66; 95% CI, .58-.73) in TBM. Both GBP5 expression and tuberculosis score were higher in participants with human immunodeficiency virus (HIV; P < .001), with good diagnostic performance of GBP5 alone (AUC, 0.86; 95% CI, .80-.93). CONCLUSIONS: The 3-gene host signature in whole blood has the ability to discriminate TBM from other brain infections, including in individuals with HIV. Validation in large prospective diagnostic study is now required.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.

Asunto(s)

RESUMEN

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.