scholarly journals Reliability of ultrasound versus digital vaginal examination in detecting cervical dilatation during labor: a diagnostic test accuracy systematic review

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Zaynab Mohaghegh ◽  
Shayesteh Jahanfar ◽  
Parvin Abedi ◽  
Mohamed A. Abd El Aziz
Keyword(s):  
Systematic Review ◽  
Web Of Science ◽  
Meta Analysis ◽  
Intraclass Correlation ◽  
Total Sample ◽  
Test Accuracy ◽  
Cervical Dilation ◽  
Nulliparous Women ◽  
Perineal Ultrasonography ◽  
Digital Vaginal Examination

Abstract Background This systematic review aimed to investigate the reliability of ultrasound method compared with digital vaginal examinations in detecting cervical dilation. Methods We searched Cochrane (CENTRAL), MEDLINE, EMBASE, CINAHL, ISI Web of Science Core Collection, Trip Database, PubMed, DARE and NHS EED, HTA, and PROSPERO. Ten observational studies with a total sample size of 856 were included in the meta-analysis. Results The intraclass correlation coefficient (ICC) values ranged between 0.21 and 0.69. The fixed-effect models for the ultrasound test showed an average of ICC (r = 0.32 (95% CI 0.26–0.38). Correlation between two methods was poor (r = 0.359, 95% CI 0.26–0.44). In nulliparous and multigravida participants the correlation between ultrasound measurements and digital examinations was (r = 0.349, 95% CI 0.25–0.43) and ICC (r = 0.676, 95% CI 0.419–0.833), respectively. Conclusion Trans-perineal ultrasonography seems to be a reliable method for assessing labor progression in multigravida women, but its usage in nulliparous women needs further studies.

Is jaw fractal dimension a reliable biomarker for osteoporosis screening? A systematic review and meta-analysis of diagnostic test accuracy studies

2021 ◽  
Author(s):  
Davi de Sá Cavalcante ◽  
Paulo Goberlânio de Barros Silva ◽  
Francisco Samuel Rodrigues Carvalho ◽  
Ana Rosa Pinto Quidute ◽  
Lúcio Mitsuo Kurita ◽  
...  
Keyword(s):  
Systematic Review ◽  
Fractal Dimension ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Grey Literature ◽  
High Sensitivity ◽  
Total Sample ◽  
Control Group ◽  
Test Accuracy ◽  
Osteoporosis Screening

Objective: To summarize the evidence on the feasibility of maxillomandibular imaging exams-related fractal dimension (FD) in screening patients with osteoporosis. Methods: This registered systematic review followed the PRISMA-DTA statement. High sensitivity search strategies were developed for six primary databases and grey literature. QUADAS-2 items evaluated the risk of bias, and the GRADE approach assessed the evidence certainty. Results: From 1,034 records initially identified through database searching, four studies were included (total sample of 747 patients [osteoporosis, 136; control group, 611]). The meta-analysis showed that the overall sensitivity and specificity of the FD were 86.17 and 72.68%, respectively. In general, all studies showed low RoB and applicability concern. The certainty of the evidence was very low to moderate. Conclusions: This systematic review showed that the jaw-related FD presented sensitivity and specificity values higher than 70%, and its sensitivity in osteoporosis screening was a better parameter than specificity.

Diagnostic test accuracy for use of machine learning in diagnosis of autism spectrum disorder: A Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Sun Jae Moon ◽  
Jin Seub Hwang ◽  
Rajesh Kana ◽  
John Torous ◽  
Jung Won Kim
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Meta Analysis ◽  
Learning Algorithms ◽  
Structural Mri ◽  
Autism Spectrum ◽  
Machine Learning Algorithms ◽  
Spectrum Disorder ◽  
Test Accuracy

BACKGROUND Over the recent years, machine learning algorithms have been more widely and increasingly applied in biomedical fields. In particular, its application has been drawing more attention in the field of psychiatry, for instance, as diagnostic tests/tools for autism spectrum disorder. However, given its complexity and potential clinical implications, there is ongoing need for further research on its accuracy. OBJECTIVE The current study aims to summarize the evidence for the accuracy of use of machine learning algorithms in diagnosing autism spectrum disorder (ASD) through systematic review and meta-analysis. METHODS MEDLINE, Embase, CINAHL Complete (with OpenDissertations), PsyINFO and IEEE Xplore Digital Library databases were searched on November 28th, 2018. Studies, which used a machine learning algorithm partially or fully in classifying ASD from controls and provided accuracy measures, were included in our analysis. Bivariate random effects model was applied to the pooled data in meta-analysis. Subgroup analysis was used to investigate and resolve the source of heterogeneity between studies. True-positive, false-positive, false negative and true-negative values from individual studies were used to calculate the pooled sensitivity and specificity values, draw SROC curves, and obtain area under the curve (AUC) and partial AUC. RESULTS A total of 43 studies were included for the final analysis, of which meta-analysis was performed on 40 studies (53 samples with 12,128 participants). A structural MRI subgroup meta-analysis (12 samples with 1,776 participants) showed the sensitivity at 0.83 (95% CI-0.76 to 0.89), specificity at 0.84 (95% CI -0.74 to 0.91), and AUC/pAUC at 0.90/0.83. An fMRI/deep neural network (DNN) subgroup meta-analysis (five samples with 1,345 participants) showed the sensitivity at 0.69 (95% CI- 0.62 to 0.75), the specificity at 0.66 (95% CI -0.61 to 0.70), and AUC/pAUC at 0.71/0.67. CONCLUSIONS Machine learning algorithms that used structural MRI features in diagnosis of ASD were shown to have accuracy that is similar to currently used diagnostic tools.

scholarly journals Detection of three pandemic causing coronaviruses from non-respiratory samples: systematic review and meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chandan Mishra ◽  
Suneeta Meena ◽  
Jitendra Kumar Meena ◽  
Suman Tiwari ◽  
Purva Mathur
Keyword(s):  
Systematic Review ◽  
Detection Rate ◽  
Meta Analysis ◽  
Total Sample ◽  
Urine Samples ◽  
Pathogenic Potential ◽  
Clinical Specimens ◽  
Qrt Pcr ◽  
Corona Virus ◽  
Positive Rate

AbstractSARS-CoV-2 has posed an unprecedented challenge to the world. Pandemics have been caused previously by viruses of this family like Middle East Respiratory Corona Virus (MERS CoV), Severe Acute Respiratory Syndrome Corona Virus (SARS CoV). Although these viruses are primarily respiratory viruses, but they have been isolated from non-respiratory samples as well. Presently, the detection rate of SARS‐CoV‐2 RNA from different clinical specimens using Real Time Reverse Transcriptase Polymerized Chain Reaction (qRT‐PCR) after onset of symptoms is not yet well established. Therefore, the aim of this systematic review was to establish the profile of detecting SARS‐CoV‐2, MERS CoV, SARS CoV from different types of clinical specimens other than the respiratory using a standard diagnostic test (qRT‐PCR). A total of 3429 non-respiratory specimens were recorded: SARS CoV (total sample—802), MERS CoV (total sample—155), SARS CoV-2 (total sample—2347). Out of all the samples studied high positive rate was seen for saliva with 96.7% (14/14; 95% CI 87.6–100.0%) for SARS CoV and 57.5% (58/250; 95% CI − 1.2 to 116.2%) for SARS CoV-2, while low detection rate in urine samples for SARS CoV-2 with 2.2% (8/318; 95% CI 0.6–3.7%) and 9.6% (12/61; 95% CI − 0.9 to 20.1%) for SARS CoV but there was relatively higher positivity in urine samples for MERS CoV with detection rate of 32.4% (2/38; 95% CI − 37.3 to 102.1%). In Stool sample positivity was 54.9% (396/779; 95% CI 41.0–68.8%), 45.2% (180/430; 95% CI 28.1–62.3%) and 34.7% (4/38; 95% CI − 29.5 to 98.9%) for SARS CoV-2, MERS CoV, and SARS CoV, respectively. In blood sample the positivity was 33.3% (7/21; 95% CI 13.2–53.5%), 23.7% (42/277; 95% CI 10.5–36.9%) and 2.5% (2/81; 95% CI 0.00–5.8%) for MERS CoV, SARS CoV-2 and SARS CoV respectively. SARS‐CoV‐2 along with previous two pandemic causing viruses from this family, were highly detected stool and saliva. A low positive rate was recorded in blood samples. Viruses were also detected in fluids along with unusual samples like semen and vaginal secretions thus highlighting unique pathogenic potential of SARS‐CoV‐2.

scholarly journals Caffeine and Cognitive Functions in Sports: A Systematic Review and Meta-Analysis

Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 868
Author(s):  
Jorge Lorenzo Calvo ◽  
Xueyin Fei ◽  
Raúl Domínguez ◽  
Helios Pareja-Galeano
Keyword(s):  
Systematic Review ◽  
Reaction Time ◽  
Cognitive Performance ◽  
Cognitive Functions ◽  
Web Of Science ◽  
Meta Analysis ◽  
Caffeine Intake ◽  
Inclusion Criteria ◽  
Research Protocols ◽  
The Relationship

Cognitive functions are essential in any form of exercise. Recently, interest has mounted in addressing the relationship between caffeine intake and cognitive performance during sports practice. This review examines this relationship through a structured search of the databases Medline/PubMed and Web of Science for relevant articles published in English from August 1999 to March 2020. The study followed PRISMA guidelines. Inclusion criteria were defined according to the PICOS model. The identified records reported on randomized cross-over studies in which caffeine intake (as drinks, capsules, energy bars, or gum) was compared to an identical placebo situation. There were no filters on participants’ training level, gender, or age. For the systematic review, 13 studies examining the impacts of caffeine on objective measures of cognitive performance or self-reported cognitive performance were selected. Five of these studies were also subjected to meta-analysis. After pooling data in the meta-analysis, the significant impacts of caffeine only emerged on attention, accuracy, and speed. The results of the 13 studies, nevertheless, suggest that the intake of a low/moderate dose of caffeine before and/or during exercise can improve self-reported energy, mood, and cognitive functions, such as attention; it may also improve simple reaction time, choice reaction time, memory, or fatigue, however, this may depend on the research protocols.

A preliminary systematic review and meta-analysis on the effects of heart rate variability biofeedback on heart rate variability and respiration of athletes

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jeffrey Cayaban Pagaduan ◽  
Yung-Sheng Chen ◽  
James William Fell ◽  
Sam Shi Xuan Wu
Keyword(s):  
Systematic Review ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Web Of Science ◽  
Meta Analysis ◽  
Academic Research ◽  
Experimental Studies ◽  
Quantitative Review ◽  
Heart Rate Variability Biofeedback ◽  
Randomized Control

Abstract To date, there is no quantitative review examining the influence of heart rate variability biofeedback (HRV BFB) on the athlete population. Such an undertaking may provide valuable information on the autonomic and respiration responses of athletes when performing HRV BFB. Thus, purpose of this preliminary systematic review and meta-analysis on the effects of HRV BFB on HRV and respiration of athletes. Searches of Springerlink, SportDiscus, Web of Science, PROQUEST Academic Research Library, Google Scholar, and ScienceDirect were conducted for studies that met the following criteria: (1) experimental studies involving athletes that underwent randomized control trial; (2) availability of HRV BFB as a treatment compared with a control (CON)/placebo (PLA); (3) any pre and post HRV variable and/or breathing frequency as dependent variable/s; and, (4) peer-reviewed articles written in English. Four out of 660 studies involving 115 athletes (25 females and 90 males) ages 16–30 years old were assessed in this review. Preliminary findings suggest the promising ability of HRV BFB to improve respiratory mechanics in athlete population. More work is needed to determine the autonomic modulatory effect of HRV BFB in athletes.

scholarly journals SARS-CoV-2 genome and antibodies in breastmilk: a systematic review and meta-analysis

2021 ◽  
pp. fetalneonatal-2020-321074
Author(s):  
Faith Zhu ◽  
Carlos Zozaya ◽  
Qi Zhou ◽  
Charmaine De Castro ◽  
Prakesh S Shah
Keyword(s):  
Systematic Review ◽  
Outcome Measures ◽  
Study Design ◽  
Web Of Science ◽  
Meta Analysis ◽  
Respiratory Support ◽  
Common Finding ◽  
Rt Pcr

ObjectiveTo systematically review and meta-analyse the rate of SARS-CoV-2 genome identification and the presence of SARS-CoV-2 antibodies in breastmilk of mothers with COVID-19.DesignA systematic review of studies published between January 2019 and October 2020 without study design or language restrictions.SettingData sourced from Ovid Embase Classic+Embase, PubMed, Web of Science, Scopus, relevant bibliographies and the John Hopkins University COVID-19 database.PatientsMothers with confirmed COVID-19 and breastmilk tested for SARS-CoV-2 by RT-PCR or for anti-SARS-CoV-2 antibodies.Main outcome measuresPresence of SARS-CoV-2 genome and antibodies in breastmilk.ResultsWe included 50 articles. Twelve out of 183 women from 48 studies were positive for SARS-CoV-2 genome in their breastmilk (pooled proportion 5% (95% CI 2% to 15%; I2=48%)). Six infants (50%) of these 12 mothers tested positive for SARS-CoV-2, with one requiring respiratory support. Sixty-one out of 89 women from 10 studies had anti-SARS-CoV-2 antibody in their breastmilk (pooled proportion 83% (95% CI 32% to 98%; I2=88%)). The predominant antibody detected was IgA.ConclusionsSARS-CoV-2 genome presence in breastmilk is uncommon and is associated with mild symptoms in infants. Anti-SARS-CoV-2 antibodies may be a more common finding. Considering the low proportion of SARS-CoV-2 genome detected in breastmilk and its lower virulence, mothers with COVID-19 should be supported to breastfeed.

Concerning the article ‘aromatherapy intervention on anxiety and pain during first stage labour in nulliparous women: a systematic review and meta-analysis’

2021 ◽  
pp. 1-1
Author(s):  
Lara Caline Santos Lira ◽  
Melania Maria Amorim ◽  
Alexandre Delgado ◽  
Mariane de Oliveira Menezes ◽  
Maíra Libertad Soligo Takemoto
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Nulliparous Women

scholarly journals Evaluating the diagnostic test accuracy of molecular xenomonitoring methods for characterising community burden of lymphatic filariasis

2021 ◽  
Author(s):  
Joseph Pryce ◽  
Lisa J Reimer
Keyword(s):  
Systematic Review ◽  
Lymphatic Filariasis ◽  
Meta Analysis ◽  
Test Accuracy ◽  
Sample Sizes ◽  
Pathogen Dna ◽  
Low Sensitivity ◽  
The Relationship ◽  
Molecular Xenomonitoring ◽  
Strong Linear Relationship

Abstract Background Molecular xenomonitoring (MX), the detection of pathogen DNA in mosquitoes, is a recommended approach to support lymphatic filariasis (LF) elimination efforts. Potential roles of MX include detecting presence of LF in communities and quantifying progress towards elimination of the disease. However, the relationship between MX results and human prevalence is poorly understood. Methods :We conducted a systematic review and meta-analysis from all previously conducted studies that reported the prevalence of filarial DNA in wild-caught mosquitoes (MX rate) and the corresponding prevalence of microfilaria (mf) in humans. We calculated a pooled estimate of MX sensitivity for detecting positive communities at a range of mf prevalence values and mosquito sample sizes. We conducted a linear regression to evaluate the relationship between mf prevalence and MX rate. Results We identified 24 studies comprising 144 study communities. MX had an overall sensitivity of 98.3% (95% CI 41.5, 99.9%) and identified 28 positive communities that were negative in the mf survey. Low sensitivity in some studies was attributed to small mosquito sample sizes (<1,000) and very low mf prevalence (<0.25%). Human mf prevalence and mass drug administration status accounted for approximately half of the variation in MX rate (R 2 = 0.49, p<0.001). Data from longitudinal studies showed that, within a given study area, there is a strong linear relationship between MX rate and mf prevalence (R 2 = 0.78, p < 0.001). Conclusion MX shows clear potential as tool for detecting communities where LF is present and as a predictor of human mf prevalence.

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