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World Journal of Emergency Surgery :... Dec 2023To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional... (Review)
Review
BACKGROUND
To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional methods. AA is a common cause of emergency department visits and abdominal surgeries. It is typically diagnosed through clinical assessments, laboratory tests, and imaging studies. However, traditional diagnostic methods can be time-consuming and inaccurate. Machine learning models have shown promise in improving diagnostic accuracy and predicting outcomes.
MAIN BODY
A systematic review following the PRISMA guidelines was conducted, searching PubMed, Embase, Scopus, and Web of Science databases. Studies were evaluated for risk of bias using the Prediction Model Risk of Bias Assessment Tool. Data points extracted included model type, input features, validation strategies, and key performance metrics.
RESULTS
In total, 29 studies were analyzed, out of which 21 focused on diagnosis, seven on prognosis, and one on both. Artificial neural networks (ANNs) were the most commonly employed algorithm for diagnosis. Both ANN and logistic regression were also widely used for categorizing types of AA. ANNs showed high performance in most cases, with accuracy rates often exceeding 80% and AUC values peaking at 0.985. The models also demonstrated promising results in predicting postoperative outcomes such as sepsis risk and ICU admission. Risk of bias was identified in a majority of studies, with selection bias and lack of internal validation being the most common issues.
CONCLUSION
AI algorithms demonstrate significant promise in diagnosing and prognosticating AA, often surpassing traditional methods and clinical scores such as the Alvarado scoring system in terms of speed and accuracy.
Topics: Adult; Humans; Artificial Intelligence; Appendicitis; Prognosis; Algorithms; Machine Learning; Acute Disease
PubMed: 38114983
DOI: 10.1186/s13017-023-00527-2 -
Journal of Tropical Medicine 2024To understand how congenital toxoplasmosis (CT) diagnosis has evolved over the years, we performed a systematic review and meta-analysis to summarize the kind of... (Review)
Review
OBJECTIVE
To understand how congenital toxoplasmosis (CT) diagnosis has evolved over the years, we performed a systematic review and meta-analysis to summarize the kind of analysis that has been employed for CT diagnosis.
METHODS
PubMed and Lilacs databases were used in order to access the kind of analysis that has been employed for CT diagnosis in several samples. Our search combined the following combining terms: "congenital toxoplasmosis" or "gestational toxoplasmosis" and "diagnosis" and "blood," "serum," "amniotic fluid," "placenta," or "colostrum." We extracted data on true positive, true negative, false positive, and false negative to generate pooled sensitivity, specificity, and diagnostic odds ratio (DOR). Random-effects models using MetaDTA were used for analysis.
RESULTS
Sixty-five articles were included in the study aiming for comparisons (75.4%), diagnosis performance (52.3%), diagnosis improvement (32.3%), or to distinguish acute/chronic infection phases (36.9%). Amniotic fluid (AF) and placenta were used in 36.9% and 10.8% of articles, respectively, targeting parasites and/or DNA. Blood was used in 86% of articles for enzymatic assays. Colostrum was used in one article to search for antibodies. In meta-analysis, PCR in AF showed the best performance for CT diagnosis based on the highest summary sensitivity (85.1%) and specificity (99.7%) added to lower magnitude heterogeneity.
CONCLUSION
Most of the assays being researched to diagnose CT are basically the same traditional approaches available for clinical purposes. The range in diagnostic performance and the challenges imposed by CT diagnosis indicate the need to better explore pregnancy samples in search of new possibilities for diagnostic tools. Exploring immunological markers and using bioinformatics tools and recombinant antigens should address the research needed for a new generation of diagnostic tools to face these challenges.
PubMed: 38419946
DOI: 10.1155/2024/1514178 -
Therapeutic Advances in Gastroenterology 2023Magnetically controlled capsule endoscopy (MCCE) is a non-invasive, painless, comfortable, and safe equipment to diagnose gastrointestinal diseases (GID), partially... (Review)
Review
BACKGROUND
Magnetically controlled capsule endoscopy (MCCE) is a non-invasive, painless, comfortable, and safe equipment to diagnose gastrointestinal diseases (GID), partially overcoming the shortcomings of conventional endoscopy and wireless capsule endoscopy (WCE). With advancements in technology, the main technical parameters of MCCE have continuously been improved, and MCCE has become more intelligent.
OBJECTIVES
The aim of this systematic review was to summarize the research progress of MCCE and artificial intelligence (AI) in the diagnosis and treatment of GID.
DATA SOURCES AND METHODS
We conducted a systematic search of PubMed and EMBASE for published studies on GID detection of MCCE, physical factors related to MCCE imaging quality, the application of AI in aiding MCCE, and its additional functions. We synergistically reviewed the included studies, extracted relevant data, and made comparisons.
RESULTS
MCCE was confirmed to have the same performance as conventional gastroscopy and WCE in detecting common GID, while it lacks research in detecting early gastric cancer (EGC). The body position and cleanliness of the gastrointestinal tract are the main factors affecting imaging quality. The applications of AI in screening intestinal diseases have been comprehensive, while in the detection of common gastric diseases such as ulcers, it has been developed. MCCE can perform some additional functions, such as observations of drug behavior in the stomach and drug damage to the gastric mucosa. Furthermore, it can be improved to perform a biopsy.
CONCLUSION
This comprehensive review showed that the MCCE technology has made great progress, but studies on GID detection and treatment by MCCE are in the primary stage. Further studies are required to confirm the performance of MCCE.
PubMed: 37900007
DOI: 10.1177/17562848231206991 -
Biomolecules Nov 2023Peripheral artery disease (PAD) involves atherosclerosis of the lower extremity arteries and is a major contributor to limb loss and death worldwide. Several studies... (Review)
Review
Peripheral artery disease (PAD) involves atherosclerosis of the lower extremity arteries and is a major contributor to limb loss and death worldwide. Several studies have demonstrated that interleukins (ILs) play an important role in the development and progression of PAD; however, a comprehensive literature review has not been performed. A systematic review was conducted and reported according to PRISMA guidelines. MEDLINE was searched from inception to 5 December 2022, and all studies assessing the association between ILs and PAD were included. We included 17 studies from a pool of 771 unique articles. Five pro-inflammatory ILs (IL-1β, IL-2, IL-5, IL-6, and IL-8) and one pro-atherogenic IL (IL-12) were positively correlated with PAD diagnosis and progression. In contrast, two anti-inflammatory ILs (IL-4 and IL-10) were protective against PAD diagnosis and adverse limb events. Specifically, IL-6 and IL-8 were the most strongly associated with PAD and can act as potential disease biomarkers to support the identification and treatment of PAD. Ongoing work to identify and validate diagnostic/prognostic inflammatory biomarkers for PAD has the potential to assist clinicians in identifying high-risk patients for further evaluation and management which could reduce the risk of adverse cardiovascular and limb events.
Topics: Humans; Interleukin-6; Prognosis; Interleukin-8; Peripheral Arterial Disease; Atherosclerosis; Biomarkers; Risk Factors
PubMed: 38002322
DOI: 10.3390/biom13111640 -
JACC. Cardiovascular Imaging Nov 2023Quantification of pulmonary edema and congestion is important to guide diagnosis and risk stratification, and to objectively evaluate new therapies in heart failure.... (Review)
Review
Quantification of pulmonary edema and congestion is important to guide diagnosis and risk stratification, and to objectively evaluate new therapies in heart failure. Herein, we review the validation, diagnostic performance, and clinical utility of noninvasive imaging modalities in this setting, including chest x-ray, lung ultrasound (LUS), computed tomography (CT), nuclear medicine imaging methods (positron emission tomography [PET], single photon emission CT), and magnetic resonance imaging (MRI). LUS is a clinically useful bedside modality, and fully quantitative methods (CT, MRI, PET) are likely to be important contributors to a more accurate and precise evaluation of new heart failure therapies and for clinical use in conjunction with cardiac imaging. There are only a limited number of studies evaluating pulmonary congestion during stress. Taken together, noninvasive imaging of pulmonary congestion provides utility for both clinical and research assessment, and continued refinement of methodologic accuracy, validation, and workflow has the potential to increase broader clinical adoption.
Topics: Humans; Pulmonary Edema; Predictive Value of Tests; Lung; Ultrasonography; Heart Failure
PubMed: 37632500
DOI: 10.1016/j.jcmg.2023.06.023 -
Journal of Clinical Medicine Aug 2023The use of radiomics and artificial intelligence applied for the diagnosis and monitoring of Alzheimer's disease has developed in recent years. However, this approach is... (Review)
Review
The use of radiomics and artificial intelligence applied for the diagnosis and monitoring of Alzheimer's disease has developed in recent years. However, this approach is not yet completely applicable in clinical practice. The aim of this paper is to provide a systematic analysis of the studies that have included the use of radiomics from different imaging techniques and artificial intelligence for the diagnosis and monitoring of Alzheimer's disease in order to improve the clinical outcomes and quality of life of older patients. A systematic review of the literature was conducted in February 2023, analyzing manuscripts and articles of the last 5 years from the PubMed, Scopus and Embase databases. All studies concerning discrimination among Alzheimer's disease, Mild Cognitive Impairment and healthy older people performing radiomics analysis through machine and deep learning were included. A total of 15 papers were included. The results showed a very good performance of this approach in the differentiating Alzheimer's disease patients-both at the dementia and pre-dementia phases of the disease-from healthy older people. In summary, radiomics and AI can be valuable tools for diagnosing and monitoring the progression of Alzheimer's disease, potentially leading to earlier and more accurate diagnosis and treatment. However, the results reported by this review should be read with great caution, keeping in mind that imaging alone is not enough to identify dementia due to Alzheimer's.
PubMed: 37629474
DOI: 10.3390/jcm12165432 -
Frontiers in Immunology 2023The utility of metagenomic next-generation sequencing (mNGS) in the diagnosis of tuberculous meningitis (TBM) remains uncertain. We performed a meta-analysis to... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
The utility of metagenomic next-generation sequencing (mNGS) in the diagnosis of tuberculous meningitis (TBM) remains uncertain. We performed a meta-analysis to comprehensively evaluate its diagnostic accuracy for the early diagnosis of TBM.
METHODS
English (PubMed, Medline, Web of Science, Cochrane Library, and Embase) and Chinese (CNKI, Wanfang, and CBM) databases were searched for relevant studies assessing the diagnostic accuracy of mNGS for TBM. Review Manager was used to evaluate the quality of the included studies, and Stata was used to perform the statistical analysis.
RESULTS
Of 495 relevant articles retrieved, eight studies involving 693 participants (348 with and 345 without TBM) met the inclusion criteria and were included in the meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the summary receiver-operating characteristic curve of mNGS for diagnosing TBM were 62% (95% confidence interval [CI]: 0.46-0.76), 99% (95% CI: 0.94-1.00), 139.08 (95% CI: 8.54-2266), 0.38 (95% CI: 0.25-0.58), 364.89 (95% CI: 18.39-7239), and 0.97 (95% CI: 0.95-0.98), respectively.
CONCLUSIONS
mNGS showed good specificity but moderate sensitivity; therefore, a more sensitive test should be developed to assist in the diagnosis of TBM.
Topics: Humans; Tuberculosis, Meningeal; Sensitivity and Specificity; ROC Curve; High-Throughput Nucleotide Sequencing; Databases, Factual
PubMed: 37822937
DOI: 10.3389/fimmu.2023.1223675 -
Clinical and Experimental Medicine Aug 2023Plasmatic presepsin (PSP) is a novel biomarker reported to be useful for sepsis diagnosis and prognosis. During the pandemic, only few studies highlighted a possible... (Meta-Analysis)
Meta-Analysis Review
Plasmatic presepsin (PSP) is a novel biomarker reported to be useful for sepsis diagnosis and prognosis. During the pandemic, only few studies highlighted a possible correlation between PSP and COVID-19 severity, but results remain inconsistent. The present study aims to establish the correlation between PSP and COVID-19 severity. English-language papers assessing a correlation between COVID-19 and PSP from MEDLINE, PubMed, Google Scholar, Cochrane Library, MeSH, LitCovid NLM, EMBASE, CINAHL Plus and the World Health Organization (WHO) website, published from January 2020 were considered with no publication date limitations. Two independent reviewers performed data abstraction and quality assessment, and one reviewer resolved inconsistencies. The protocol was registered on PROSPERO (CRD42022325971).Fifteen articles met our eligibility criteria. The aggregate study population included 1373 COVID-19 patients who had undergone a PSP assessment. The random-effect meta-analysis was performed in 7 out of 15 selected studies, considering only those reporting the mean PSP levels in low- and high-severity cases (n = 707).The results showed that the pooled mean difference of PSP levels between high- and low-severity COVID-19 patients was 441.70 pg/ml (95%CI: 150.40-732.99 pg/ml).Our data show that presepsin is a promising biomarker that can express COVID-19 severity.
Topics: Humans; COVID-19; Prognosis; Biomarkers; Pandemics; Sepsis; Peptide Fragments; Lipopolysaccharide Receptors
PubMed: 36380007
DOI: 10.1007/s10238-022-00936-8 -
Best Practice & Research. Clinical... Aug 2023Of all neonates, 21% are delivered by cesarean section (CS). A long-term maternal complication of an SC is a uterine niche. The aim of this review is to provide an... (Review)
Review
Of all neonates, 21% are delivered by cesarean section (CS). A long-term maternal complication of an SC is a uterine niche. The aim of this review is to provide an overview of the current literature on imaging techniques and niche-related symptomatology. We performed systematic searches on imaging and niche symptoms. For both searches, 87 new studies were included. Niche evaluation by transvaginal sonography (TVS) or contrast sonohysterography (SHG) proved superior over hysteroscopy or magnetic resonance imaging. Studies that used SHG in a random population identified a niche prevalence of 42%-84%. Niche prevalence differed based on niche definition, symptomatology, and imaging technique. Most studies reported an association with gynecological symptoms, poor reproductive outcomes, obstetrical complications, and reduced quality of life. In conclusion, non-invasive TVS and SHG are the superior imaging modalities to diagnose a niche. Niches are prevalent and strongly associated with gynecological symptoms and poor reproductive outcomes.
Topics: Infant, Newborn; Pregnancy; Female; Humans; Cesarean Section; Quality of Life; Uterus; Hysteroscopy; Ultrasonography; Cicatrix
PubMed: 37506497
DOI: 10.1016/j.bpobgyn.2023.102390 -
Insights Into Imaging Jul 2023We aimed to present the state of the art of CT- and MRI-based radiomics in the context of ovarian cancer (OC), with a focus on the methodological quality of these... (Review)
Review
OBJECTIVES
We aimed to present the state of the art of CT- and MRI-based radiomics in the context of ovarian cancer (OC), with a focus on the methodological quality of these studies and the clinical utility of these proposed radiomics models.
METHODS
Original articles investigating radiomics in OC published in PubMed, Embase, Web of Science, and the Cochrane Library between January 1, 2002, and January 6, 2023, were extracted. The methodological quality was evaluated using the radiomics quality score (RQS) and Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pairwise correlation analyses were performed to compare the methodological quality, baseline information, and performance metrics. Additional meta-analyses of studies exploring differential diagnoses and prognostic prediction in patients with OC were performed separately.
RESULTS
Fifty-seven studies encompassing 11,693 patients were included. The mean RQS was 30.7% (range - 4 to 22); less than 25% of studies had a high risk of bias and applicability concerns in each domain of QUADAS-2. A high RQS was significantly associated with a low QUADAS-2 risk and recent publication year. Significantly higher performance metrics were observed in studies examining differential diagnosis; 16 such studies as well as 13 exploring prognostic prediction were included in a separate meta-analysis, which revealed diagnostic odds ratios of 25.76 (95% confidence interval (CI) 13.50-49.13) and 12.55 (95% CI 8.38-18.77), respectively.
CONCLUSION
Current evidence suggests that the methodological quality of OC-related radiomics studies is unsatisfactory. Radiomics analysis based on CT and MRI showed promising results in terms of differential diagnosis and prognostic prediction.
CRITICAL RELEVANCE STATEMENT
Radiomics analysis has potential clinical utility; however, shortcomings persist in existing studies in terms of reproducibility. We suggest that future radiomics studies should be more standardized to better bridge the gap between concepts and clinical applications.
PubMed: 37395888
DOI: 10.1186/s13244-023-01464-z