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A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining.Healthcare (Basel, Switzerland) May 2018The growing healthcare industry is generating a large volume of useful data on patient demographics, treatment plans, payment, and insurance coverage—attracting... (Review)
Review
The growing healthcare industry is generating a large volume of useful data on patient demographics, treatment plans, payment, and insurance coverage—attracting the attention of clinicians and scientists alike. In recent years, a number of peer-reviewed articles have addressed different dimensions of data mining application in healthcare. However, the lack of a comprehensive and systematic narrative motivated us to construct a literature review on this topic. In this paper, we present a review of the literature on healthcare analytics using data mining and big data. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a database search between 2005 and 2016. Critical elements of the selected studies—healthcare sub-areas, data mining techniques, types of analytics, data, and data sources—were extracted to provide a systematic view of development in this field and possible future directions. We found that the existing literature mostly examines analytics in clinical and administrative decision-making. Use of human-generated data is predominant considering the wide adoption of Electronic Medical Record in clinical care. However, analytics based on website and social media data has been increasing in recent years. Lack of prescriptive analytics in practice and integration of domain expert knowledge in the decision-making process emphasizes the necessity of future research.
PubMed: 29882866
DOI: 10.3390/healthcare6020054 -
Nutrition in Clinical Practice :... Jun 2017Human milk-associated microbes are among the first to colonize the infant gut and may help to shape both short- and long-term infant health outcomes. We performed a... (Review)
Review
Human milk-associated microbes are among the first to colonize the infant gut and may help to shape both short- and long-term infant health outcomes. We performed a systematic review to characterize the microbiota of human milk. Relevant primary studies were identified through a comprehensive search of PubMed (January 1, 1964, to June 31, 2015). Included studies were conducted among healthy mothers, were written in English, identified bacteria in human milk, used culture-independent methods, and reported primary results at the genus level. Twelve studies satisfied inclusion criteria. All varied in geographic location and human milk collection/storage/analytic methods. Streptococcus was identified in human milk samples in 11 studies (91.6%) and Staphylococcus in 10 (83.3%); both were predominant genera in 6 (50%). Eight of the 12 studies used conventional ribosomal RNA (rRNA) polymerase chain reaction (PCR), of which 7 (87.5%) identified Streptococcus and 6 (80%) identified Staphylococcus as present. Of these 8 studies, 2 (25%) identified Streptococcus and Staphylococcus as predominant genera. Four of the 12 studies used next-generation sequencing (NGS), all of which identified Streptococcus and Staphylococcus as present and predominant genera. Relative to conventional rRNA PCR, NGS is a more sensitive method to identify/quantify bacterial genera in human milk, suggesting the predominance of Streptococcus and Staphylococcus may be underestimated in studies using older methods. These genera, Streptococcus and Staphylococcus, may be universally predominant in human milk, regardless of differences in geographic location or analytic methods. Primary studies designed to evaluate the effect of these 2 genera on short- and long-term infant outcomes are warranted.
Topics: Food Microbiology; Humans; Infant; Microbiota; Milk, Human; Staphylococcus; Streptococcus
PubMed: 27679525
DOI: 10.1177/0884533616670150 -
Briefings in Bioinformatics Jan 2018Repositioning of previously approved drugs is a promising methodology because it reduces the cost and duration of the drug development pipeline and reduces the... (Review)
Review
Repositioning of previously approved drugs is a promising methodology because it reduces the cost and duration of the drug development pipeline and reduces the likelihood of unforeseen adverse events. Computational repositioning is especially appealing because of the ability to rapidly screen candidates in silico and to reduce the number of possible repositioning candidates. What is unclear, however, is how useful such methods are in producing clinically efficacious repositioning hypotheses. Furthermore, there is no agreement in the field over the proper way to perform validation of in silico predictions, and in fact no systematic review of repositioning validation methodologies. To address this unmet need, we review the computational repositioning literature and capture studies in which authors claimed to have validated their work. Our analysis reveals widespread variation in the types of strategies, predictions made and databases used as 'gold standards'. We highlight a key weakness of the most commonly used strategy and propose a path forward for the consistent analytic validation of repositioning techniques.
Topics: Computational Biology; Computer Simulation; Databases, Factual; Drug Repositioning; Humans; Validation Studies as Topic
PubMed: 27881429
DOI: 10.1093/bib/bbw110 -
Journal of Critical Care Feb 2022Existing expert systems have not improved the diagnostic accuracy of ventilator-associated pneumonia (VAP). The aim of this systematic literature review was to review... (Meta-Analysis)
Meta-Analysis Review
PURPOSE
Existing expert systems have not improved the diagnostic accuracy of ventilator-associated pneumonia (VAP). The aim of this systematic literature review was to review and summarize state-of-the-art prediction models detecting or predicting VAP from exhaled breath, patient reports and demographic and clinical characteristics.
METHODS
Both diagnostic and prognostic prediction models were searched from a representative list of multidisciplinary databases. An extensive list of validated search terms was added to the search to cover papers failing to mention predictive research in their title or abstract. Two authors independently selected studies, while three authors extracted data using predefined criteria and data extraction forms. The Prediction Model Risk of Bias Assessment Tool was used to assess both the risk of bias and the applicability of the prediction modelling studies. Technology readiness was also assessed.
RESULTS
Out of 2052 identified studies, 20 were included. Fourteen (70%) studies reported the predictive performance of diagnostic models to detect VAP from exhaled human breath with a high degree of sensitivity and a moderate specificity. In addition, the majority of them were validated on a realistic dataset. The rest of the studies reported the predictive performance of diagnostic and prognostic prediction models to detect VAP from unstructured narratives [2 (10%)] as well as baseline demographics and clinical characteristics [4 (20%)]. All studies, however, had either a high or unclear risk of bias without significant improvements in applicability.
CONCLUSIONS
The development and deployment of prediction modelling studies are limited in VAP and related outcomes. More computational, translational, and clinical research is needed to bring these tools from the bench to the bedside.
REGISTRATION
PROSPERO CRD42020180218, registered on 05-07-2020.
Topics: Bias; Humans; Pneumonia, Ventilator-Associated; Prognosis
PubMed: 34673331
DOI: 10.1016/j.jcrc.2021.10.001 -
Biomedicines Jul 2022Reported levels of amyloid-beta and tau in human cerebrospinal fluid (CSF) were evaluated to discover if these biochemical markers can predict the transition from Mild... (Review)
Review
Reported levels of amyloid-beta and tau in human cerebrospinal fluid (CSF) were evaluated to discover if these biochemical markers can predict the transition from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD). A systematic review of the literature in PubMed and Web of Science (April 2021) was performed by a single researcher to identify studies reporting immunologically-based (xMAP or ELISA) measures of CSF analytes Aβ(1-42) and/or P-tau and/or T-tau in clinical studies with at least two timepoints and a statement of diagnostic criteria. Of 1137 screened publications, 22 met the inclusion criteria for CSF Aβ(1-42) measures, 20 studies included T-tau, and 17 included P-tau. Six meta-analyses were conducted to compare the analytes for healthy controls (HC) versus progressive MCI (MCI_AD) and for non-progressive MCI (Stable_MCI) versus MCI_AD; effect sizes were determined using random effects models. The heterogeneity of effect sizes across studies was confirmed with very high significance (p < 0.0001) for all meta-analyses except HC versus MCI_AD T-tau (p < 0.05) and P-tau (non-significant). Standard mean difference (SMD) was highly significant (p < 0.0001) for all comparisons (Stable_MCI versus MCI_AD: SMD [95%-CI] Aβ(1-42) = 1.19 [0.96,1.42]; T-tau = −1.03 [−1.24,−0.82]; P-tau = −1.03 [−1.47,−0.59]; HC versus MCI_AD: SMD Aβ(1-42) = 1.73 [1.39,2.07]; T-tau = −1.13 [−1.33,−0.93]; P-tau = −1.10 [−1.23,−0.96]). The follow-up interval in longitudinal evaluations was a critical factor in clinical study design, and the Aβ(1−42)/P-tau ratio most robustly differentiated progressive from non-progressive MCI. The value of amyloid-beta and tau as markers of patient outcome are supported by these findings.
PubMed: 35885018
DOI: 10.3390/biomedicines10071713 -
Cancer Informatics 2019Visual analytics and visualisation can leverage the human perceptual system to interpret and uncover hidden patterns in big data. The advent of next-generation... (Review)
Review
Visual analytics and visualisation can leverage the human perceptual system to interpret and uncover hidden patterns in big data. The advent of next-generation sequencing technologies has allowed the rapid production of massive amounts of genomic data and created a corresponding need for new tools and methods for visualising and interpreting these data. Visualising genomic data requires not only simply plotting of data but should also offer a decision or a choice about what the message should be conveyed in the particular plot; which methodologies should be used to represent the results must provide an easy, clear, and accurate way to the clinicians, experts, or researchers to interact with the data. Genomic data visual analytics is rapidly evolving in parallel with advances in high-throughput technologies such as artificial intelligence (AI) and virtual reality (VR). Personalised medicine requires new genomic visualisation tools, which can efficiently extract knowledge from the genomic data and speed up expert decisions about the best treatment of individual patient's needs. However, meaningful visual analytics of such large genomic data remains a serious challenge. This article provides a comprehensive systematic review and discussion on the tools, methods, and trends for visual analytics of cancer-related genomic data. We reviewed methods for genomic data visualisation including traditional approaches such as scatter plots, heatmaps, coordinates, and networks, as well as emerging technologies using AI and VR. We also demonstrate the development of genomic data visualisation tools over time and analyse the evolution of visualising genomic data.
PubMed: 30890859
DOI: 10.1177/1176935119835546 -
Acta Psychiatrica Scandinavica Jan 2022Major depressive disorder (MDD) and anxiety disorders are both common and especially challenging during pregnancy. Considering possible risks of intrauterine drug... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
Major depressive disorder (MDD) and anxiety disorders are both common and especially challenging during pregnancy. Considering possible risks of intrauterine drug exposure of the child, the role of psychopharmacological treatment is ambiguous and various negative obstetric outcomes were inconsistently associated with medication. Consequently, a critical examination of peri- and postnatal phenomena associated with intrauterine exposure to antidepressants based on serotonin reuptake inhibition (SRI) and subsumed under the term "poor neonatal adaptation syndrome" (PNAS) is urgently called for.
METHODS
A comprehensive literature search was conducted, revealing a total number of 33 relevant studies and 69 individual outcomes among 3025 screened studies. Seventeen outcomes allowed meta-analytic evaluation (random effects model). Measures for heterogeneity (I ) and contour-enhanced funnel plots were generated.
RESULTS
Single studies showed increased risks for deficits in neurological functioning and autonomous adaptation in SRI exposed infants. Meta-analytical evaluation showed increased symptom occurrence or severity in exposed neonates for low APGAR scores, birth weight, size for gestational age, preterm delivery, neuromuscular and autonomous regulation, and higher rates of admission to specialized care. Mostly, increased risk after SRI exposure was supported by comparison to unexposed infants born to mothers diagnosed with depression.
CONCLUSION
Whereas statistically significant evidence for various effects of intrauterine exposure to SRI was found, the clinical relevance remains unresolved because of inherently low data quality in this research domain and insufficiently defined samples and outcomes. More systematic research under ethical considerations is required to improve multiprofessional counseling in the many women dealing with MDD during pregnancy and the peripartum.
Topics: Antidepressive Agents; Anxiety Disorders; Child; Depressive Disorder, Major; Female; Gestational Age; Humans; Infant, Newborn; Pregnancy; Pregnancy Complications; Selective Serotonin Reuptake Inhibitors
PubMed: 34486740
DOI: 10.1111/acps.13367 -
BMC Medical Research Methodology Nov 2014Syntheses of qualitative studies can inform health policy, services and our understanding of patient experience. Meta-ethnography is a systematic seven-phase... (Review)
Review
BACKGROUND
Syntheses of qualitative studies can inform health policy, services and our understanding of patient experience. Meta-ethnography is a systematic seven-phase interpretive qualitative synthesis approach well-suited to producing new theories and conceptual models. However, there are concerns about the quality of meta-ethnography reporting, particularly the analysis and synthesis processes. Our aim was to investigate the application and reporting of methods in recent meta-ethnography journal papers, focusing on the analysis and synthesis process and output.
METHODS
Methodological systematic review of health-related meta-ethnography journal papers published from 2012-2013. We searched six electronic databases, Google Scholar and Zetoc for papers using key terms including 'meta-ethnography.' Two authors independently screened papers by title and abstract with 100% agreement. We identified 32 relevant papers. Three authors independently extracted data and all authors analysed the application and reporting of methods using content analysis.
RESULTS
Meta-ethnography was applied in diverse ways, sometimes inappropriately. In 13% of papers the approach did not suit the research aim. In 66% of papers reviewers did not follow the principles of meta-ethnography. The analytical and synthesis processes were poorly reported overall. In only 31% of papers reviewers clearly described how they analysed conceptual data from primary studies (phase 5, 'translation' of studies) and in only one paper (3%) reviewers explicitly described how they conducted the analytic synthesis process (phase 6). In 38% of papers we could not ascertain if reviewers had achieved any new interpretation of primary studies. In over 30% of papers seminal methodological texts which could have informed methods were not cited.
CONCLUSIONS
We believe this is the first in-depth methodological systematic review of meta-ethnography conduct and reporting. Meta-ethnography is an evolving approach. Current reporting of methods, analysis and synthesis lacks clarity and comprehensiveness. This is a major barrier to use of meta-ethnography findings that could contribute significantly to the evidence base because it makes judging their rigour and credibility difficult. To realise the high potential value of meta-ethnography for enhancing health care and understanding patient experience requires reporting that clearly conveys the methodology, analysis and findings. Tailored meta-ethnography reporting guidelines, developed through expert consensus, could improve reporting.
Topics: Anthropology, Cultural; Data Interpretation, Statistical; Humans; Publishing; Qualitative Research; Research Design
PubMed: 25407140
DOI: 10.1186/1471-2288-14-119 -
Contraception Nov 2023This study aimed to update our 2019 systematic review of data on the effectiveness and safety of misoprostol-only for first-trimester abortion. (Meta-Analysis)
Meta-Analysis Review
OBJECTIVES
This study aimed to update our 2019 systematic review of data on the effectiveness and safety of misoprostol-only for first-trimester abortion.
STUDY DESIGN
We searched PubMed on December 18, 2022, to find published articles describing the outcomes of treatment with misoprostol-only for abortion of viable intrauterine pregnancy at ≤91 days of gestation. From each article identified, two authors independently abstracted relevant data about each group of patients treated with a distinct regimen. We assessed the risk of bias using four defined indicators. We estimated the proportion of patients with treatment failure using meta-analytic methods as well as the proportion hospitalized or transfused after treatment. We examined associations between treatment failure and selected characteristics of the groups.
RESULTS
We identified 49 papers with 66 groups that collectively included 16,354 evaluable patients, of whom 2960 (meta-analytic estimate 15%, 95% CI 12%, 19%) had treatment failures. Of 9228 patients assessed for ongoing pregnancy after treatment, 521 (meta-analytic estimate 6%, 95% CI 5%, 8%) had that condition. Failure risk was significantly associated with misoprostol dose, the total allowed number of doses, the maximum duration of dosing, and certain indicators of risk of bias. Among 11,007 patients allowed to take at least three misoprostol doses, the first consisting of misoprostol 800 mcg administered vaginally, sublingually, or buccally, the meta-analytic estimate of the failure risk was 11% (95% CI 8%, 14%). At most, 0.2% of 15,679 evaluable patients were hospitalized or received transfusions.
CONCLUSIONS
Although some studies in this updated review were adjudicated to have a high risk of bias, the results continue to support the key conclusion of our 2019 analysis: misoprostol-only is effective and safe for the termination of first-trimester intrauterine pregnancy.
IMPLICATIONS
Misoprostol-only is a safe and effective option for medication abortion in the first trimester if mifepristone is unavailable or inaccessible.
Topics: Pregnancy; Female; Humans; Misoprostol; Abortifacient Agents; Pregnancy Trimester, First; Mifepristone; Abortion, Induced; Abortifacient Agents, Nonsteroidal
PubMed: 37517447
DOI: 10.1016/j.contraception.2023.110132 -
Journal of the American Academy of... Jul 2024Early-onset psychosis (EOP) refers to the development of psychosis before the age of 18 years. We aimed to summarize, for the first time, the meta-analytical evidence in... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
Early-onset psychosis (EOP) refers to the development of psychosis before the age of 18 years. We aimed to summarize, for the first time, the meta-analytical evidence in the field of this vulnerable population and to provide evidence-based recommendations.
METHOD
We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant, pre-registered (PROSPERO: CRD42022350868) systematic review of several databases and registers to identify meta-analyses of studies conducted in EOP individuals to conduct an umbrella review. Literature search, screening, data extraction, and quality assessment were carried out independently. Results were narratively reported, clustered across core domains. Quality assessment was performed with the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) tool.
RESULTS
A total of 30 meta-analyses were included (373 individual studies, 25,983 participants, mean age 15.1 years, 38.3% female). Individuals with EOP showed more cognitive impairments compared with controls and individuals with adult/late-onset psychosis. Abnormalities were observed meta-analytically in neuroimaging markers but not in oxidative stress and inflammatory response markers. In all, 60.1% of EOP individuals had a poor prognosis. Clozapine was the antipsychotic with the highest efficacy for overall, positive, and negative symptoms. Tolerance to medication varied among the evaluated antipsychotics. The risk of discontinuation of antipsychotics for any reason or side effects was low or equal compared to placebo.
CONCLUSION
EOP is associated with cognitive impairment, involuntary admissions, and poor prognosis. Antipsychotics can be efficacious in EOP, but tolerability and safety need to be taken into consideration. Clozapine should be considered in EOP individuals who are resistant to 2 non-clozapine antipsychotics. Further meta-analytical research is needed on response to psychological interventions and other prognostic factors.
PLAIN LANGUAGE SUMMARY
This umbrella review summarized the meta-analytical knowledge from 30 meta-analyses on early-onset psychosis. Early-onset psychosis refers to the development of psychosis before the age of 18 years and is associated with cognitive impairment, hospitalization, and poor prognosis. Individuals with early-onset psychosis show more cognitive impairments and abnormalities compared with controls. Clozapine was the antipsychotic with the highest efficacy for positive, negative, and overall symptoms and should be considered in individuals with early-onset psychosis.
STUDY PREREGISTRATION INFORMATION
Early Onset Psychosis: Umbrella Review on Diagnosis, Prognosis and Treatment factors; https://www.crd.york.ac.uk/PROSPERO/; CRD42022350868.
Topics: Humans; Psychotic Disorders; Adolescent; Age of Onset; Antipsychotic Agents; Meta-Analysis as Topic; Cognitive Dysfunction
PubMed: 38280414
DOI: 10.1016/j.jaac.2023.10.016