Artificial intelligence driven malnutrition diagnostic model for patients with acute abdomen based on GLIM criteria: a cross-sectional research protocol.

BACKGROUND: Patients with acute abdomen often experience reduced voluntary intake and a hypermetabolic process, leading to a high occurrence of malnutrition. The Global Leadership Initiative on Malnutrition (GLIM) criteria have rapidly developed into a principal methodological tool for nutritional diagnosis. Additionally, machine learning is emerging to establish artificial intelligent-enabled diagnostic models, but the accuracy and robustness need to be verified. We aimed to establish an intelligence-enabled malnutrition diagnosis model based on GLIM for patients with acute abdomen. METHOD: This study is a single-centre, cross-sectional observational investigation into the prevalence of malnutrition in patients with acute abdomen using the GLIM criteria. Data collection occurs on the day of admission, at 3 and 7 days post-admission, including biochemical analysis, body composition indicators, disease severity scoring, nutritional risk screening, malnutrition diagnosis and nutritional support information. The occurrence rate of malnutrition in patients with acute abdomen is analysed with the GLIM criteria based on the Nutritional Risk Screening 2002 and the Mini Nutritional Assessment Short-Form to investigate the sensitivity and accuracy of the GLIM criteria. After data cleansing and preprocessing, a machine learning approach is employed to establish a predictive model for malnutrition diagnosis in patients with acute abdomen based on the GLIM criteria. ETHICS AND DISSEMINATION: This study has obtained ethical approval from the Ethics Committee of the Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital on 28 November 2022 (Yan-2022-442). The results of this study will be disseminated in peer-reviewed journals, at scientific conferences and directly to study participants. TRIAL REGISTRATION NUMBER: ChiCTR2200067044.

Pretreatment optimization of tissue metabolomics in colorectal cancer.

BACKGROUND AND OBJECTIVES: To optimize the pretreatment method of colorectal cancer tissue samples for metabolomics research based on solid-phase nuclear magnetic resonance (NMR). METHODS AND STUDY DESIGN: The mucosal tissues of colorectal cancer were classified into five groups with a volume of 0.2 cm*0.2 cm*0.2 cm. The pretreatment methods for each group were as follows: I. Preservation with liquid nitrogen alone. Samples were also treated with liquid nitrogen for 10 (II), 20 (III), and 30 min (IV), respectively, immediately after isolation and then transferred to a -80℃ refrigerator; V. Only -80℃ refrigerator storage. No more than 30 minutes should pass between isolation and pretreatment of tumor samples. The tissue sample testing process was carried out on Bruker AVII-600 NMR Spectrometer. NMR signals were collected and analysed using partial least-squares discrimination analysis (PLS-DA) to explore the effects of different pretreatment methods on the metabolic changes of samples. RESULTS: The levels of pelargonic acid, stearic acid, D-Ribose, heptadecanoic acid, pyruvic acid, succinate, sarcosine, glycine, creatine, and L-lactate in the group I (only liquid nitrogen) were significantly lower than the other groups (p<0.05); the content of glycerophosphocholine in the group I (only liquid nitrogen) was lower than that in the other groups (p=0.055). These indicated that the glucose and choline phospholipid metabolism levels of the liquid nitrogen group were significantly lower than those of the other four groups. CONCLUSIONS: Liquid nitrogen storage can stop the metabolic process of glucose and choline phospholipid in colorectal cancer tissue samples in vitro, thus maintaining the metabolic state of tissue samples in vivo as much as possible.

Gut, metabolism and nutritional Support for COVID-19: Experiences from China.

There is little research that focuses on the relationship between the gut, metabolism, nutritional support and COVID-19. As a group of Chinese physicians, nutritionists and scientists working on the frontline treating COVID-19 patients, we aim to integrate our experiences and the current clinical evidence to address this pressing issue in this article. Based on our clinical observations and available evidence, we recommend the following practice. Firstly, the Nutritional Risk Screening 2002 tool should be used routinely and periodically; for patients with a score ≥3, oral nutritional supplements should be given immediately. Secondly, for patients receiving the antiviral agents lopinavir/ritonavir, gastrointestinal side effects should be monitored for and timely intervention provided. Thirdly, for feeding, the enteral route should be the first choice. In patients undergoing mechanical ventilation, establishing a jejunal route as early as possible can guarantee the feeding target being achieved if gastric dilatation occurs. Fourthly, we suggest a permissive underfeeding strategy for severe/critical patients admitted to the intensive care unit during the first week of admission, with the energy target no more than 20 kcal/kg/day (for those on mechanical ventilation, this target may be lowered to 10-15 kcal/kg/day) and the protein target around 1.0-1.2 g/kg/day. If the inflammatory condition is significantly alleviated, the energy target may be gradually increased to 25-30 kcal/kg/day and the protein target to 1.2-1.5 g/kg/day. Fifthly, supplemental parenteral nutrition should be used with caution. Lastly, omega-3 fatty acids may be used as immunoregulators, intravenous administration of omega-3 fatty emulsion (10 g/day) at an early stage may help to reduce the inflammatory reaction.

Metabolic dynamics in critically injured patients: a prospective cohort study integrated with 1H NMR metabolomics.

BACKGROUND AND OBJECTIVES: By combining the techniques of metabolomics and computational biology, this research aims to explore the mechanism of metabolic dynamics in critically injured patients and develop a new early warning method for mortality. METHODS AND STUDY DESIGN: A prospective cohort study was conducted, group plasma samples of critically injured patients were collected for 1H-NMR metabolomics analysis. The data was processed with partial least squares regression, to explore the role of enzyme-gene network regulatory mechanism in critically injured metabolic network regulation and to build a quantitative prediction model for early warning of fast death. RESULTS: In total, 60 patients were enrolled. There were significant differences in plasma metabolome between the surviving patients and the deceased ones. Compared to the surviving patients, 112 enzymes and genes regulating the 6 key metabolic marker disturbances of neopterin, corticosterone, 3-methylhistidine, homocysteine, Serine, tyrosine, prostaglandin E2, tryptophan, testosterone and estriol, were observed in the plasmas of deceased ones. Among patients of different injury stages, there were significant differences in plasma metabolome. Progressing from T0 to T50 stages of injury, increased levels of neopterin, corticosterone, prostaglandin E2, tryptophan and testosterone, together with decreased levels of homocysteine, and estriol, were observed. Eventually, the quantitative prediction model of death warning was established. Cross-validation results showed that the predictive effect was good (RMSE=0.18408, R2=0.87 p=0.036). CONCLUSIONS: Metabolomics approaches can be used to quantify the metabolic dynamics of patients with critically injuries and to predict death of critically injured patients by plasma 1H-NMR metabolomics.

The dilemma of heterogeneity tests in meta-analysis: a challenge from a simulation study.

INTRODUCTION: After several decades' development, meta-analysis has become the pillar of evidence-based medicine. However, heterogeneity is still the threat to the validity and quality of such studies. Currently, Q and its descendant I(2) (I square) tests are widely used as the tools for heterogeneity evaluation. The core mission of this kind of test is to identify data sets from similar populations and exclude those are from different populations. Although Q and I(2) are used as the default tool for heterogeneity testing, the work we present here demonstrates that the robustness of these two tools is questionable. METHODS AND FINDINGS: We simulated a strictly normalized population S. The simulation successfully represents randomized control trial data sets, which fits perfectly with the theoretical distribution (experimental group: p = 0.37, control group: p = 0.88). And we randomly generate research samples Si that fits the population with tiny distributions. In short, these data sets are perfect and can be seen as completely homogeneous data from the exactly same population. If Q and I(2) are truly robust tools, the Q and I(2) testing results on our simulated data sets should not be positive. We then synthesized these trials by using fixed model. Pooled results indicated that the mean difference (MD) corresponds highly with the true values, and the 95% confidence interval (CI) is narrow. But, when the number of trials and sample size of trials enrolled in the meta-analysis are substantially increased; the Q and I(2) values also increase steadily. This result indicates that I(2) and Q are only suitable for testing heterogeneity amongst small sample size trials, and are not adoptable when the sample sizes and the number of trials increase substantially. CONCLUSIONS: Every day, meta-analysis studies which contain flawed data analysis are emerging and passed on to clinical practitioners as "updated evidence". Using this kind of evidence that contain heterogeneous data sets leads to wrong conclusion, makes chaos in clinical practice and weakens the foundation of evidence-based medicine. We suggest more strict applications of meta-analysis: it should only be applied to those synthesized trials with small sample sizes. We call upon that the tools of evidence-based medicine should keep up-to-dated with the cutting-edge technologies in data science. Clinical research data should be made available publicly when there is any relevant article published so the research community could conduct in-depth data mining, which is a better alternative for meta-analysis in many instances.

Is omega-3 fatty acids enriched nutrition support safe for critical ill patients? A systematic review and meta-analysis.

OBJECTIVE: To systematically review the effects of omega-3 poly unsaturated fatty acids (FA) enriched nutrition support on the mortality of critically illness patients. METHODS: Databases of Medline, ISI, Cochrane Library, and Chinese Biomedicine Database were searched and randomized controlled trials (RCTs) were identified. We enrolled RCTs that compared fish oil enriched nutrition support and standard nutrition support. Major outcome is mortality. Methodological quality assessment was conducted based on Modified Jadad's score scale. For control heterogeneity, we developed a method that integrated I2 test, nutritional support route subgroup analysis and clinical condition of severity. RevMan 5.0 software (The Nordic Cochrane Centre, Copenhagen, Denmark) was used for meta-analysis. RESULTS: Twelve trials involving 1208 patients that met all the inclusion criteria. Heterogeneity existed between the trials. A random model was used, there was no significant effect on mortality RR, 0.82, 95% confidence interval (CI) (0.62, 1.09), p = 0.18. Knowing that the route of fish oil administration may affect heterogeneity, we categorized the trials into two sub-groups: parenteral administration (PN) of omega-3 and enteral administration (EN) of omega-3. Six trials administered omega-3 FA through PN. Pooled results indicated that omega-3 FA had no significant effect on mortality, RR 0.76, 95% CI (0.52, 1.10), p = 0.15. Six trials used omega-3 fatty acids enriched EN. After excluded one trial that was identified as source of heterogeneity, pooled data indicated omega-3 FA enriched EN significant reduce mortality, RR=0.69, 95% CI [0.53, 0.91] (p = 0.007). CONCLUSION: Omega-3 FA enriched nutrition support is safe. Due to the limited sample size of the included trials, further large-scale RCTs are needed.

Establishment of quantitative severity evaluation model for spinal cord injury by metabolomic fingerprinting.

Spinal cord injury (SCI) is a devastating event with a limited hope for recovery and represents an enormous public health issue. It is crucial to understand the disturbances in the metabolic network after SCI to identify injury mechanisms and opportunities for treatment intervention. Through plasma 1H-nuclear magnetic resonance (NMR) screening, we identified 15 metabolites that made up an "Eigen-metabolome" capable of distinguishing rats with severe SCI from healthy control rats. Forty enzymes regulated these 15 metabolites in the metabolic network. We also found that 16 metabolites regulated by 130 enzymes in the metabolic network impacted neurobehavioral recovery. Using the Eigen-metabolome, we established a linear discrimination model to cluster rats with severe and mild SCI and control rats into separate groups and identify the interactive relationships between metabolic biomarkers in the global metabolic network. We identified 10 clusters in the global metabolic network and defined them as distinct metabolic disturbance domains of SCI. Metabolic paths such as retinal, glycerophospholipid, arachidonic acid metabolism; NAD-NADPH conversion process, tyrosine metabolism, and cadaverine and putrescine metabolism were included. In summary, we presented a novel interdisciplinary method that integrates metabolomics and global metabolic network analysis to visualize metabolic network disturbances after SCI. Our study demonstrated the systems biological study paradigm that integration of 1H-NMR, metabolomics, and global metabolic network analysis is useful to visualize complex metabolic disturbances after severe SCI. Furthermore, our findings may provide a new quantitative injury severity evaluation model for clinical use.

The origin of novel avian influenza A (H7N9) and mutation dynamics for its human-to-human transmissible capacity.

In February 2013, H7N9 (A/H7N9/2013_China), a novel avian influenza virus, broke out in eastern China and caused human death. It is a global priority to discover its origin and the point in time at which it will become transmittable between humans. We present here an interdisciplinary method to track the origin of H7N9 virus in China and to establish an evolutionary dynamics model for its human-to-human transmission via mutations. After comparing influenza viruses from China since 1983, we established an A/H7N9/2013_China virus evolutionary phylogenetic tree and found that the human instances of virus infection were of avian origin and clustered into an independent line. Comparing hemagglutinin (HA) and neuraminidase (NA) gene sequences of A/H7N9/2013_China viruses with all human-to-human, avian, and swine influenza viruses in China in the past 30 years, we found that A/H7N9/2013_China viruses originated from Baer's Pochard H7N1 virus of Hu Nan Province 2010 (HA gene, EPI: 370846, similarity with H7N9 is 95.5%) and duck influenza viruses of Nanchang city 2000 (NA gene, EPI: 387555, similarity with H7N9 is 97%) through genetic re-assortment. HA and NA gene sequence comparison indicated that A/H7N9/2013_China virus was not similar to human-to-human transmittable influenza viruses. To simulate the evolution dynamics required for human-to-human transmission mutations of H7N9 virus, we employed the Markov model. The result of this calculation indicated that the virus would acquire properties for human-to-human transmission in 11.3 years (95% confidence interval (CI): 11.2-11.3, HA gene).

Malnutrition in hospitalized people living with HIV/AIDS: evidence from a cross-sectional study from Chengdu, China.

OBJECTIVES: Nutrition support has long been ignored in China's HIV/AIDS treatment and care. The objectives of this project were to evaluate the prevalence of malnutrition among Chengdu urban HIV positive patients, and to provide evidence for further nutritional intervention. MATERIALS AND METHODS: HIV-infected adults admitted to an infectious diseases inpatient unit were eligible for this study. Nutritional status was evaluated using Subject Global Assessment (SGA), Malnutrition Universal Screening Tool (MUST), body mass index (BMI), food frequency questionnaire and dietary records. RESULTS: 94 hospitalized HIV positive patients were enrolled from April 2009 to May 2010. The median CD4 T cell count was 44.0/mm3. The prevalence of malnutrition is measured by three tools and ranged from 37.2% (by BMI) to 77.2% (by SGA class B/C or MUST scores ≥ 2). Chi-square test showed significant relationship between opportunistic infections and MUST score (OR=5.67, p<0.005, 95% CI=1.96-16.4). Of patients, 59.6% had insufficient total energy intake; while 54.3% had insufficient protein intake. CONCLUSIONS: Malnutrition is highly prevalent among Chengdu urban HIV/AIDS patients who underwent inpatient treatment. Calorie and protein deficiency should be given more attention in HIV/AIDS care programs. Nutrition evaluation and support should be considered an integral parts of national and community HIV/AIDS treatment and care guidelines.

Efficacy of hypocaloric parenteral nutrition for surgical patients: a systematic review and meta-analysis.

BACKGROUND AND AIMS: Hypocaloric parenteral nutrition is an underfeeding strategy that lowers energy intake to around 20 kcal/kg/d. It is believed to achieve benefits by modulating metabolic responses and alleviating hyperglycemia. This study aims to systematically review the clinical efficacy of hypocaloric parenteral nutrition on surgical patients. METHODS: Medline, SCI, Embase, Cochrane Library, Chinese Biomedicine Database (CBM) and China Knowledge Resource Integrated Database (CNKI) were searched for studies published before July 1, 2010. Randomized control trials (RCTs) that compared hypocaloric PN with standard or higher energy PN in surgical patients were identified and included. Methodological quality assessment was based on Cochrane Reviewers' Handbook and modified Jadad's Score Scale. Statistical software RevMan 5.0 was used for meta-analysis. RESULTS: Five trials met all inclusion criteria and were included in the final meta-analysis. There were significant reductions in infectious complications (RR, 0.60; 95%CI 0.39-0.91, P = 0.02; I(2) = 38%) and length of hospitalization (LOS) associated with receiving hypocaloric PN (MD-2.49 days, 95%CI -3.88 to -1.11, P = 0.0004; I² = 48%). Stratified analysis of the smaller trials (<60) and larger trials demonstrated that the heterogeneity between trials was mainly associated with sample size. When smaller trials were excluded, hypocaloric PN was associated with reduction in infectious complications (RR, 0.21, 95%CI 0.06-0.72, P = 0.01, I2 = 0%) and shortening of LOS (MD, -2.32 days, 95%CI -3.72 to -0.93, P = 0.001, I² = 0%). CONCLUSION: Hypocaloric parenteral nutrition may reduce infectious complications and the length of hospitalization in post-operative patients. However, this conclusion is tentative due to patient type and sample size. Furthermore, in terms of hypocaloric PN, the actual energy amount still varies a great deal (from 15 kcal/kg/d to 20 kcal/kg/d). This suggests that further research, including larger randomized clinical trials is required.