Supported in part by funds from David H. Koch provided through the Prostate Cancer Foundation, the Sidney Kimmel Center for Prostate and Urologic Cancers and P50-CA92629 SPORE grant from the National Cancer Institute to Dr. P. T. Scardino.
Part Time - PDA (2013).81
Platelets are small sized, disk-shaped cells without a nucleus. These are derived from bone marrow and released into the circulation and have an average life span of 10 days. When present in the circulation, platelets have no tendency for adhesion to each other and vessel wall. However, when stimulated, they show alteration in shape, aggregate together, and adhere to the vessel wall. The activation of platelets, aggregation together, and adherence to the vessel wall is an integral part of physiological hemostasis mechanism. Platelets form a platelet plug to occlude the bleeding vessel and help in hemostasis [3].
Conti in an editorial mentioned that there is no need to stop aspirin prior to invasive surgical procedure if bleeding time is within normal limit [35]. Little et al. suggested that aspirin affected platelets did not cause significant bleeding complications unless the bleeding time is greater than 20 minutes [33]. Similarly, Sonksen et al. [31] and Gaspar et al. [45] claimed that there is no significant intraoperative and postoperative bleeding after dental extractions as long as prolongation in bleeding time remains within acceptable limit (bleeding time up to 20 minutes).
In an editorial published in journal named Angiology, Koskinas et al. commented on the study conducted by Lillis et al. [64]. The authors mentioned that if the results of the study conducted by Lillis et al. were considered, it showed that the incidence of bleeding incidence was substantially (6-fold) higher in patients on antiplatelet monotherapy group compared with controls. If the dual therapy group was compared with control group, the bleeding incidence was increased by more than 100-fold. They further stated that if procedural safety was based merely on the incidence of bleeding complication, then the study of Lillis et al. might be interpreted as evidence of increased bleeding risk in patients on single and dual antiplatelet therapy particularly for dual therapy. However, if additional meaningful clinical parameters such as time frame of occurrence of increased bleeding and efficacy of local hemostatic measures to control bleeding are added, then the results can be interpreted differently; that is, patients on antiplatelet therapy have increased incidence of prolonged bleeding when compared to control group, but the increased bleeding was presented in the time frame of safe clinical setting and can be easily controlled by local hemostatic measures [65].
A prospective trial conducted by Cardona-Tortajada et al. involving 155 patients on antiplatelet therapy confirmed that local measures to achieve hemostasis are sufficient to control postoperative hemorrhage after tooth extraction. It is advisable to minimize the surgical trauma by minimizing the number of teeth to be extracted at a time. It has been recommended that three single rooted teeth and two molars either adjacent or corelative to each other should be extracted during a single visit [70].
Extraction is one of the most common procedures performed in oral surgery. Surgical procedures performed on the patients must be based on sound scientific knowledge of literature. Nothing is static, so is the science. Recommendation changes from time to time. Based on the review of literature, it can be concluded that current recommendations and consensus are in favor of not stopping antiplatelet dose of aspirin prior to tooth extraction. The safety of dental extractions in such patients is supported by studies reported in literature. It must be emphasized that appropriate use of local hemostatic measures should always be considered whenever indicated. There is no justification to predispose the patient to the risk of thromboembolism at the expense of minor bleeding which can be easily controlled.
As per Mazefsky et al. (2018a, b), differential item functioning (DIF) analysis was then conducted to explore whether items behaved similarly with respect to their quantification of the trait in (a) older vs. younger children; (b) males vs. females; (c) those with higher or lower parent-reported intellectual ability levels; and (d) those with higher vs. lower independence in daily living activities. An item is designated as showing DIF if it is more or less difficult to endorse, or more or less discriminating in one or other group (e.g., males or females). DIF analysis was conducted by fitting GRM models in which item parameters for one item at a time were allowed to vary by group, with all other items fitted with parameters constrained to be the same across both groups. The likelihood ratio test was used to explore the presence of DIF. Items showing DIF were dropped from the refined version.
Limitations of the present study include the lack of clinical data (e.g., gold-standard diagnostic instruments), reliance on informant report of diagnoses, reliance on a single method of data collection (i.e., questionnaires), and a single informant (one parent/caregiver). Further multimethod investigation is needed in a sample who have received standardized clinical assessments. We note that a similar pattern of results was reported by Chowdhury et al. (2016) with respect to links between the HSQ and other measures in a clinic-based ASD sample. Although common rater-bias could have inflated the strength of detected relations, we were able to detect differential links across measures, suggesting that this did not compromise the findings.
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There is also a significant racial disparity in the STEM education pipeline, though part of this is due to gaps in educational attainment that are not necessarily STEM-specific (Lim, Haddad, Butler, & Giglio, 2013). Students from minority ethnic groups are less likely to have access to high school math and science courses that allow them to build the skills necessary for STEM degrees. As with women, both racial stereotypes and a lack of diversity in mentorship are cited as obstacles for students of color studying STEM (Grandy, 1998; Strayhorn, DeVita, & Blakewood, 2012). Though nearly two-thirds of students who initially major in STEM have not dropped that major three years later, the percentage of Black and Hispanic students who graduate with a STEM degree is far lower than the number who showed interest in STEM fields upon entering university (Anderson & Kim, 2006).
Not all data could be combined to research all questions of interest, as not all the data sources contained the same identifiers required to combine the data. For example, the FEVS data was reported at the agency level and not the individual employee level; thus, it is not possible to combine that data on a one-to-one basis with EHRI data, which is individual level data. Furthermore, EEOC complaint data does not include occupation; thus, it is not possible to report the number of EEO complaints that are specific to Federal Women in STEM employees. Also, as noted above, this report examines only full-time, permanent federal employees in OPM classifications identified as STEM occupations; the list of STEM occupations was obtained from FedScope and may be reviewed there.[2]
Before delving into specific demographic characteristics of women in STEM occupations, it is necessary to understand the basic participation of women in STEM occupations, relative to men. Table 1 below provides the overall STEM demographics for women in STEM occupational groups.
The overall average age of women in STEM occupations is 45.5 years compared to the average age of 47.4 years for men. Figure 1 below demonstrates that women in STEM occupations are, on average, younger than their male counterparts. Women in engineering are the youngest (x=42.68 years), while women in Technology (x=49.74 years) are the oldest.
More women with disabilities are needed within Science, Engineering, and Math occupations, since only the participation of women with disabilities in Technology met the 12 percent goal threshold for the federal workforce. None of the occupations met the 2 percent goal.
In addition to understanding where women are currently working, it is important to understand where there should be greater female representation. Thus, we analyzed the expected participation of women in specific categories based upon their overall numbers in STEM occupations; the results are presented in Table 4 below.
Glass, J., Sassler, S., Levitte, Y., & Michelmore, K. (2013). What's so special about STEM? A comparison of women's retention in STEM and professional occupations. Social Forces, 92(2), 723-756. www.jstor.org/stable/43287810
National Academy of Sciences, National Academy of Engineering, & Institute of Medicine (2011). Expanding underrepresented minority participation: America's Science and Technology talent at the crossroads. Washington, DC: National Academies Press.
Riegle-Crumb, C., King, B., Grodsky, E., & Muller, C. (2012). The more things change, the more they stay the same? Prior achievement fails to explain gender inequality in entry into STEM college majors over time. American Educational Research Journal, 49(6), 1048-1073. doi:10.3102/0002831211435229 2ff7e9595c
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