BackgroundOptic nerve head measurements extracted from optical coherence tomography (OCT) show promise for monitoring clinical conditions with elevated optic nerve heads. The aim of this study is to compare reliability within and between raters and between image acquisition devices of optic nerve measurements derived from OCT scans in eyes with varying degrees of optic nerve elevation.MethodsWide angle line scans and narrow angle radial scans through optic nerve heads were obtained using three spectral domain(SD) OCT devices on 5 subjects (6 swollen optic nerves, 4 normal optic nerves). Three raters independently semi-manually segmented the internal limiting membrane(ILM) and Bruch’s membrane(BM) on each scan using customized software. One rater segmented each scan twice. Segmentations were qualitatively and quantitatively compared. Inter-rater, intra-rater and inter-device reliability was assessed for the optic nerve cross sectional area calculated from the ILM and BM segmentations using intraclass correlation coefficients and graphical comparison.ResultsLine scans from all devices were qualitatively similar. Radial scans for which frame rate could not be adjusted were of lower quality. Intra-rater reliability for segmentation and optic nerve cross sectional area was better than inter-rater reliability, which was better than inter-device reliability, though all ICC exceeded 0.95. Reliability was not impacted by the degree of optic nerve elevation.ConclusionsSD-OCT devices acquired similar quality scans of the optic nerve head, with choice of scan protocol affecting the quality. For image derived markers, variability between devices was greater than that attributable to inter and intra-rater differences.

Background: Misclassification bias is introduced into medical claims-based research because of reliance on diagnostic coding rather than full medical record review. We sought to characterize this bias for idiopathic intracranial hypertension (IIH) and evaluate strategies to reduce it. Methods: A retrospective review of medical records was conducted using a clinical data warehouse containing medical records and administrative data from an academic medical center. Patients with 1 or more instances of International Classification of Diseases (ICD)-9 or -10 codes for IIH (348.2 or G93.2) between 1989 and 2017 and original results of neuroimaging (head CT or MRI), lumbar puncture, and optic nerve examination were included in the study. Diagnosis of IIH was classified as definite, probable, possible, or inaccurate based on review of medical records. The positive predictive value (PPV) for IIH ICD codes was calculated for all subjects, subjects with an IIH code after all testing was completed, subjects with high numbers of IIH ICD codes and codes spanning longer periods, subjects with IIH ICD codes associated with expert encounters (ophthalmology, neurology, or neurosurgery), and subjects with acetazolamide treatment. Results: Of 1,005 patients with ICD codes for IIH, 103 patients had complete testing results and were included in the study. PPV of ICD-9/-10 codes for IIH was 0.63. PPV in restricted samples was 0.82 (code by an ophthalmologist n = 57), 0.70 (acetazolamide treatment n = 87), and 0.72 (code after all testing, n = 78). High numbers of code instances and longer duration between the first and last code instance also increased the PPV. Conclusions: An ICD-9 or -10 code for IIH had a PPV of 63% for probable or definite IIH in patients with necessary diagnostic testing performed at a single institution. Coding accuracy was improved in patients with an IIH ICD code assigned by an ophthalmologist. Use of coding algorithms consider-ing treatment providers, number of codes, and treatment is a potential strategy to reduce misclassification bias in medical claims-based research on IIH. However, these are associated with a reduced sample size.

Background:Misclassification bias is introduced into medical claims–based research because of reliance on diagnostic coding rather than full medical record review. We sought to characterize this bias for idiopathic intracranial hypertension (IIH) and evaluate strategies to reduce it.Methods:A retrospective review of medical records was conducted using a clinical data warehouse containing medical records and administrative data from an academic medical center. Patients with 1 or more instances of International Classification of Diseases (ICD)-9 or -10 codes for IIH (348.2 or G93.2) between 1989 and 2017 and original results of neuroimaging (head CT or MRI), lumbar puncture, and optic nerve examination were included in the study. Diagnosis of IIH was classified as definite, probable, possible, or inaccurate based on review of medical records. The positive predictive value (PPV) for IIH ICD codes was calculated for all subjects, subjects with an IIH code after all testing was completed, subjects with high numbers of IIH ICD codes and codes spanning longer periods, subjects with IIH ICD codes associated with expert encounters (ophthalmology, neurology, or neurosurgery), and subjects with acetazolamide treatment.Results:Of 1,005 patients with ICD codes for IIH, 103 patients had complete testing results and were included in the study. PPV of ICD-9/-10 codes for IIH was 0.63. PPV in restricted samples was 0.82 (code by an ophthalmologist n = 57), 0.70 (acetazolamide treatment n = 87), and 0.72 (code after all testing, n = 78). High numbers of code instances and longer duration between the first and last code instance also increased the PPV.Conclusions:An ICD-9 or -10 code for IIH had a PPV of 63% for probable or definite IIH in patients with necessary diagnostic testing performed at a single institution. Coding accuracy was improved in patients with an IIH ICD code assigned by an ophthalmologist. Use of coding algorithms considering treatment providers, number of codes, and treatment is a potential strategy to reduce misclassification bias in medical claims–based research on IIH. However, these are associated with a reduced sample size.

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