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  • 1
    Online Resource
    Online Resource
    Emergency Department Visits Following Suboccipital Decompression for Adult Chiari Malformation Type I
    Ovid Technologies (Wolters Kluwer Health) ; 2020
    In:  Neurosurgery Vol. 67, No. Supplement_1 ( 2020-12)
    Details
    In: Neurosurgery, Ovid Technologies (Wolters Kluwer Health), Vol. 67, No. Supplement_1 ( 2020-12)
    Type of Medium: Online Resource
    ISSN: 0148-396X
    URL: Article
    DOI: 10.1093/neuros/nyaa447_781
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2020
    detail.hit.zdb_id: 1491894-8
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  • 2
    Online Resource
    Online Resource
    162 Recruiting Women Into Neurosurgery: A Quantitative Analysis of Feeder Medical School Characteristics
    Ovid Technologies (Wolters Kluwer Health) ; 2022
    In:  Neurosurgery Vol. 68, No. Supplement_1 ( 2022-04), p. 48-48
    Details
    In: Neurosurgery, Ovid Technologies (Wolters Kluwer Health), Vol. 68, No. Supplement_1 ( 2022-04), p. 48-48
    Type of Medium: Online Resource
    ISSN: 0148-396X , 1524-4040
    URL: Article
    DOI: 10.1227/NEU.0000000000001880_162
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2022
    detail.hit.zdb_id: 1491894-8
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  • 3
    Online Resource
    Online Resource
    External validation of current prediction systems of improvement after decompression surgery in Chiari malformation type I patients: can we do better?
    Journal of Neurosurgery Publishing Group (JNSPG) ; 2021
    In:  Journal of Neurosurgery Vol. 134, No. 5 ( 2021-05), p. 1466-1471
    Details
    In: Journal of Neurosurgery, Journal of Neurosurgery Publishing Group (JNSPG), Vol. 134, No. 5 ( 2021-05), p. 1466-1471
    Abstract: The Chiari Severity Index (CSI) and points-based algorithm of Thakar et al. are two prognostic tools that have been developed to predict the likelihood of improvement after suboccipital decompression in adult patients with Chiari malformation type I (CM-I). This study aimed to externally validate and critically evaluate these algorithms in the interest of guiding the development of improved prediction systems. METHODS A consecutive cohort of CM-I patients undergoing suboccipital decompression between September 2006 and September 2018 were included. The CSI and Thakar point score were computed for all patients, and associations with improvement were analyzed. The ability of both prediction systems to predict improvement as measured by different Chicago Chiari Outcome Scale (CCOS) cutoffs was assessed using receiver operating curve analysis. Post hoc correlations between the algorithms and different CCOS subcomponents were also assessed. RESULTS The surgical cohort was composed of 149 adult CM-I patients, of whom 39 (26%) had a syrinx. Most patients experienced improvement after surgery (80% CCOS ≥ 13; 96% CCOS ≥ 11). The proportion of patients improving decreased with increasing CSI, but the results were not statistically significant (p = 0.246). No statistically significant difference in the mean Thakar point score was identified between improved and nonimproved patients using both CCOS cutoffs (p = 0.246 for a cutoff of 13 and p = 0.480 for a cutoff of 11). The CSI had a poor ability in identifying improved patients at a CCOS cutoff of 13 (area under the curve [AUC] 0.582) and 11 (AUC 0.646). The Thakar point score similarly had poor discrimination at a cutoff of 13 (AUC 0.467) and 11 (AUC 0.646). Neither algorithm had significant correlation with any of the CCOS subcomponents except for CSI and nonpain symptom improvement (coefficient = −0.273, p = 0.001). CONCLUSIONS Previously published algorithms failed to provide prediction value with regard to clinically meaningful improvement following suboccipital decompression in adult CM-I patients. Future models and practical scoring systems are still required to improve the decision-making process.
    Type of Medium: Online Resource
    ISSN: 0022-3085 , 1933-0693
    URL: Article
    DOI: 10.3171/2020.2.JNS20181
    RVK:
    XA 10000
    RVK:
    XA 55270
    Language: Unknown
    Publisher: Journal of Neurosurgery Publishing Group (JNSPG)
    Publication Date: 2021
    detail.hit.zdb_id: 2026156-1
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  • 4
    Online Resource
    Online Resource
    Which medical schools produce the most neurosurgery residents? An analysis of the 2014–2020 cohort
    Journal of Neurosurgery Publishing Group (JNSPG) ; 2022
    In:  Journal of Neurosurgery Vol. 137, No. 1 ( 2022-07-01), p. 283-295
    Details
    In: Journal of Neurosurgery, Journal of Neurosurgery Publishing Group (JNSPG), Vol. 137, No. 1 ( 2022-07-01), p. 283-295
    Abstract: In this study, the authors sought to determine which US medical schools have produced the most neurosurgery residents and to evaluate potential associations between recruitment and medical school characteristics. METHODS Demographic and bibliometric characteristics were collected for 1572 residents in US-based and Accreditation Council for Graduate Medical Education (ACGME)–accredited neurosurgery programs over the 2014 to 2020 match period using publicly available websites. US medical school characteristics were collected, including class size, presence of a home neurosurgery program, number of clinical neurosurgery faculty, research funding, presence of a neurosurgery interest group, and a top 10 ranking via U.S. News & World Report or Doximity. Correlations and associations were then evaluated using Pearson’s correlation coefficient (PCC), independent-samples t-test, and univariable or stepwise multivariable linear regression, as appropriate. RESULTS Vanderbilt University produced the most neurosurgery residents as a percentage of medical graduates at 3.799%. Case Western Reserve University produced the greatest absolute number of neurosurgery residents (n = 40). The following factors were shown to be associated with a higher mean percentage of graduates entering neurosurgery: number of clinical neurosurgery faculty (PCC 0.509, p 〈 0.001), presence of a neurosurgery interest group (1.022% ± 0.737% vs 0.351% ± 0.327%, p 〈 0.001) or home neurosurgery program (1.169% ± 0.766% vs 0.428% ± 0.327%, p 〈 0.001), allopathic compared with osteopathic school (0.976% ± 0.719% vs 0.232% ± 0.272%, p 〈 0.001), U.S. News top 10 ranking for neurology and neurosurgery (1.923% ± 0.924% vs 0.757% ± 0.607%, p 〈 0.001), Doximity top 10 residency program ranking (1.715% ± 0.803% vs 0.814% ± 0.688%, p 〈 0.001), and amount of NIH funding (PCC 0.528, p 〈 0.001). CONCLUSIONS The results of this study have delineated which medical schools produced the most neurosurgery residents currently in training, and the most important independent factors predicting the percentage of graduates entering neurosurgery and the preresidency h -index.
    Type of Medium: Online Resource
    ISSN: 0022-3085 , 1933-0693
    URL: Article
    DOI: 10.3171/2021.7.JNS211530
    RVK:
    XA 10000
    RVK:
    XA 55270
    Language: Unknown
    Publisher: Journal of Neurosurgery Publishing Group (JNSPG)
    Publication Date: 2022
    detail.hit.zdb_id: 2026156-1
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  • 5
    Online Resource
    Online Resource
    Recruitment of women in neurosurgery: a 7-year quantitative analysis
    Journal of Neurosurgery Publishing Group (JNSPG) ; 2023
    In:  Journal of Neurosurgery Vol. 138, No. 1 ( 2023-01-01), p. 251-260
    Details
    In: Journal of Neurosurgery, Journal of Neurosurgery Publishing Group (JNSPG), Vol. 138, No. 1 ( 2023-01-01), p. 251-260
    Abstract: The authors aimed to characterize which US medical schools have the most female neurosurgery residents and to identify potential associations between medical school characteristics and successful recruitment of women pursuing a neurosurgery career. METHODS The authors evaluated a total of 1572 residents in US neurosurgery programs accredited by the Accreditation Council for Graduate Medical Education as of February 2021, representing match cohorts from 2014 to 2020. The authors extracted US medical school characteristics and ranked schools based on the percentages of women graduates entering neurosurgery. They additionally studied yearly trends of the percentage of women constituting incoming neurosurgery resident cohorts as well as associations between female recruitment percentage and medical school characteristics using univariable and stepwise multivariable linear regression (including significant univariable factors). RESULTS The cohort consisted of 1255 male and 317 (20%) female residents. Yearly trends indicated a significant drop in incoming female residents in 2016, followed by significant increases in 2017 and 2019. On multivariable analysis, the following factors were associated with a higher average percentage of female graduates entering neurosurgery: total affiliated neurosurgery clinical faculty (β = 0.006, 95% CI 0.001–0.011, p = 0.01), allopathic versus osteopathic schools (β = 0.231, 95% CI 0.053–0.409, p = 0.01), and top 10 U.S. News & World Report ranking (β = 0.380, 95% CI 0.129–0.589, p 〈 0.01). When the number of female clinical faculty was added to the model, the variable was not statistically significant. Multivariable bibliometric analyses indicated a higher mean preresidency H-index for men, with an even greater gender difference identified in the 2021 H-index. CONCLUSIONS This study characterizes which medical schools are most successful at recruiting female students who constituted the total neurosurgery resident workforce of the 2020–2021 academic year. The overall number of clinical neurosurgery faculty rather than faculty gender was independently associated with female recruitment. Gender differences in research productivity persisted with control for confounders and increased between preresidency and 2021 time points. Such understanding of factors that influence the recruitment of women can help improve female representation in neurosurgery residency training moving forward.
    Type of Medium: Online Resource
    ISSN: 0022-3085 , 1933-0693
    URL: Article
    DOI: 10.3171/2022.4.JNS22410
    RVK:
    XA 10000
    RVK:
    XA 55270
    Language: Unknown
    Publisher: Journal of Neurosurgery Publishing Group (JNSPG)
    Publication Date: 2023
    detail.hit.zdb_id: 2026156-1
    Location Call Number Limitation Availability
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