Are adipokines related to COVID-19 and its severity? A systematic review and meta-analysis.

Introduction: The relationship between several adipokines and COVID-19 severity has lately been evaluated, results being inconclusive. Therefore, we aimed to assess the association between adipokines in COVID-19 and its severity. Methods: A search was performed in PubMed, Scopus, and Embase using predefined keywords. The Newcastle of Ottawa Scale (NOS) was used for the quality assessment of included studies. The main summary outcome was the mean difference (MD) in adipokine levels. Results: A total of 8 studies involving 473 individuals were included. A significant MD in serum adiponectin levels was demonstrated in mild vs. severe COVID-19 patients (-5.734 [95% CI -11.215 - -0.252]), with no significant MD in mild vs. moderate (-7.117 [95% CI -19.546 - 5.313]), or moderate vs. severe COVID-19 (-1.846 [95% CI -4.516 - 0.824]). Moreover, no significant MD was found in adiponectin and leptin levels when comparing COVID-19 patients vs. controls (-12.675 [95% CI -36.159 - 10.808]) and (8.034 [95% CI -10.403 - 26.471]), respectively. Conclusion: Adiponectin levels were significantly increased in patients with severe compared to mild COVID-19. However, no significant MD was found in adiponectin levels in mild vs. moderate and moderate vs. severe COVID-19 patients, nor in adiponectin and leptin levels in COVID-19 patients vs. controls.

The Efficiency of Serum Biomarkers in Predicting the Clinical Outcome of Patients with Mesenteric Ischemia during Follow-Up: A Systematic Review.

The initial clinical manifestation of acute mesenteric ischemia poses a diagnostic challenge, often leading to delays in identification and subsequent surgical intervention, contributing to adverse outcomes. Serum biomarkers, offering insights into the underlying pathophysiology, hold promise as prognostic indicators for acute mesenteric ischemia. This systematic review comprehensively explores the role of blood biomarkers in predicting clinical outcomes during follow-up for patients with mesenteric ischemia. A thorough literature search across the PubMed, Cochrane Library, and EMBASE databases yielded 33 relevant publications investigating the efficacy of serum biomarkers in predicting outcomes for mesenteric ischemia. Numerous studies underscore the utility of blood biomarkers in swiftly and accurately differentiating between causes of mesenteric ischemia, facilitating a prompt diagnosis. Elevated levels of specific biomarkers, particularly D-dimers, consistently correlate with heightened mortality risk and poorer clinical outcomes. While certain serum indicators exhibit substantial potential in associating with mesenteric ischemia, further research through rigorous human trials is imperative to enhance their consistent predictive ability during the follow-up period. This study underscores the diagnostic and prognostic significance of specific biomarkers for mesenteric ischemia, emphasizing the necessity for standardized procedures in future investigations.

The management of Clostridioides difficile infection: from empirism to evidence.

Clostridioides difficile infection (CDI) in clinical practice represents a challenge for its management and also prevention of recurrence. Even though there are updated guidelines for infection prevention, control and treatment, CDI remains a leading cause of healthcare acquired diarrhea with increasing incidence in the community. We present here a synthesis of the most recent international guidelines on the management of CDI. In 2021 updated guidelines on the treatment of CDI in adults were published by the Infectious Diseases Society of America (IDSA) and the Society for Healthcare Epidemiology of America (SHEA), American College of Gastroenterology (ACG) and the European Society of Clinical Microbiology and Infectious Diseases (ESCMID). These guidelines focused on CDI management in adults, including new data on the clinical efficacy of Fidaxomicin (FDX) and Bezlotoxumab. The 2017 publication of IDSA and SHEA - Clinical Practice Guidelines for Clostridium difficile infection also included pediatric treatment recommendations that are not a part of the 2021 update. Vancomycin (VAN) treatment for an initial CDI episode remains an acceptable alternative to FDX, considering the monetary and logistical challenge of acquiring FDX. There is growing literature on fecal microbiota transplantation (FMT) and the 2021 guidelines describe its role in severe complicated refractory CDI cases and for which surgical management is not feasible. Moreover, there are new data on the secondary prophylaxis with VAN in refractory CDI in patients with risk factors who receive broad spectrum antibiotics.

Difficult defecation in constipated patients: Diagnosis by minimally invasive diagnostic tests.

BACKGROUND AND AIMS: Defecation Disorders (DD) are a frequent cause of refractory chronic constipation. DD diagnosis requires anorectal physiology testing. Our aim was to evaluate the accuracy and Odds Ratio (OR) of a straining question (SQ) and a digital rectal examination (DRE) augmented by abdomen palpation on predicting a DD diagnosis in refractory CC patients. METHODS: Two hundred and thirty-eight constipated patients were enrolled. Patients underwent SQ, augmented DRE and balloon evacuation test before entering the study and after a 30-day fiber/laxative trial. All patients underwent anorectal manometry. OR and accuracy were calculated for SQ and augmented DRE for both dyssynergic defecation and inadequate propulsion. RESULTS: "Anal Muscles" response was associated to both dyssynergic defecation and inadequate propulsion, with an OR of 13.6 and 5.85 and an accuracy of 78.5% and 66.4%, respectively. "Failed anal relaxation" on augmented DRE was associated with dyssynergic defecation, with an OR of 21.4 and an accuracy of 73.1%. "Failed abdominal contraction" on augmented DRE was associated with inadequate propulsion with an OR >100 and an accuracy of 97.1%. CONCLUSIONS: Our data support screening constipated patients for DD by SQ and augmented DRE to improve management and appropriateness of referral to biofeedback.

Enteroscopy versus Video Capsule Endoscopy for Automatic Diagnosis of Small Bowel Disorders-A Comparative Analysis of Artificial Intelligence Applications.

BACKGROUND: Small bowel disorders present a diagnostic challenge due to the limited accessibility of the small intestine. Accurate diagnosis is made with the aid of specific procedures, like capsule endoscopy or double-ballon enteroscopy, but they are not usually solicited and not widely accessible. This study aims to assess and compare the diagnostic effectiveness of enteroscopy and video capsule endoscopy (VCE) when combined with artificial intelligence (AI) algorithms for the automatic detection of small bowel diseases. MATERIALS AND METHODS: We performed an extensive literature search for relevant studies about AI applications capable of identifying small bowel disorders using enteroscopy and VCE, published between 2012 and 2023, employing PubMed, Cochrane Library, Google Scholar, Embase, Scopus, and ClinicalTrials.gov databases. RESULTS: Our investigation discovered a total of 27 publications, out of which 21 studies assessed the application of VCE, while the remaining 6 articles analyzed the enteroscopy procedure. The included studies portrayed that both investigations, enhanced by AI, exhibited a high level of diagnostic accuracy. Enteroscopy demonstrated superior diagnostic capability, providing precise identification of small bowel pathologies with the added advantage of enabling immediate therapeutic intervention. The choice between these modalities should be guided by clinical context, patient preference, and resource availability. Studies with larger sample sizes and prospective designs are warranted to validate these results and optimize the integration of AI in small bowel diagnostics. CONCLUSIONS: The current analysis demonstrates that both enteroscopy and VCE with AI augmentation exhibit comparable diagnostic performance for the automatic detection of small bowel disorders.

Herbal Remedies for Constipation-Predominant Irritable Bowel Syndrome: A Systematic Review of Randomized Controlled Trials.

BACKGROUND: Constipation-predominant irritable bowel syndrome (IBS-C) is a common gastrointestinal disorder characterized by abdominal pain and altered bowel habits. Conventional treatments for IBS-C often provide limited efficiency, leading to an increasing interest in exploring herbal remedies. This systematic review aims to evaluate the efficacy and safety of herbal remedies in the management of IBS-C. MATERIALS AND METHODS: A comprehensive search of PubMed, MEDLINE, Embase, Scopus, and the Cochrane Library was conducted to identify relevant studies published up to July 2023 and data extraction was performed independently by two reviewers. RESULTS: Overall, the included studies demonstrated some evidence of the beneficial effects of herbal remedies on IBS-C symptoms, including improvements in bowel frequency, stool consistency, abdominal pain, and quality of life. However, the heterogeneity of the interventions and outcome measures limited the ability to perform a meta-analysis. CONCLUSION: This systematic review suggests that herbal remedies may have potential benefits in the management of IBS-C. However, the quality of evidence is limited, and further well-designed, large-scale RCTs are needed to establish the efficacy and safety of specific herbal remedies for IBS-C. Clinicians should exercise caution when recommending herbal remedies and consider individual patient characteristics and preferences.

The Effect of Polyphenols, Minerals, Fibers, and Fruits on Irritable Bowel Syndrome: A Systematic Review.

BACKGROUND: Irritable bowel syndrome (IBS) is a chronic gastrointestinal disorder characterized by abdominal pain, bloating, and changes in bowel habits. Various dietary factors have been implicated in the pathogenesis and management of IBS symptoms. This systematic review aims to evaluate the effects of polyphenols, minerals, fibers, and fruits on the symptoms and overall well-being of individuals with IBS. MATERIALS AND METHODS: A comprehensive literature search was conducted in several electronic databases, including PubMed, Scopus, and Web of Science. Studies published up until July 2023 were included. RESULTS: The selected studies varied in terms of study design, participant characteristics, intervention duration, and outcome measures. Overall, the findings suggest that dietary interventions involving polyphenols, minerals, fibers, and fruits can have a positive impact on IBS symptoms. Dietary fiber supplementation, particularly soluble fiber, has been associated with reduced bloating and enhanced stool consistency. CONCLUSIONS: This systematic review provides evidence supporting the beneficial effects of polyphenols, minerals, fibers, and fruits in IBS patients. These dietary components hold promise as complementary approaches for managing IBS symptoms. However, due to the heterogeneity of the included studies and the limited number of high-quality randomized controlled trials, further well-designed trials are warranted to establish the optimal dosages, duration, and long-term effects of these interventions. Understanding the role of specific dietary components in IBS management may pave the way for personalized dietary recommendations and improve the quality of life for individuals suffering from this complex disorder.

Irritable Bowel Syndrome and Resilience.

Irritable bowel syndrome (IBS) is a disorder of the gut-brain interaction (DGBI), characterized, mainly in severe cases, by altered psychological stress reactivity, psychological disorders, and dysfunction of the brain-gut-microbiota axis. Prior studies have highlighted significant physical and emotional impairments in the health-related quality of life of patients with IBS. Resilience is a psychosocial ability that reduces negative emotions while enhancing adaptation to adversities. Resilience is essential for health promotion and stress response. The present study aimed to carry out a review of the literature in multiple databases, using the descriptors "resilience", "resiliency", and "irritable bowel syndrome". The inclusion criteria for obtaining the most relevant papers were research articles on resilience and irritable bowel syndrome written in English, published in a peer-reviewed journal, and involving human subjects. Studies specifically on resilience in IBS were sparse. These results need to be understood in light of these limitations. As resilience appears to be modifiable, it is essential to conduct direct research on resilience-enhancing interventions for people with IBS. The study of the factors involved in successful adaptation must be extended, to possibly yield new interventions that help the patients overcome the difficulties imposed by the disease.

Waist to height ratio in nonalcoholic fatty liver disease - Systematic review and meta-analysis.

BACKGROUND AND AIMS: Current nonalcoholic fatty liver disease (NAFLD) guidelines do not provide any recommendations regarding the waist-to-height ratio (WHtR), a simple obesity metric calculated by dividing waist circumference by height. Therefore, we performed a systematic review and meta-analysis aiming to evaluate WHtR in NAFLD. METHODS: We performed a systematic electronic search on PubMed, Embase, and Scopus, identifying observational studies assessing WHtR in NAFLD. QUADAS-2 tool was used to evaluate the quality of included studies. The two main statistical outcomes were the area under the curve (AUC) and the mean difference (MD). RESULTS: We included a total of 27 studies in our quantitative and qualitative synthesis, with a total population of 93,536 individuals. WHtR was significantly higher in NAFLD patients compared to controls with an MD of 0.073 (95% CI 0.058 - 0.088). This was also confirmed after conducting a subgroup analysis according to the hepatic steatosis diagnosis method, for ultrasound (MD 0.066 [96% CI 0.051 - 0.081]) and transient elastography (MD 0.074 [96% CI 0.053 - 0.094]). Moreover, NAFLD male patients presented significantly lower WHtR compared to female patients (MD -0.022 [95% CI -0.041 - -0.004]). The AUC of WHtR for predicting NAFLD was 0.815 (95% CI 0.780 - 0.849). CONCLUSIONS: WHtR is considerably higher in NAFLD patients compared to controls. Female NAFLD patients present higher WHtR compared to NAFLD male patients. In comparison to other presently suggested scores and markers, the WHtR's accuracy in predicting NAFLD is considered acceptable.

Adiponectin Levels in Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis.

INTRODUCTION: Adipose tissue plays an important role in the pathogenesis of inflammatory conditions. The role of adipokines in inflammatory bowel disease (IBD) has been evaluated in the current literature with conflicting results. The aim of this study was to evaluate adiponectin levels in IBD patients, including Crohn's disease (CD) and ulcerative colitis (UC), compared to controls, as well as further subgroup analyses. Hence, assessing the potential role of adiponectin as a surrogate marker. METHODS: We performed a systematic electronic search on PubMed, Embase, Scopus, and Cochrane Library, including observational or interventional studies evaluating serum or plasma adiponectin levels in IBD patients in humans. The primary summary outcome was the mean difference (MD) in serum or plasma adiponectin levels between IBD patients versus controls. Subgroup analyses were conducted involving adiponectin levels in CD and UC compared to controls, as well as CD compared to UC. RESULTS: A total of 20 studies were included in our qualitative synthesis and 14 studies in our quantitative synthesis, with a total population sample of 2,085 subjects. No significant MD in serum adiponectin levels was observed between IBD patients versus controls {-1.331 (95% confidence interval [CI]: -3.135-0.472)}, UC patients versus controls (-0.213 [95% CI: -1.898-1.472]), and CD patients versus controls (-0.851 [95% CI: -2.263-0.561]). Nevertheless, a significant MD was found between UC patients versus CD patients (0.859 [95% CI: 0.097-1.622]). CONCLUSIONS: Serum adiponectin levels were not able to differentiate between IBD, UC, and CD patients compared to controls. However, significantly higher serum adiponectin levels were observed in UC compared to CD patients.

Do Colonic Mucosal Tumor Necrosis Factor Alpha Levels Play a Role in Diverticular Disease? A Systematic Review and Meta-Analysis.

Diverticular disease (DD) is the most frequent condition in the Western world that affects the colon. Although chronic mild inflammatory processes have recently been proposed as a central factor in DD, limited information is currently available regarding the role of inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α). Therefore, we conducted a systematic review and meta-analysis aiming to assess the mucosal TNF-α levels in DD. We conducted a systematic literature search using PubMed, Embase, and Scopus to identify observational studies assessing the TNF-α levels in DD. Full-text articles that satisfied our inclusion and exclusion criteria were included, and a quality assessment was performed using the Newcastle-Ottawa Scale (NOS). The principal summary outcome was the mean difference (MD). The results were reported as MD (95% confidence interval (CI)). A total of 12 articles involving 883 subjects were included in the qualitative synthesis, out of which 6 studies were included in our quantitative synthesis. We did not observe statistical significance related to the mucosal TNF-α levels in symptomatic uncomplicated diverticular disease (SUDD) vs. the controls (0.517 (95% CI -1.148-2.182)), and symptomatic vs. asymptomatic DD patients (0.657 (95% CI -0.883-2.196)). However, the TNF-α levels were found to be significantly increased in DD compared to irritable bowel disease (IBS) patients (27.368 (95% CI 23.744-30.992)), and segmental colitis associated with diverticulosis (SCAD) vs. IBS patients (25.303 (95% CI 19.823-30.784)). Between SUDD and the controls, as well as symptomatic and asymptomatic DD, there were no significant differences in the mucosal TNF-α levels. However, the TNF-α levels were considerably higher in DD and SCAD patients than IBS patients. Our findings suggest that TNF-α may play a key role in the pathogenesis of DD in specific subgroups and could potentially be a target for future therapies.

Diagnosis of Liver Fibrosis Using Artificial Intelligence: A Systematic Review.

Background and Objectives: The development of liver fibrosis as a consequence of continuous inflammation represents a turning point in the evolution of chronic liver diseases. The recent developments of artificial intelligence (AI) applications show a high potential for improving the accuracy of diagnosis, involving large sets of clinical data. For this reason, the aim of this systematic review is to provide a comprehensive overview of current AI applications and analyze the accuracy of these systems to perform an automated diagnosis of liver fibrosis. Materials and Methods: We searched PubMed, Cochrane Library, EMBASE, and WILEY databases using predefined keywords. Articles were screened for relevant publications about AI applications capable of diagnosing liver fibrosis. Exclusion criteria were animal studies, case reports, abstracts, letters to the editor, conference presentations, pediatric studies, studies written in languages other than English, and editorials. Results: Our search identified a total of 24 articles analyzing the automated imagistic diagnosis of liver fibrosis, out of which six studies analyze liver ultrasound images, seven studies analyze computer tomography images, five studies analyze magnetic resonance images, and six studies analyze liver biopsies. The studies included in our systematic review showed that AI-assisted non-invasive techniques performed as accurately as human experts in detecting and staging liver fibrosis. Nevertheless, the findings of these studies need to be confirmed through clinical trials to be implemented into clinical practice. Conclusions: The current systematic review provides a comprehensive analysis of the performance of AI systems in diagnosing liver fibrosis. Automatic diagnosis, staging, and risk stratification for liver fibrosis is currently possible considering the accuracy of the AI systems, which can overcome the limitations of non-invasive diagnosis methods.

Applications of Artificial Intelligence in the Automatic Diagnosis of Focal Liver Lesions: A Systematic Review.

BACKGROUND AND AIMS: Focal liver lesions (FLLs) are defined as abnormal solid or liquid masses differentiated from normal liver, frequently being clinically asymptomatic. The aim of this systematic review is to provide a comprehensive overview of current artificial intelligence (AI) applications, deep learning systems and convolutional neural networks, capable of performing a completely automated diagnosis of FLLs. METHODS: We searched PubMed, Cochrane Library, EMBASE, and WILEY databases using predefined keywords. Articles were screened for relevant publications about AI applications capable of automated diagnosis of FLLs. The search terms included: (focal liver lesions OR FLLs OR hepatic focal lesions OR liver focal lesions OR liver tumor OR hepatic tumor) AND (artificial intelligence OR machine learning OR neural networks OR deep learning OR automated diagnosis OR ultrasound OR US OR computer scan OR CT OR magnetic resonance imaging OR MRI OR computer-aided diagnosis OR automated computer tomography OR automated magnetic imaging). RESULTS: Our search identified a total of 32 articles analyzing complete automated imagistic diagnosis of FLLs, out of which 14 studies analyzing liver ultrasound images, 8 studies analyzing computer tomography images and 10 studies analyzing images obtained from magnetic resonance imaging. CONCLUSIONS: We found significant evidence demonstrating that implementing a complete automated system for FLLs diagnosis using AI-based applications is currently feasible. Various automated AI-based applications have been analyzed. However, there is no clear evidence about the superiority of any of the systems.

MBOAT7 rs641738 variant in metabolic-dysfunction-associated fatty liver disease and cardiovascular risk.

Introduction: Although metabolic-dysfunction-associated fatty liver disease (MAFLD) is associated with an increased cardiovascular risk, MAFLD predisposing genetic variants were not steadily related to cardiovascular events. Therefore, we aimed to assess whether membrane-bound O-acyltransferase domain-containing 7 (MBOAT7) rs641738 variant is associated with an increased cardiovascular risk in in MAFLD patients. Methods: We conducted an observational cross-sectional study including 77 subjects (38 MAFLD patients, 39 controls), between January-September 2020 using hepatic ultrasonography and SteatoTestTM to assess hepatic steatosis. Echocardiographic and Doppler ultrasound parameters were evaluated. Genomic DNA was extracted and rs641738 SNP was genotyped using TaqMan assays. Results: The rs641738 variant was not significantly associated with MAFLD, with a p-value of 0.803, 0.5265, 0.9535, and 0.5751 for codominant, dominant, recessive, and overdominant genotypes, respectively. The rs641738 variant overdominant genotype significantly predicted atherosclerotic cardiovascular disease (ASCVD) risk algorithm in univariate analysis (-4.3 [95% CI -8.55 - -0.55, p-value= 0.048]), but lost significance after multivariate analysis (-3.98 [95% CI -7.9 - -0.05, p-value= 0.053]). The rs641738 variant recessive genotype significantly predicted ActiTest in univariate analysis (0.0963 [95% CI 0.0244 - 0.1681, p-value= 0.009]), but lost significance after multivariate analysis (0.0828 [95% CI -0.016 - 0.1816, p-value= 0.105]). Conclusion: No significant association was observed between rs641738 variant and MAFLD in the studied population. The rs641738 variant was found to predict ASCVD risk score and ActiTest in univariate linear regression analysis. However, the significance of both associations was lost after performing multivariate analysis.

Automatic Diagnosis of High-Resolution Esophageal Manometry Using Artificial Intelligence.

BACKGROUND AND AIMS: High-resolution esophageal manometry (HREM) is the gold standard procedure used for the diagnosis of esophageal motility disorders (EMD). Artificial intelligence (AI) might provide an efficient solution for the automatic diagnosis of EMD by improving the subjective interpretation of HREM images. The aim of our study was to develop an AI-based system, using neural networks, for the automatic diagnosis of HREM images, based on one wet swallow raw image. METHODS: In the first phase of the study, the manometry recordings of our patients were retrospectively analyzed by three experienced gastroenterologists, to verify and confirm the correct diagnosis. In the second phase of the study raw images were used to train an artificial neural network. We selected only those tracings with ten test swallows that were available for analysis, including a total of 1570 images. We had 10 diagnosis categories, as follows: normal, type I achalasia, type II achalasia, type III achalasia, esophago-gastric junction outflow obstruction, jackhammer oesophagus, absent contractility, distal esophageal spasm, ineffective esophageal motility, and fragmented peristalsis, based on Chicago classification v3.0 for EMDs. RESULTS: The raw images were cropped, binarized, and automatically divided in 3 parts: training, testing, validation. We used Inception V3 CNN model, pre-trained on ImageNet. We developed a custom classification layer, that allowed the CNN to classify each wet swallow image from the HREM system into one of the diagnosis categories mentioned above. Our algorithm was highly accurate, with an overall precision of more than 93%. CONCLUSION: Our neural network approach using HREM images resulted in a high accuracy automatic diagnosis of EMDs.

Low Atrial Rhythm in a Large Cohort of Children from Transylvania, Romania.

Low atrial rhythm (LAR) is an ectopic rhythm originating in the lower part of the right or left atrium. Prior observational studies attempted to quantify the prevalence of low atrial rhythm in the pediatric population, but the observed prevalence was highly variable with relatively small sample sizes. We aimed to characterize low atrial rhythm and determine its prevalence in a large population of 24,316 asymptomatic children from northwestern Transylvania. We found a prevalence of 0.6% (145 children) for low atrial rhythm. Children with LAR had a significantly lower heart rate (mean 78.6 ± 8.3 bpm), than the control sinus rhythm group (85.02 ± 4.5 bpm). Furthermore, a shorter PR interval was seen in children with LAR (132.7 ± 12.7 ms) than in the children from the control group (141.7 ± 5.4; p = 0.0001).There was no significant association between gender and the presence of left LAR (LLAR) or right LAR (RLAR) (p = 0.5876). The heart rate of children with LLAR was significantly higher (81.7 ± 11.6 bpm) than that of the children with LRAR (77.6 ± 11.1 bpm) (p = 0.037). Pediatric cardiologists should recognize low atrial rhythm and be aware that asymptomatic, healthy children can exhibit this pattern, which does not require therapeutic intervention.

Deep Learning and Antibiotic Resistance.

Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless all known antibiotics in the fight against bacterial infections. Although bacterial resistance appeared before any human life form, this process has accelerated in the past years. Important causes of AR in modern times could be the over-prescription of antibiotics, the presence of faulty infection-prevention strategies, pollution in overcrowded areas, or the use of antibiotics in agriculture and farming, together with a decreased interest from the pharmaceutical industry in researching and testing new antibiotics. The last cause is primarily due to the high costs of developing antibiotics. The aim of the present review is to highlight the techniques that are being developed for the identification of new antibiotics to assist this lengthy process, using artificial intelligence (AI). AI can shorten the preclinical phase by rapidly generating many substances based on algorithms created by machine learning (ML) through techniques such as neural networks (NN) or deep learning (DL). Recently, a text mining system that incorporates DL algorithms was used to help and speed up the data curation process. Moreover, new and old methods are being used to identify new antibiotics, such as the combination of quantitative structure-activity relationship (QSAR) methods with ML or Raman spectroscopy and MALDI-TOF MS combined with NN, offering faster and easier interpretation of results. Thus, AI techniques are important additional tools for researchers and clinicians in the race for new methods of overcoming bacterial resistance.

Atherogenic Index of Plasma in Non-Alcoholic Fatty Liver Disease: Systematic Review and Meta-Analysis.

(1) Background: Approximately a billion people worldwide are affected by NAFLD, which places a high clinical burden and financial cost on society. Liver biopsy is the gold standard for diagnosing NAFLD, but its invasivity limits the early diagnosis of NAFLD. Hence, it is important to look for alternate techniques in detecting and diagnosing NAFLD. NAFLD is associated with atherosclerosis. The purpose of this study was to assess the effectiveness of the atherogenic index of plasma (AIP) as a non-invasive modality for predicting NAFLD. (2) Methods: A search using electronic databases PubMed, EMBASE, and Scopus was carried out to find observational studies, looking at research that had been published up until the date of 11 May 2022. The included studies' quality, risk of bias, and internal validity were evaluated using the QUADAS-2 quality assessment tool. The key summary outcomes were the mean difference (MD) and area under the curve (AUC). (3) Results: A total of eight studies (81,178 participants) were included in our review, while 17% of the included participants had NAFLD. A sex distribution of 57.8% men and 42.2% women was observed. The AIP between NAFLD and the controls was not significant (MD 0.212 [95% CI 0.231-0.655]). A significant MD in AIP between the males and females with NAFLD was observed (MD 0.246 [95% CI 0.098-0.395]). The AIP predicted NAFLD with an AUC of 0.764 as well as in males (AUC 0.761) and females (AUC 0.733). (4) Conclusions: There was a substantial MD in the AIP between both sexes, but there was no significant difference in the AIP values between patients with NAFLD and the controls. The AIP is a reliable biomarker for the diagnosis of NAFLD since its ability to predict the development of NAFLD was comparable to that of the other biomarkers.