Bilateral high origin and superficial trajectory of the deep femoral artery: clinical and applied anatomy

ABSTRACT The anatomy of the femoral triangle is explored in various approaches, ranging from pulse verification to invasive catheterization procedures. Within the femoral triangle, the deep femoral artery is one of the vessels reported to present several anatomical variations that must be considered before clinical or surgical interventions. Here, we are reporting a unique bilateral variation of the deep femoral artery for medical education purposes and reflecting on its applied, surgical, and clinical anatomy. During the dissection of the femoral triangle, we observed that the deep femoral artery originated in the vicinity of the inguinal ligament and ran in parallel with the femoral artery in a superficial trajectory on both sides of the donor. On the right side, the DFA continued superficial for 8.8 cm, with an origin of 1.2 cm inferior to the inguinal ligament. On the left side, it presented a similar anatomical arrangement, though with an origin of 1.6cm inferior to the inguinal ligament and a superficial course of 5cm. The position of the lateral circumflex femoral vein posterior to the deep femoral artery played a role in this distinctive, lengthy, and superficial presentation of the deep femoral artery. This anatomical variation directly affects surgical procedures, diagnostics, and endovascular interventions. A deep femoral artery with such a lengthy superficial trajectory can be mistakenly used for catheterization instead of the femoral artery or be injured, disrupting the main blood supply of the thigh muscles.

SeroTracker-RoB: A decision rule-based algorithm for reproducible risk of bias assessment of seroprevalence studies.

Risk of bias (RoB) assessments are a core element of evidence synthesis but can be time consuming and subjective. We aimed to develop a decision rule-based algorithm for RoB assessment of seroprevalence studies. We developed the SeroTracker-RoB algorithm. The algorithm derives seven objective and two subjective critical appraisal items from the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence studies and implements decision rules that determine study risk of bias based on the items. Decision rules were validated using the SeroTracker seroprevalence study database, which included non-algorithmic RoB judgments from two reviewers. We quantified efficiency as the mean difference in time for the algorithmic and non-algorithmic assessments of 80 randomly selected articles, coverage as the proportion of studies where the decision rules yielded an assessment, and reliability using intraclass correlations comparing algorithmic and non-algorithmic assessments for 2070 articles. A set of decision rules with 61 branches was developed using responses to the nine critical appraisal items. The algorithmic approach was faster than non-algorithmic assessment (mean reduction 2.32 min [SD 1.09] per article), classified 100% (n = 2070) of studies, and had good reliability compared to non-algorithmic assessment (ICC 0.77, 95% CI 0.74-0.80). We built the SeroTracker-RoB Excel Tool, which embeds this algorithm for use by other researchers. The SeroTracker-RoB decision-rule based algorithm was faster than non-algorithmic assessment with complete coverage and good reliability. This algorithm enabled rapid, transparent, and reproducible RoB evaluations of seroprevalence studies and may support evidence synthesis efforts during future disease outbreaks. This decision rule-based approach could be applied to other types of prevalence studies.

Timeliness of reporting of SARS-CoV-2 seroprevalence results and their utility for infectious disease surveillance.

Seroprevalence studies have been used throughout the COVID-19 pandemic to monitor infection and immunity. These studies are often reported in peer-reviewed journals, but the academic writing and publishing process can delay reporting and thereby public health action. Seroprevalence estimates have been reported faster in preprints and media, but with concerns about data quality. We aimed to (i) describe the timeliness of SARS-CoV-2 serosurveillance reporting by publication venue and study characteristics and (ii) identify relationships between timeliness, data validity, and representativeness to guide recommendations for serosurveillance efforts. We included seroprevalence studies published between January 1, 2020 and December 31, 2021 from the ongoing SeroTracker living systematic review. For each study, we calculated timeliness as the time elapsed between the end of sampling and the first public report. We evaluated data validity based on serological test performance and correction for sampling error, and representativeness based on the use of a representative sample frame and adequate sample coverage. We examined how timeliness varied with study characteristics, representativeness, and data validity using univariate and multivariate Cox regression. We analyzed 1844 studies. Median time to publication was 154 days (IQR 64-255), varying by publication venue (journal articles: 212 days, preprints: 101 days, institutional reports: 18 days, and media: 12 days). Multivariate analysis confirmed the relationship between timeliness and publication venue and showed that general population studies were published faster than special population or health care worker studies; there was no relationship between timeliness and study geographic scope, geographic region, representativeness, or serological test performance. Seroprevalence studies in peer-reviewed articles and preprints are published slowly, highlighting the limitations of using the academic literature to report seroprevalence during a health crisis. More timely reporting of seroprevalence estimates can improve their usefulness for surveillance, enabling more effective responses during health emergencies.