-
Computational and Structural... 2021The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in>3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are... (Review)
Review
The worldwide health crisis caused by the SARS-Cov-2 virus has resulted in>3 million deaths so far. Improving early screening, diagnosis and prognosis of the disease are critical steps in assisting healthcare professionals to save lives during this pandemic. Since WHO declared the COVID-19 outbreak as a pandemic, several studies have been conducted using Artificial Intelligence techniques to optimize these steps on clinical settings in terms of quality, accuracy and most importantly time. The objective of this study is to conduct a systematic literature review on published and preprint reports of Artificial Intelligence models developed and validated for screening, diagnosis and prognosis of the coronavirus disease 2019. We included 101 studies, published from January 1st, 2020 to December 30th, 2020, that developed AI prediction models which can be applied in the clinical setting. We identified in total 14 models for screening, 38 diagnostic models for detecting COVID-19 and 50 prognostic models for predicting ICU need, ventilator need, mortality risk, severity assessment or hospital length stay. Moreover, 43 studies were based on medical imaging and 58 studies on the use of clinical parameters, laboratory results or demographic features. Several heterogeneous predictors derived from multimodal data were identified. Analysis of these multimodal data, captured from various sources, in terms of prominence for each category of the included studies, was performed. Finally, Risk of Bias (RoB) analysis was also conducted to examine the applicability of the included studies in the clinical setting and assist healthcare providers, guideline developers, and policymakers.
PubMed: 34025952
DOI: 10.1016/j.csbj.2021.05.010 -
Scandinavian Journal of Clinical and... Oct 2020The Coronavirus Disease (COVID-19) pandemic first broke out in December 2019 in Wuhan, China, and has now spread worldwide. Laboratory findings have been only partially... (Meta-Analysis)
Meta-Analysis
The Coronavirus Disease (COVID-19) pandemic first broke out in December 2019 in Wuhan, China, and has now spread worldwide. Laboratory findings have been only partially described in some observational studies. To date, more comprehensive systematic reviews of laboratory findings on COVID-19 are missing. We performed a systematic review with a meta-analysis to assess laboratory findings in patients with COVID-19. Observational studies from three databases were selected. We calculated pooled proportions and 95% confidence interval (95% CI) using the random-effects model meta-analysis. A total of 1106 articles were identified from PubMed, Web of Science, CNKI (China), and other sources. After screening, 28 and 7 studies were selected for a systematic review and a meta-analysis, respectively. Of the 4,663 patients included, the most prevalent laboratory finding was increased C-reactive protein (CRP; 73.6%, 95% CI 65.0-81.3%), followed by decreased albumin (62.9%, 95% CI 28.3-91.2%), increased erythrocyte sedimentation rate (61.2%, 95% CI 41.3-81.0%), decreased eosinophils (58.4%, 95% CI 46.5-69.8%), increased interleukin-6 (53.1%, 95% CI 36.0-70.0%), lymphopenia (47.9%, 95% CI 41.6-54.9%), and increased lactate dehydrogenase (LDH; 46.2%, 95% CI 37.9-54.7%). A meta-analysis of seven studies with 1905 patients showed that increased CRP (OR 3.0, 95% CI: 2.1-4.4), lymphopenia (OR 4.5, 95% CI: 3.3-6.0), and increased LDH (OR 6.7, 95% CI: 2.4-18.9) were significantly associated with severity. These results demonstrated that more attention is warranted when interpreting laboratory findings in patients with COVID-19. Patients with elevated CRP levels, lymphopenia, or elevated LDH require proper management and, if necessary, transfer to the intensive care unit.
Topics: Adult; Betacoronavirus; Biomarkers; Blood Sedimentation; C-Reactive Protein; COVID-19; China; Coronavirus Infections; Eosinophils; Female; Humans; Interleukin-6; L-Lactate Dehydrogenase; Lymphopenia; Male; Middle Aged; Observational Studies as Topic; Pandemics; Pneumonia, Viral; SARS-CoV-2; Serum Albumin; Severity of Illness Index
PubMed: 32449374
DOI: 10.1080/00365513.2020.1768587 -
Mayo Clinic Proceedings. Innovations,... Apr 2021To evaluate differences in thromboinflammatory biomarkers between patients with severe coronavirus disease 2019 (COVID-19) infection/death and mild infection.
OBJECTIVE
To evaluate differences in thromboinflammatory biomarkers between patients with severe coronavirus disease 2019 (COVID-19) infection/death and mild infection.
PATIENTS AND METHODS
MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, EBSCO, Web of Science, and CINAHL databases were searched for studies comparing thromboinflammatory biomarkers in COVID-19 among patients with severe COVID-19 disease or death (severe/nonsurvivors) and those with nonsevere disease or survivors (nonsevere/survivors) from January 1, 2020, through July 11, 2020. Inclusion criteria were (1) hospitalized patients 18 years or older comparing severe/nonsurvivors vs nonsevere/survivors and (2) biomarkers of inflammation and/or thrombosis. A random-effects model was used to estimate the weighted mean difference (WMD) between the 2 groups of COVID-19 severity.
RESULTS
We included 75 studies with 17,052 patients. The severe/nonsurvivor group was older, had a greater proportion of men, and had a higher prevalence of hypertension, diabetes, cardiac or cerebrovascular disease, chronic kidney disease, malignancy, and chronic obstructive pulmonary disease. Thromboinflammatory biomarkers were significantly higher in patients with severe disease, including D-dimer (WMD, 0.60; 95% CI, 0.49 to 0.71; =83.85%), fibrinogen (WMD, 0.42; 95% CI, 0.18 to 0.67; =61.88%; <.001), C-reactive protein (CRP) (WMD, 35.74; 95% CI, 30.16 to 41.31; =85.27%), high-sensitivity CRP (WMD, 62.68; 95% CI, 45.27 to 80.09; =0%), interleukin 6 (WMD, 22.81; 95% CI, 17.90 to 27.72; =90.42%), and ferritin (WMD, 506.15; 95% CI, 356.24 to 656.06; =52.02%). Moderate to significant heterogeneity was observed for all parameters ( > 25%). Subanalysis based on disease severity, mortality, and geographic region of the studies revealed similar inferences.
CONCLUSION
Thromboinflammatory biomarkers (D-dimer, fibrinogen, CRP, high-sensitivity CRP, ferritin, and interleukin 6) and marker of end-organ damage (high-sensitivity troponin I) are associated with increased severity and mortality in COVID-19 infection.
PubMed: 33585800
DOI: 10.1016/j.mayocpiqo.2021.01.009 -
Journal of Pediatric Hematology/oncology Aug 2021Eculizumab is indicated for the treatment of paroxysmal nocturnal hemoglobinuria (PNH). This study aimed to evaluate the efficacy and safety of eculizumab in patients... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Eculizumab is indicated for the treatment of paroxysmal nocturnal hemoglobinuria (PNH). This study aimed to evaluate the efficacy and safety of eculizumab in patients with PNH.
METHODS
PubMed, EMBASE, The Cochrane Library, and ClinicalTrials.gov were searched for prospective interventional studies treating PNH with eculizumab. The primary outcome was the change in lactate dehydrogenase (LDH) levels, whereas secondary outcomes included the change in hemoglobin (Hb) levels, transfusion rates, and adverse drug events.
RESULTS
Patients (n=235) from 6 studies were included in this meta-analysis. LDH and Hb levels and transfusion rates decreased significantly at 12, 26 weeks, 12, 15, and >15 months. The most frequent adverse events included nasopharyngitis (effect size [ES]: 0.53; 95% confidence intervals [CI]: 0.47 to 0.60; P=0.00), headache (ES: 0.47; 95% CI: 0.25 to 0.69; P=0.00), upper respiratory tract infection (ES: 0.37; 95% CI: 0.27 to 0.46; P=0.00), nausea (ES: 0.31; 95% CI: 0.24 to 0.38; P=0.00), fatigue, diarrhea, cough, pyrexia, abdominal pain, pain in extremities, and contusion.
CONCLUSION
Eculizumab is an effective and well-tolerated treatment for patients with PNH. It is effective at decreasing LDH levels and transfusion rates while increasing Hb levels. Further studies are needed to explore the safety of eculizumab.
Topics: Antibodies, Monoclonal, Humanized; Complement Inactivating Agents; Hemoglobinuria, Paroxysmal; Humans; L-Lactate Dehydrogenase; Treatment Outcome
PubMed: 33902068
DOI: 10.1097/MPH.0000000000002178 -
Clinical Ophthalmology (Auckland, N.Z.) 2022This study aims to identify the available literature describing the utilization of artificial intelligence (AI) as a clinical tool in uveal diseases. (Review)
Review
PURPOSE
This study aims to identify the available literature describing the utilization of artificial intelligence (AI) as a clinical tool in uveal diseases.
METHODS
A comprehensive literature search was conducted in 5 electronic databases, finding studies relating to AI and uveal diseases.
RESULTS
After screening 10,258 studies,18 studies met the inclusion criteria. Uveal melanoma (44%) and uveitis (56%) were the two uveal diseases examined. Ten studies (56%) used complex AI, while 13 studies (72%) used regression methods. Lactate dehydrogenase (LDH), found in 50% of studies concerning uveal melanoma, was the only biomarker that overlapped in multiple studies. However, 94% of studies highlighted that the biomarkers of interest were significant.
CONCLUSION
This study highlights the value of using complex and simple AI tools as a clinical tool in uveal diseases. Particularly, complex AI methods can be used to weigh the merit of significant biomarkers, such as LDH, in order to create staging tools and predict treatment outcomes.
PubMed: 36065357
DOI: 10.2147/OPTH.S377358 -
Infectious Diseases and Therapy Sep 2020The ability to predict likely prognosis and infectiousness for patients with COVID-19 would aid patient management decisions. Diagnosis is usually via real-time PCR, and... (Review)
Review
BACKGROUND
The ability to predict likely prognosis and infectiousness for patients with COVID-19 would aid patient management decisions. Diagnosis is usually via real-time PCR, and it is unclear whether the semi-quantitative capability of this method, determining viral load through cycle threshold (Ct) values, can be leveraged.
OBJECTIVES
We aim to review available knowledge on correlations between SARS-COV-2 Ct values and patient- or healthcare-related outcomes to determine whether Ct values provide useful clinical information.
SOURCES
A PubMed search was conducted on 1 June 2020 based on a search strategy of (Ct value OR viral load) AND SARS-CoV-2. Data were extracted from studies reporting on the presence or absence of an association between Ct values, or viral loads determined via Ct value, and clinical outcomes.
CONTENT
Data from 18 studies were relevant for inclusion. One study reported on the correlation between Ct values and mortality and one study reported on the correlation between Ct values and progression to severe disease; both reported a significant association (p < 0.001 and p = 0.008, respectively). Fourteen studies reported on the correlation between Ct value or viral loads determined via Ct value and disease severity, and an association was observed in eight (57%) studies. Studies reporting on the correlation of viral load with biochemical and haematological markers showed an association with at least one marker, including increased lactate dehydrogenase (n = 4), decreased lymphocytes (n = 3) and increased high-sensitivity troponin I (n = 2). Two studies reporting on the correlation with infectivity showed that lower Ct values were associated with higher viral culture positivity.
IMPLICATIONS
Data suggest that lower Ct values may be associated with worse outcomes and that Ct values may be useful in predicting the clinical course and prognosis of patients with COVID-19; however, further studies are warranted to confirm clinical value.
PubMed: 32725536
DOI: 10.1007/s40121-020-00324-3 -
Frontiers in Pharmacology 2022This study aimed to evaluate the intervention effect of curcumin in myocardial infarction rodent models. A systematic retrieval of relevant studies on curcumin...
This study aimed to evaluate the intervention effect of curcumin in myocardial infarction rodent models. A systematic retrieval of relevant studies on curcumin intervention in rats or mice myocardial infarction models was conducted, and the data were extracted. The outcome indicators included biochemical blood indicators, such as creatine kinase (CK), creatine kinase isoenzyme (CK-MB), malondialdehyde (MDA), lactate dehydrogenase (LDH) and superoxide dismutase (SOD), as well as cardiac tissue structure indicators, such as left ventricular weight to body weight ratio (LVW/BW), apoptosis index, left ventricular end-diastolic dimension (LVEDD), left ventricular end-systolic diameter (LVESD), and myocardial infarction area, and hemodynamic indexes, such as systolic blood pressure (SBP), diastolic blood pressure (DBP), left ventricular end-diastolic pressure (LVEDP), left ventricular ejection fraction (LVEF), left ventricular fractional shortening (LVFS), maximum rate of left ventricular pressure rise (+dp/dtmax), and maximum rate of left ventricular pressure decline (-dp/dtmax). These results were then analyzed by meta-analysis. Studies were evaluated for methodological quality using the syrcle's bias risk tool. A total of 24 studies were included in the meta-analysis. The quality assessment of included studies revealed that the evidence was low quality and none of studies was judged as having a low risk of bias across all domains. The results revealed that curcumin could reduce CK-MB, CK, LDH, and MDA levels. They also revealed that it could lower SBP, DBP, LVEDP, LVW/BW, apoptosis index, LVEDD, LVESD, and myocardial infarction area and increase LVEF, LVFS, +dp/dtmax, and-dp/dtmax. However, it had no significant impact on the heart rate and the levels of SOD in the models. Curcumin alleviates myocardial injury and oxidative stress in myocardial infarction rodent models in terms of blood biochemistry indicators, improves the diastolic and systolic capacity of the ventricle in terms of hemodynamic indexes, and reduces the necrosis and apoptosis of cardiomyocytes in terms of tissue structure. The methodological quality of the studies was low and additional research is warranted.
PubMed: 36330084
DOI: 10.3389/fphar.2022.999386 -
Postgraduate Medical Journal Jun 2022This meta-analysis aimed to evaluate the prognostic performance of elevated lactate dehydrogenase (LDH) in patients with COVID-19. (Meta-Analysis)
Meta-Analysis
PURPOSE
This meta-analysis aimed to evaluate the prognostic performance of elevated lactate dehydrogenase (LDH) in patients with COVID-19.
METHODS
A systematic literature search was performed using PubMed, Embase and EuropePMC on 19 November 2020. The outcome of interest was composite poor outcome, defined as a combined endpoint of mortality, severity, need for invasive mechanical ventilation and need for intensive care unit care. Severity followed the included studies' criteria.
RESULTS
There are 10 399 patients from 21 studies. Elevated LDH was present in 44% (34%-53%) of the patients. Meta-regression analysis showed that diabetes was correlated with elevated LDH (OR 1.01 (95% CI 1.00 to 1.02), p=0.038), but not age (p=0.710), male (p=0.068) and hypertension (p=0.969). Meta-analysis showed that elevated LDH was associated with composite poor outcome (OR 5.33 (95% CI 3.90 to 7.31), p<0.001; I: 77.5%). Subgroup analysis showed that elevated LDH increased mortality (OR 4.22 (95% CI 2.49 to 7.14), p<0.001; I: 89%). Elevated LDH has a sensitivity of 0.74 (95% CI 0.60 to 0.85), specificity of 0.69 (95% CI 0.58 to 0.78), positive likelihood ratio of 2.4 (95% CI 1.9 to 2.9), negative likelihood ratio of 0.38 (95% CI 0.26 to 0.55), diagnostic OR of 6 (95% CI 4 to 9) and area under curve of 0.77 (95% CI 0.73 to 0.80). Elevated LDH would indicate a 44% posterior probability and non-elevated LDH would in indicate 11% posterior probability for poor prognosis. Meta-regression analysis showed that age, male, hypertension and diabetes did not contribute to the heterogeneity of the analyses.
CONCLUSION
LDH was associated with poor prognosis in patients with COVID-19.
PROSPERO REGISTRATION NUMBER
CRD42020221594.
Topics: COVID-19; Diabetes Mellitus; Humans; Hypertension; L-Lactate Dehydrogenase; Lactate Dehydrogenases; Male; Prognosis
PubMed: 33452143
DOI: 10.1136/postgradmedj-2020-139542 -
Journal of Biochemical and Molecular... Mar 2023Inhibition of cholinesterase (ChE) activity has been long considered as the main diagnostic method of organophosphate (OP) and carbamate pesticides poisoning; however,... (Review)
Review
Inhibition of cholinesterase (ChE) activity has been long considered as the main diagnostic method of organophosphate (OP) and carbamate pesticides poisoning; however, it has been shown that ChE activity may also be altered due to exposure to other non-organophosphorus toxicants and variety of different medical conditions. Hence, to avoid misdiagnosis, we aimed to systematically review available documents to look for additional biomarkers of OP and carbamate poisoning. The electronic databases in addition to Google scholar were searched for eligible articles on March 2022 using "organophosphate," "carbamate," and "biomarker" including all their similar terms. After collecting the relevant documents, the data were extracted and described qualitatively. In total, data of 66 articles from 51 human and 15 animal studies were extracted. Findings demonstrated that enzymes such as β-glucuronidase, neuropathy target esterase, amylase, and lipase, in addition to hematological indicators such as CBC, CRP, lactate dehydrogenase, and CPK have high sensitivity and accuracy in the diagnosis of OP poisoning. Findings suggest that using various markers for diagnosis of OP intoxication is helpful for appropriate management, and early identifying the patients at risk of death. The suggested biomarkers also help to avoid misdiagnosis of OP poisoning with other similar conditions.
Topics: Animals; Humans; Pesticides; Organophosphates; Organophosphate Poisoning; Carbamates; Biomarkers
PubMed: 36524544
DOI: 10.1002/jbt.23285 -
Journal of Thoracic Disease Dec 2020Since December 2019, the pneumonia cases infected with 2019 novel coronavirus have appeared, posing a critical threat to global health. In this study, we performed a... (Review)
Review
Since December 2019, the pneumonia cases infected with 2019 novel coronavirus have appeared, posing a critical threat to global health. In this study, we performed a meta-analysis to discover the different clinical characteristics between severe and non-severe patients with COVID-19 to find the potential risk factors and predictors of this disease's severity, as well as to serve as a guidance for subsequent epidemic prevention and control work. PubMed, Cochrane Library, Medline, Embase and other databases were searched to collect studies on the difference of clinical characteristics of severe and non-severe patients. Meta-analysis was performed using RevMan 5.3 software, and the funnel plots could be made to evaluate the publication bias. P>0.05 means no statistical significance. Furthermore, a meta-regression analysis was performed by using Stata 15.0 to find the potential factors of the high degree of heterogeneity (I>50%). Sixteen studies have been included, with 1,172 severe patients and 2,803 non-severe patients. Compared with non-severe patients, severe patients were more likely to have the symptoms of dyspnea, hemoptysis, and the complications of ARDS, shock, secondary infection, acute kidney injury, and acute cardiac injury. Interestingly, the former smokers were more prevalent in severe cases as compared to non-severe cases, but there was no difference between the two groups of 'current smokers'. Except for chronic liver disease and chronic kidney disease, the underlying comorbidities of hypertension, diabetes, cardiovascular disease, chronic obstructive pulmonary disease (COPD), malignancy, cerebrovascular disease, and HIV can make the disease worse. In terms of laboratory indicators, the decreased lymphocyte and platelet count, and the increased levels of white blood cell (WBC), D-dimer, creatine kinase, lactate dehydrogenase, procalcitonin, alanine aminotransferase, aspartate aminotransferase, and C-reactive protein were more prevalent in severe patients. Meta-regression analysis showed that patient age, gender, and proportion of severe cases did not significantly impact on the outcomes of any clinical indexes that showed high degree of heterogeneity in the meta-analysis. In conclusion, the severity of COVID-19 could be evaluated by, radiologic finding, some symptoms like dyspnea and hemoptysis, some laboratory indicators, and smoking history, especially the ex-smokers. Compared with non-severe patients, severe patients were more likely to have complications and comorbidities including hypertension, cardiovascular disease etc., which were the risk factors for the disease to be severer, but the chronic liver disease and chronic kidney disease were not associated the severity of COVID-19 in China.
PubMed: 33447431
DOI: 10.21037/jtd-20-1743