scholarly journals Evidence synthesis from a qualitative and a quantitative systematic literature review combined with a focus group interview to identify relevant criteria for decision-making on management options for early pregnancy loss

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Mirjam Peters ◽  
Andrea Icks ◽  
Charalabos Markos Dintsios
Keyword(s):  
Decision Making ◽  
Focus Group ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Early Pregnancy ◽  
Pregnancy Loss ◽  
Focus Group Interview ◽  
Evidence Synthesis ◽  
Early Pregnancy Loss ◽  
Management Options

scholarly journals Triploidy that escaped diagnosis using chromosomal microarray testing in early pregnancy loss: Two cases and a literature review

2019 ◽  
Vol 16 (2) ◽  
pp. 76-80
Author(s):  
Ji Eun Park ◽  
Ji Kwon Park ◽  
Min Young Kang ◽  
Hyen Chul Jo ◽  
In Ae Cho ◽  
...  
Keyword(s):  
Literature Review ◽  
Early Pregnancy ◽  
Pregnancy Loss ◽  
Chromosomal Microarray ◽  
Early Pregnancy Loss

Early Pregnancy Loss

2018 ◽  
Author(s):  
Bri Anne McKeon ◽  
Sarah Lambeth
Keyword(s):  
Early Pregnancy ◽  
Pregnancy Loss ◽  
Treatment Options ◽  
Reproductive Age ◽  
Early Pregnancy Loss ◽  
Management Options ◽  
Dilation And Curettage ◽  
Pelvic Ultrasonography ◽  
Products Of Conception ◽  
Threatened Abortion

Early pregnancy loss is a common clinical scenario for women of reproductive age. Confirmation of pregnancy loss by pelvic ultrasonography using established criteria is crucial to ensure that potentially viable pregnancies are not interrupted. Both medical and surgical management options are effective and safe methods for the management of early pregnancy loss. Management should largely be influenced by patient preference in the hemodynamically stable patient. The purpose of this section is to describe the criteria for the diagnosis of early pregnancy loss, discuss various evidence-based treatment options for early pregnancy loss, and review current recommendations for attempts at future conception. This review contains 4 figures, 5 tables and 41 references Key Words: dilation and curettage, inevitable abortion, miscarriage, missed abortion, misoprostol, nonviable pregnancy, retained products of conception, threatened abortion, ultrasonography criteria

Obesity is a risk factor for early pregnancy loss after IVF or ICSI

2000 ◽  
Vol 79 (1) ◽  
pp. 43-48 ◽  
Author(s):  
PÉTER FEDORCSÁK ◽  
RITSA STORENG ◽  
PER OLAV DALE ◽  
TOM TANBO ◽  
THOMAS ÅBYHOLM
Keyword(s):  
Risk Factor ◽  
Early Pregnancy ◽  
Pregnancy Loss ◽  
Early Pregnancy Loss

scholarly journals Systematic literature review of machine learning methods used in the analysis of real-world data for patient-provider decision making

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alan Brnabic ◽  
Lisa M. Hess
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Real World ◽  
Learning Algorithms ◽  
External Validation ◽  
Machine Learning Algorithms ◽  
Learning Methods ◽  
Machine Learning Methods

Abstract Background Machine learning is a broad term encompassing a number of methods that allow the investigator to learn from the data. These methods may permit large real-world databases to be more rapidly translated to applications to inform patient-provider decision making. Methods This systematic literature review was conducted to identify published observational research of employed machine learning to inform decision making at the patient-provider level. The search strategy was implemented and studies meeting eligibility criteria were evaluated by two independent reviewers. Relevant data related to study design, statistical methods and strengths and limitations were identified; study quality was assessed using a modified version of the Luo checklist. Results A total of 34 publications from January 2014 to September 2020 were identified and evaluated for this review. There were diverse methods, statistical packages and approaches used across identified studies. The most common methods included decision tree and random forest approaches. Most studies applied internal validation but only two conducted external validation. Most studies utilized one algorithm, and only eight studies applied multiple machine learning algorithms to the data. Seven items on the Luo checklist failed to be met by more than 50% of published studies. Conclusions A wide variety of approaches, algorithms, statistical software, and validation strategies were employed in the application of machine learning methods to inform patient-provider decision making. There is a need to ensure that multiple machine learning approaches are used, the model selection strategy is clearly defined, and both internal and external validation are necessary to be sure that decisions for patient care are being made with the highest quality evidence. Future work should routinely employ ensemble methods incorporating multiple machine learning algorithms.

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