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Cauda equina syndrome (CES) is an uncommon condition that can lead to permanent neurological deficits if not diagnosed and addressed promptly. Varying prognoses, including retropulsed fracture fragments, disc herniations, and epidural abscesses, can result in CES. Our objective was to identify the top 50 most impactful articles on CES and analyze the characteristics of these publications. In August of 2021, we used the Web of Science Core Collection bibliographic database to query the phrase "cauda equina syndrome." Articles between 1900 and 2021 were included in the search, and these articles were ranked based on the number of citations. The following variables were recorded: title, first author, journal, year of publication, number of citations, country of origin, the institution of publication, and topic of the paper. A total of 2096 articles matched the search criteria. The top 50 most impactful articles ranged from 43 to 439 in their number of citations. All articles on the list were published in English, with the year of publication ranging from 1938 to 2014. The United States accounted for the greatest number of articles published at 27. The medical journal Spine accounted for the greatest number of publications at nine. And the 2000s was the decade with the most cited articles. It is generally acknowledged that the clinical signals for CES are diverse with no predictive value on patient outcomes. Similar uncertainty exists in the etiology of the condition, though CES induced by spinal anesthesia is a factor of particular interest. Additionally, it is generally recognized that delayed diagnosis of the condition often results in permanent neurological deficits. Identification of the most impactful articles on CES is critical in drawing attention to this significant condition.

Introduction:The purpose of this study was to demonstrate a novel technology used to measure improvements in quality and value of care for treatment of hip fracture patients.Methods:A novel value-based triaging methodology uses a risk prediction (risk M) and inpatient cost prediction (risk C) algorithm and has been demonstrated to accurately predict high-risk:high-cost episodes of care. Two hundred twenty-nine hip fracture patients from 2014 to 2016 were used to establish baseline length of stay (LOS) and total inpatient cost for each (16) risk:cost quadrants. Two hundred sixty-five patients between 2017 and 2019 with hip fractures were input into the algorithm, and historical LOS and cost for each patient were calculated. Historical values were compared with actual values to determine whether the value of the inpatient episode of care differed from the 2014 to 16 cohort.Results:When evaluated without risk or cost stratification, the mean actual LOS and cost of the baseline cohort compared with the 2017 to 2019 cohort were 8.0 vs 7.5 days (P = 0.43) and $25,446 vs $29,849 (P = 0.15), respectively. This analysis demonstrates that there was only a small change in value of care provided to patients based on LOS/cost over the studied period; however, risk:cost analysis using the novel methodology demonstrated that for select risk:cost quadrants, value of care measured by LOS/cost improved, whereas for others it decreased and for others there was no change.Conclusion:Risk-cost–adjusted analysis of inpatient episodes of care rendered by a value-based triaging methodology provides a robust method of assessing improvements and/or decreases in value-based care when compared with a historical cohort. This methodology provides the tools to both track hospital interventions designed to improve quality and decrease cost as well as determine whether these interventions are effective in improving value.

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