Purpose: To find the most appropriate color-coded scales for the anterior and posterior elevation maps of scanning slit topography in the screening of abnormal corneas such as keratoconus.
Design: Retrospective case-control study.
Participants: Eighty eyes of 40 normal subjects and 175 eyes of 95 patients with keratoconus.
Intervention: Anterior and posterior corneal elevations were assessed using Orbscan 2. Best-fit sphere maps were drawn with several color-coded scales: 2-, 5-, 10-, and 20-microm height per each color interval.
Main Outcome Measures: The maps were judged to be abnormal when more than three colors (discriminant number) were found within the central 3-mm area. For each color-coded scale, sensitivity, specificity, positive predictive value, negative predictive value, and sensitivity + specificity were calculated. After determining the most appropriate color-coded scales for the anterior and posterior elevation maps, validity of the discriminant number was assessed. By varying the discriminant number from two to eight, receiver operator characteristic (ROC) curves were created using the sensitivity and specificity for each threshold number.
Results: The highest sensitivity + specificity values and highly balanced predictive values were obtained with the 10- and 20-microm scales for the anterior and posterior elevation maps, respectively. The ROC curve analyses showed that the best discriminant color number is three, indicating that maps with four or more colors within the central 3-mm area are judged abnormal in screening.
Conclusions: The 10- and 20-microm interval color scales are most appropriate for the anterior and posterior elevation maps of the scanning slit topography, respectively.
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http://dx.doi.org/10.1016/s0161-6420(02)01030-8 | DOI Listing |
Neurosurg Rev
January 2025
Department of Spine Surgery, Lishui Hospital of Wenzhou Medical University, Lishui People's Hospital, Lishui, Zhejiang, China.
At present, the choice of approach for the surgical treatment of cervical ossification of the posterior longitudinal ligament (OPLL) remains controversial. We performed this meta-analysis to compare the efficacy of the anterior and posterior approaches in the treatment of cervical OPLL. PubMed, EMBASE and the Cochrane Library were systematically searched for all eligible articles as of August 3, 2023, without any publication date restrictions.
View Article and Find Full Text PDFJ Burn Care Res
January 2025
Indiana University, Division of Plastic Surgery, Indianapolis, IN, USA.
Burn injuries in patients with significant pre-existing medical conditions provide unique challenges in both medical management and surgical planning. Spasticity, if left untreated, can be one of the most disabling consequences of a neurologic injury. Treatment is largely dependent on pharmacologic management with anti-spasmodic agents such as baclofen.
View Article and Find Full Text PDFGinekol Pol
January 2025
VM Medical Park Maltepe Hospital, Istanbul, Türkiye.
Objectives: To investigate the outcomes of central cystocele and rectocele repair using natural tissue layers. To describe a novel technique (Dogan technique).
Material And Methods: This is a retrospective cohort study.
Curr Eye Res
January 2025
Sussex Eye Hospital, Brighton & Sussex University Hospitals NHS Trust, Brighton, UK.
Purpose: To assess the relationship between angle kappa (apparent chord mu) and ocular parameters in cataract patients.
Methods: In this cross-sectional study, the data on apparent chord mu, age, axial length, anterior chamber depth, anterior and posterior mean keratometry, mean total keratometry, white-to-white, central corneal thickness and lens thickness were collected for consecutive cataract patients. Correlation (Pearson) between chord mu and the other ocular parameters was calculated.
Osteoarthr Cartil Open
March 2025
Department for Health Sciences, Medicine and Research, University of Continuing Education Krems, Krems, Austria.
Objective: Lower limb malalignment can complicate symptoms and accelerate knee osteoarthritis (OA), necessitating consideration in study population selection. In this study, we develop and validate a deep learning model that classifies leg alignment as "normal" or "malaligned" from knee antero-posterior (AP)/postero-anterior (PA) radiographs alone, using an adjustable hip-knee-ankle (HKA) angle threshold.
Material And Methods: We utilized 8878 digital radiographs, including 6181 AP/PA full-leg x-rays (LLRs) and 2697 AP/PA knee x-rays (2292 with positioning frame, 405 without).
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