-
International Journal of Nursing Studies Jan 2024The number of risk prediction models for deep venous thrombosis (DVT) in patients with acute stroke is increasing, while the quality and applicability of these models in... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
The number of risk prediction models for deep venous thrombosis (DVT) in patients with acute stroke is increasing, while the quality and applicability of these models in clinical practice and future research remain unknown.
OBJECTIVE
To systematically review published studies on risk prediction models for DVT in patients with acute stroke.
DESIGN
Systematic review and meta-analysis of observational studies.
METHODS
China National Knowledge Infrastructure (CNKI), Wanfang Database, China Science and Technology Journal Database (VIP), SinoMed, PubMed, Web of Science, The Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Embase were searched from inception to November 7, 2022. Data from selected studies were extracted, including study design, data source, outcome definition, sample size, predictors, model development and performance. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was used to assess the risk of bias and applicability.
RESULTS
A total of 940 studies were retrieved, and after the selection process, nine prediction models from nine studies were included in this review. All studies utilized logistic regression to establish DVT risk prediction models. The incidence of DVT in patients with acute stroke ranged from 0.4 % to 28 %. The most frequently used predictors were D-dimer and age. The reported area under the curve (AUC) ranged from 0.70 to 0.912. All studies were found to have a high risk of bias, primarily due to inappropriate data sources and poor reporting of the analysis domain. The pooled AUC value of the five validated models was 0.76 (95 % confidence interval: 0.70-0.81), indicating a fair level of discrimination.
CONCLUSION
Although the included studies reported a certain level of discrimination in the prediction models of DVT in patients with acute stroke, all of them were found to have a high risk of bias according to the PROBAST checklist. Future studies should focus on developing new models with larger samples, rigorous study designs, and multicenter external validation.
REGISTRATION
The protocol for this study is registered with PROSPERO (registration number: CRD42022370287).
Topics: Humans; Stroke; Risk Assessment; Venous Thrombosis; China; Multicenter Studies as Topic
PubMed: 37944356
DOI: 10.1016/j.ijnurstu.2023.104623 -
Nature Communications May 2024The Modified Vaccinia Ankara vaccine developed by Bavarian Nordic (MVA-BN) was widely deployed to prevent mpox during the 2022 global outbreak. This vaccine was... (Meta-Analysis)
Meta-Analysis
The Modified Vaccinia Ankara vaccine developed by Bavarian Nordic (MVA-BN) was widely deployed to prevent mpox during the 2022 global outbreak. This vaccine was initially approved for mpox based on its reported immunogenicity (from phase I/II trials) and effectiveness in animal models, rather than evidence of clinical efficacy. However, no validated correlate of protection after vaccination has been identified. Here we performed a systematic search and meta-analysis of the available data to test whether vaccinia-binding ELISA endpoint titer is predictive of vaccine effectiveness against mpox. We observe a significant correlation between vaccine effectiveness and vaccinia-binding antibody titers, consistent with the existing assumption that antibody levels may be a correlate of protection. Combining this data with analysis of antibody kinetics after vaccination, we predict the durability of protection after vaccination and the impact of dose spacing. We find that delaying the second dose of MVA-BN vaccination will provide more durable protection and may be optimal in an outbreak with limited vaccine stock. Although further work is required to validate this correlate, this study provides a quantitative evidence-based approach for using antibody measurements to predict the effectiveness of mpox vaccination.
Topics: Animals; Humans; Antibodies, Viral; Enzyme-Linked Immunosorbent Assay; Smallpox Vaccine; Vaccination; Vaccine Efficacy; Vaccinia; Monkeypox virus
PubMed: 38719852
DOI: 10.1038/s41467-024-48180-w -
Frontiers in Neurology 2023The recognition of Auditory Processing Disorder (APD) as a distinct clinical condition that impacts hearing capacity and mental health has gained attention. Although... (Review)
Review
The recognition of Auditory Processing Disorder (APD) as a distinct clinical condition that impacts hearing capacity and mental health has gained attention. Although pure tone audiometry is the gold standard for assessing hearing, it inadequately reflects everyday hearing abilities, especially in challenging acoustic environments. Deficits in speech perception in noise, a key aspect of APD, have been linked to an increased risk of dementia. The World Health Organization emphasizes the need for evaluating central auditory function in cases of mild hearing loss and normal audiometry results. Specific questionnaires play a crucial role in documenting and quantifying the difficulties faced by individuals with APD. Validated questionnaires such as the Children's Auditory Processing Performance Scale, the Fisher's Auditory Problems Checklist, and the Auditory Processing Domains Questionnaire are available for children, while questionnaires for adults include items related to auditory functions associated with APD. This systematic review and meta-analysis identified six questionnaires used for screening and evaluating APD with a total of 783 participants across 12 studies. The questionnaires exhibited differences in domains evaluated, scoring methods, and evaluation of listening in quiet and noise. Meta-analysis results demonstrated that individuals with APD consistently exhibited worse scores compared to healthy controls across all questionnaires. Additionally, comparisons with clinical control groups showed varying results. The study highlights (i) the importance of standardized questionnaires in identifying and assessing APD, aiding in its diagnosis and management, and (ii) the need to use sub-scores as well as overall scores of questionnaires to elaborate on specific hearing and listening situations. There is a need to develop more APD specific questionnaires for the adult population as well as for more focused research on APD diagnosed individuals to further establish the validity and reliability of these questionnaires.
PubMed: 37621857
DOI: 10.3389/fneur.2023.1243170 -
Annals of Internal Medicine Jan 2024Severe maternal morbidity and mortality are worse in the United States than in all similar countries, with the greatest effect on Black women. Emerging research suggests... (Review)
Review
BACKGROUND
Severe maternal morbidity and mortality are worse in the United States than in all similar countries, with the greatest effect on Black women. Emerging research suggests that disrespectful care during childbirth contributes to this problem.
PURPOSE
To conduct a systematic review on definitions and valid measurements of respectful maternity care (RMC), its effectiveness for improving maternal and infant health outcomes for those who are pregnant and postpartum, and strategies for implementation.
DATA SOURCES
Systematic searches of Ovid Medline, CINAHL, Embase, Cochrane Central Register of Controlled Trials, PsycInfo, and SocINDEX for English-language studies (inception to July 2023).
STUDY SELECTION
Randomized controlled trials and nonrandomized studies of interventions of RMC versus usual care for effectiveness studies; additional qualitative and noncomparative validation studies for definitions and measurement studies.
DATA EXTRACTION
Dual data abstraction and quality assessment using established methods, with resolution of disagreements through consensus.
DATA SYNTHESIS
Thirty-seven studies were included across all questions, of which 1 provided insufficient evidence on the effectiveness of RMC to improve maternal outcomes and none studied RMC to improve infant outcomes. To define RMC, authors identified 12 RMC frameworks, from which 2 main concepts were identified: and frameworks. Disrespect and abuse components focused on recognizing birth mistreatment; rights-based frameworks incorporated aspects of reproductive justice, human rights, and antiracism. Five overlapping framework themes include freedom from abuse, consent, privacy, dignity, communication, safety, and justice. Twelve tools to measure RMC were validated in 24 studies on content validity, construct validity, and internal consistency, but lack of a gold standard limited evaluation of criterion validity. Three tools specific for RMC had at least 1 study demonstrating consistency internally and with an intended construct relevant to U.S. settings, but no single tool stands out as the best measure of RMC.
LIMITATIONS
No studies evaluated other health outcomes or RMC implementation strategies. The lack of definition and gold standard limit evaluation of RMC tools.
CONCLUSION
Frameworks for RMC are well described but vary in their definitions. Tools to measure RMC demonstrate consistency but lack a gold standard, requiring further evaluation before implementation in U.S. settings. Evidence is lacking on the effectiveness of implementing RMC to improve any maternal or infant health outcome.
PRIMARY FUNDING SOURCE
Agency for Healthcare Research and Quality. (PROSPERO: CRD42023394769).
Topics: Infant; Pregnancy; Female; Humans; Maternal Health Services; Respect; Obstetrics; Delivery, Obstetric; Postpartum Period; Quality of Health Care
PubMed: 38163377
DOI: 10.7326/M23-2676 -
Critical Care (London, England) Nov 2023Despite the extensive volume of research published on checklists in the intensive care unit (ICU), no review has been published on the broader role of checklists within... (Review)
Review
BACKGROUND
Despite the extensive volume of research published on checklists in the intensive care unit (ICU), no review has been published on the broader role of checklists within the intensive care unit, their implementation and validation, and the recommended clinical context for their use. Accordingly, a scoping review was necessary to map the current literature and to guide future research on intensive care checklists. This review focuses on what checklists are currently used, how they are used, process of checklist development and implementation, and outcomes associated with checklist use.
METHODS
A systematic search of MEDLINE (Ovid), Embase, Scopus, and Google Scholar databases was conducted, followed by a grey literature search. The abstracts of the identified studies were screened. Full texts of relevant articles were reviewed, and the references of included studies were subsequently screened for additional relevant articles. Details of the study characteristics, study design, checklist intervention, and outcomes were extracted.
RESULTS
Our search yielded 2046 studies, of which 167 were selected for further analysis. Checklists identified in these studies were categorised into the following types: rounding checklists; delirium screening checklists; transfer and handover checklists; central line-associated bloodstream infection (CLABSI) prevention checklists; airway management checklists; and other. Of 72 significant clinical outcomes reported, 65 were positive, five were negative, and two were mixed. Of 122 significant process of care outcomes reported, 114 were positive and eight were negative.
CONCLUSIONS
Checklists are commonly used in the intensive care unit and appear in many clinical guidelines. Delirium screening checklists and rounding checklists are well implemented and validated in the literature. Clinical and process of care outcomes associated with checklist use are predominantly positive. Future research on checklists in the intensive care unit should focus on establishing clinical guidelines for checklist types and processes for ongoing modification and improvements using post-intervention data.
Topics: Humans; Checklist; Critical Care; Delirium; Intensive Care Units
PubMed: 38037056
DOI: 10.1186/s13054-023-04758-2 -
Children (Basel, Switzerland) Oct 2023All societies should carefully address the child abuse and neglect phenomenon due to its acute and chronic sequelae. Even if artificial intelligence (AI) implementation... (Review)
Review
All societies should carefully address the child abuse and neglect phenomenon due to its acute and chronic sequelae. Even if artificial intelligence (AI) implementation in this field could be helpful, the state of the art of this implementation is not known. No studies have comprehensively reviewed the types of AI models that have been developed/validated. Furthermore, no indications about the risk of bias in these studies are available. For these reasons, the authors conducted a systematic review of the PubMed database to answer the following questions: "what is the state of the art about the development and/or validation of AI predictive models useful to contrast child abuse and neglect phenomenon?"; "which is the risk of bias of the included articles?". The inclusion criteria were: articles written in English and dated from January 1985 to 31 March 2023; publications that used a medical and/or protective service dataset to develop and/or validate AI prediction models. The reviewers screened 413 articles. Among them, seven papers were included. Their analysis showed that: the types of input data were heterogeneous; artificial neural networks, convolutional neural networks, and natural language processing were used; the datasets had a median size of 2600 cases; the risk of bias was high for all studies. The results of the review pointed out that the implementation of AI in the child abuse and neglect field lagged compared to other medical fields. Furthermore, the evaluation of the risk of bias suggested that future studies should provide an appropriate choice of sample size, validation, and management of overfitting, optimism, and missing data.
PubMed: 37892322
DOI: 10.3390/children10101659 -
Journal of Ovarian Research Nov 2023Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease,... (Review)
Review
Clinical prediction models play an important role in the field of medicine. These can help predict the probability of an individual suffering from disease, complications, and treatment outcomes by applying specific methodologies. Polycystic ovary syndrome (PCOS) is a common disease with a high incidence rate, huge heterogeneity, short- and long-term complications, and complex treatments. In this systematic review study, we reviewed the progress of clinical prediction models in PCOS patients, including diagnosis and prediction models for PCOS complications and treatment outcomes. We aimed to provide ideas for medical researchers and clues for the management of PCOS. In the future, models with poor accuracy can be greatly improved by adding well-known parameters and validations, which will further expand our understanding of PCOS in terms of precision medicine. By developing a series of predictive models, we can make the definition of PCOS more accurate, which can improve the diagnosis of PCOS and reduce the likelihood of false positives and false negatives. It will also help discover complications earlier and treatment outcomes being known earlier, which can result in better outcomes for women with PCOS.
Topics: Female; Humans; Polycystic Ovary Syndrome; Models, Statistical; Prognosis
PubMed: 38007488
DOI: 10.1186/s13048-023-01310-2 -
American Journal of Obstetrics &... Sep 2023This study aimed to conduct a systematic review and to evaluate the psychometric measurement properties of instruments for postpartum anxiety using the Consensus-Based... (Review)
Review
OBJECTIVE
This study aimed to conduct a systematic review and to evaluate the psychometric measurement properties of instruments for postpartum anxiety using the Consensus-Based Standards for the Selection of Health Measurement Instruments guidelines to identify the best available patient-reported outcome measure.
DATA SOURCES
We searched 4 databases (CINAHL, Embase, PubMed, and Web of Science in July 2022) and included studies that evaluated at least 1 psychometric measurement property of a patient-reported outcome measurement instrument. The protocol was registered with the International Prospective Register for Systematic Reviews under identifier CRD42021260004 and followed the Consensus-Based Standards for the Selection of Health Measurement Instruments guidelines for systematic reviews.
STUDY ELIGIBILITY
Studies eligible for inclusion were those that assessed the performance of a patient-reported outcome measure for screening for postpartum anxiety. We included studies in which the instruments were subjected to some form of psychometric property assessment in the postpartum maternal population, consisted of at least 2 questions, and were not subscales.
METHODS
This systematic review used the Consensus-Based Standards for the Selection of Health Measurement Instruments and the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines to identify the best patient-reported outcome measurement instrument for examining postpartum anxiety. A risk of bias assessment was performed, and a modified GRADE approach was used to assess the level of evidence with recommendations being made for the overall quality of each instrument.
RESULTS
A total of 28 studies evaluating 13 instruments in 10,570 patients were included. Content validity was sufficient in 9 with 5 instruments receiving a class A recommendation (recommended for use). The Postpartum Specific Anxiety Scale, Postpartum Specific Anxiety Scale Research Short Form, Postpartum Specific Anxiety Scale Research Short Form Covid, Postpartum Specific Anxiety Scale-Persian, and the State-Trait Anxiety Inventory demonstrated adequate content validity and sufficient internal consistency. Nine instruments received a recommendation of class B (further research required). No instrument received a class C recommendation (not recommended for use).
CONCLUSION
Five instruments received a class A recommendation, all with limitations, such as not being specific to the postpartum population, not assessing all domains, lacking generalizability, or evaluation of cross-cultural validity. There is currently no freely available instrument that assess all domains of postpartum anxiety. Future studies are needed to determine the optimum current instrument or to develop and validate a more specific measure for maternal postpartum anxiety.
Topics: Humans; COVID-19; Anxiety; Patient Reported Outcome Measures; Psychometrics
PubMed: 37402438
DOI: 10.1016/j.ajogmf.2023.101076 -
Artificial intelligence for diagnostic and prognostic neuroimaging in dementia: A systematic review.Alzheimer's & Dementia : the Journal of... Dec 2023Artificial intelligence (AI) and neuroimaging offer new opportunities for diagnosis and prognosis of dementia. (Review)
Review
INTRODUCTION
Artificial intelligence (AI) and neuroimaging offer new opportunities for diagnosis and prognosis of dementia.
METHODS
We systematically reviewed studies reporting AI for neuroimaging in diagnosis and/or prognosis of cognitive neurodegenerative diseases.
RESULTS
A total of 255 studies were identified. Most studies relied on the Alzheimer's Disease Neuroimaging Initiative dataset. Algorithmic classifiers were the most commonly used AI method (48%) and discriminative models performed best for differentiating Alzheimer's disease from controls. The accuracy of algorithms varied with the patient cohort, imaging modalities, and stratifiers used. Few studies performed validation in an independent cohort.
DISCUSSION
The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions. We make recommendations to improve model validation including addressing key clinical questions, providing sufficient description of AI methods and validating findings in independent datasets. Collaborative approaches between experts in AI and medicine will help achieve the promising potential of AI tools in practice.
HIGHLIGHTS
There has been a rapid expansion in the use of machine learning for diagnosis and prognosis in neurodegenerative disease Most studies (71%) relied on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with no other individual dataset used more than five times There has been a recent rise in the use of more complex discriminative models (e.g., neural networks) that performed better than other classifiers for classification of AD vs healthy controls We make recommendations to address methodological considerations, addressing key clinical questions, and validation We also make recommendations for the field more broadly to standardize outcome measures, address gaps in the literature, and monitor sources of bias.
Topics: Humans; Alzheimer Disease; Prognosis; Artificial Intelligence; Neurodegenerative Diseases; Brain; Neuroimaging
PubMed: 37563912
DOI: 10.1002/alz.13412 -
The Journal of Prosthetic Dentistry Sep 2023Photogrammetry technology may be useful in implant dentistry, but a systematic review is lacking and is indicated before routine use in clinical practice. (Review)
Review
STATEMENT OF PROBLEM
Photogrammetry technology may be useful in implant dentistry, but a systematic review is lacking and is indicated before routine use in clinical practice.
PURPOSE
The purpose of this systematic review was to assess the role of the photogrammetry technology used in implant dentistry and determine its validity as an accurate tool with clinical applications.
MATERIAL AND METHODS
Four major databases, PubMed MEDLINE, Google Scholar, Scopus, and Web of Science, were selected to retrieve articles published from January 2011 to February 2021 based on custom criteria. The search was augmented by a manual search. After screening of the collected articles, data, including study design and setting, type of application, digitizer used, reference body, method of evaluation, and overall outcomes, were extracted.
RESULTS
Twenty articles were included based on the selection criteria. Most of the articles confirmed that the use of photogrammetry was promising as an implant coordinate transfer system. However, few articles showed its use for 3-dimensional scanning, which might require more development.
CONCLUSIONS
The initial reports of using photogrammetry technology considered this method as a valid and reliable clinical tool in implant dentistry. More studies to develop the photogrammetry technology and to assess the results with evidence-based research are recommended to enhance its application in different clinical situations.
Topics: Dental Implants; Photogrammetry; Databases, Factual
PubMed: 34801243
DOI: 10.1016/j.prosdent.2021.09.015