A 10-year review of assault-related open-globe injuries at an urban hospital.

Graefes Arch Clin Exp Ophthalmol

Institute of Ophthalmology and Visual Sciences, New Jersey Medical School, University of Medicine and Dentistry of New Jersey, Doctors Office Building, Suite 6100, 90 Bergen Street, Newark, NJ 07103, USA.

Published: March 2013

Background: To describe the demographics and outcomes of assault-related open-globe injuries (OGI) at University Hospital (UH), Newark, New Jersey over a ten-year period.

Methods: The medical records of all subjects presenting to a single university referral center with an OGI were retrospectively analyzed to identify prognostic factors for enucleation and final visual acuity (VA) of no light perception (NLP).

Results: One hundred and forty-eight eyes of 147 patients presented to UH with assault-related OGI. Eighty-two percent of patients were male, and the mean age was 35.9 years. The anatomic site of the wound was zone 3 in the majority (54.1 %) of eyes. Most common type of injury noted was rupture (57.4 %), followed by penetrating injury (35.1 %). Mean initial presenting and final VA in LogMAR were 2.38 ± 0.12 and 2.18 ± 0.16 respectively. Initial Snellen VA was no light perception (NLP) in 57 eyes (38.5 %); four eyes had an initial VA of ≥ 20/40 (2.7 %). Final VA was NLP in 68 eyes (45.9 %) of which 46 were enucleated (31.1 %); 18 eyes (12.2 %) had a final VA of ≥ 20/40. Fifty eyes (33.8 %) underwent pars plana vitrectomy (PPV). Significant risk factors of final VA of NLP or enucleation included initial VA of NLP, perforating or rupture type of OGI, and zone 3 injury. Eyes that sustained penetrating injuries were less likely to have final VA of NLP or require enucleation.

Conclusions: Assault-related OGIs carry an extremely poor visual prognosis and a high rate of enucleations. Only eighteen eyes (12.2 %) recovered VA ≥ 20/40. We found initial VA of NLP and zone 3 injury to be significant predictors of final VA of NLP or undergoing enucleation. Penetrating injuries were less likely to have a final VA of NLP or an enucleation.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00417-012-2136-zDOI Listing

Publication Analysis

Top Keywords

final nlp
20
≥ 20/40
12
eyes
9
assault-related open-globe
8
open-globe injuries
8
final
8
light perception
8
nlp
8
nlp eyes
8
eyes 122
8

Similar Publications

Background: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence of their real-world effectiveness remains unclear.

Objective: To summarise the evidence on the effectiveness of NLP/ML in detecting ADEs from unstructured EHR data and ultimately improve pharmacovigilance in comparison to other data sources.

View Article and Find Full Text PDF

Public Health.

Alzheimers Dement

December 2024

Peninsula Clinical School, Central Clinical School, Monash University, Melbourne, VIC, Australia.

Background: Population dementia prevalence is traditionally estimated using cohort studies, surveys, routinely-collected administrative data, and registries. Hospital Electronic Health Records (EHRs) are comprised of rich structured and unstructured (text) clinical data that are underutilised for this purpose. We aimed to develop a suite of algorithms using routinely-collected EHR data to reliably identify cases of dementia, as a key step towards incorporating such data in prevalence estimation.

View Article and Find Full Text PDF
Article Synopsis
  • The study explores using natural language processing to analyze text responses from gamers as a potential complement to traditional rating scales for measuring gaming disorders.
  • Researchers compared a new tool with 4 open-ended questions to a widely-used numerical rating scale, aiming to see if the qualitative data could enhance understanding of gaming-related mental states.
  • After processing responses from 417 participants using a language model called HerBERT, they applied machine learning to predict gaming disorder scores based on the open-ended answers.
View Article and Find Full Text PDF

Paradigm shifts: exploring AI's influence on qualitative inquiry and analysis.

Front Res Metr Anal

December 2024

Teesside University International Business School, TU Online, Teesside University, Middlesbrough, United Kingdom.

Article Synopsis
  • Technology is generally compatible with qualitative research methods, but AI—specifically in automating qualitative analysis—poses challenges to interpretivist assumptions, raising questions about validity and ethics.
  • AI tools like Natural Language Processing can expedite data analysis but may risk missing the nuances of human communication that a human researcher would interpret.
  • The article suggests a balanced approach, advocating for partial automation to improve efficiency while maintaining human oversight, and hints at the emergence of new research paradigms that may better suit the digital age.
View Article and Find Full Text PDF

Objective: Natural language processing (NLP) can enhance research studies for febrile infants by more comprehensive cohort identification. We aimed to refine and validate an NLP algorithm to identify and extract quantified temperature measurements from infants aged 90 days and younger with fevers at home or clinics prior to emergency department (ED) visits.

Patients And Methods: We conducted a cross-sectional study using electronic health record (EHR) data from 17 EDs in 10 health systems that are part of the Pediatric Emergency Care Applied Research Network Registry.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!