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1.
J Anat ; 241(2): 245-258, 2022 08.
Article in English | MEDLINE | ID: mdl-35357009

ABSTRACT

The vascular supply of the human auditory ossicles has long been of anatomical and clinical interest. While the external blood supply has been well-described, there is only limited information available regarding the internal vascular architecture of the ossicles, and there has been little comparison of this between individuals. Based on high-resolution micro-CT scans, we made reconstructions of the internal vascular channels and cavities in 12 sets of ossicles from elderly donors. Despite considerable individual variation, a common basic pattern was identified. The presence of channels within the stapes footplate was confirmed. The long process of the incus and neck of the stapes showed signs of bony erosion in all specimens examined. More severe erosion was associated with interruption of some or all of the main internal vascular channels which normally pass down the incudal long process; internal excavation of the proximal process could interrupt vascular channels in ossicles which did not appear to be badly damaged from exterior inspection. An awareness of this possibility may be helpful for surgical procedures that compromise the mucosal blood supply. We also calculated ossicular densities, finding that the malleus tends to be denser than the incus. This is mainly due to a lower proportion of vascular channels and cavities within the malleus.


Subject(s)
Ear Ossicles , Incus , Aged , Ear, Middle , Humans , Malleus , Tomography, X-Ray Computed
2.
JAMA Netw Open ; 3(9): e2015909, 2020 09 01.
Article in English | MEDLINE | ID: mdl-32886123

ABSTRACT

Importance: Electronic health records are a potentially valuable source of information for identifying patients with opioid use disorder (OUD). Objective: To evaluate whether proxy measures from electronic health record data can be used reliably to identify patients with probable OUD based on Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (DSM-5) criteria. Design, Setting, and Participants: This retrospective cross-sectional study analyzed individuals within the Geisinger health system who were prescribed opioids between December 31, 2000, and May 31, 2017, using a mixed-methods approach. The cohort was identified from 16 253 patients enrolled in a contract-based, Geisinger-specific medication monitoring program (GMMP) for opioid use, including patients who maintained or violated contract terms, as well as a demographically matched control group of 16 253 patients who were prescribed opioids but not enrolled in the GMMP. Substance use diagnoses and psychiatric comorbidities were assessed using automated electronic health record summaries. A manual medical record review procedure using DSM-5 criteria for OUD was completed for a subset of patients. The analysis was conducted beginning from June 5, 2017, until May 29, 2020. Main Outcomes and Measures: The primary outcome was the prevalence of OUD as defined by proxy measures for DSM-5 criteria for OUD as well as the prevalence of comorbidities among patients prescribed opioids within an integrated health system. Results: Among the 16 253 patients enrolled in the GMMP (9309 women [57%]; mean [SD] age, 52 [14] years), OUD diagnoses as defined by diagnostic codes were present at a much lower rate than expected (291 [2%]), indicating the necessity for alternative diagnostic strategies. The DSM-5 criteria for OUD can be assessed using manual medical record review; a manual review of 200 patients in the GMMP and 200 control patients identifed a larger percentage of patients with probable moderate to severe OUD (GMMP, 145 of 200 [73%]; and control, 27 of 200 [14%]) compared with the prevalence of OUD assessed using diagnostic codes. Conclusions and Relevance: These results suggest that patients with OUD may be identified using information available in the electronic health record, even when diagnostic codes do not reflect this diagnosis. Furthermore, the study demonstrates the utility of coding for DSM-5 criteria from medical records to generate a quantitative DSM-5 score that is associated with OUD severity.


Subject(s)
Documentation/statistics & numerical data , Electronic Health Records/statistics & numerical data , Opioid-Related Disorders/diagnosis , Adult , Aged , Cross-Sectional Studies , Documentation/methods , Female , Humans , Male , Middle Aged , Opioid-Related Disorders/physiopathology , Prevalence , Retrospective Studies
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