PURPOSE: To establish and validate a formula to predict spectral domain (SD)-optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) thickness from time domain (TD)-OCT RNFL measurements and other factors. METHODS: SD-OCT and TD-OCT scans were obtained on the same day from healthy participants and patients with glaucoma. Univariate and multivariate linear regression relationships were analyzed to convert average Stratus TD-OCT measurements to average Cirrus SD-OCT measurements. Additional baseline characteristics included age, sex, intraocular pressure, central corneal thickness, spherical equivalent, anterior chamber depth, optic disc area, visual field (VF) mean deviation, and pattern standard deviation. The formula was generated using a training set of 220 patients and then evaluated on a validation dataset of 105 patients. RESULTS: The training set included 71 healthy participants and 149 patients with glaucoma. The validation set included 27 healthy participants and 78 patients with glaucoma. Univariate analysis determined that TD-OCT RNFL thickness, age, optic disc area, VF mean deviation, and pattern standard deviation were significantly associated with SD-OCT RNFL thickness. Multivariate regression analysis using available variables yielded the following equation: SD-OCT RNFL = 0.746 x TD-OCT RNFL + 17.104 (determination coefficient [R2] = 0.879). In the validation sample, the multiple regression model explained 85.6% of the variance in the SD-OCT RNFL thickness. CONCLUSIONS: The proposed formula based on TD-OCT RNFL thickness may be useful in predicting SD-OCT RNFL thickness. Other factors associated with SD-OCT RNFL thickness, such as age, disc area, and mean deviation, did not contribute to the accuracy of the final equation.
*Algorithms ; Female ; Glaucoma/*pathology ; Humans ; Linear Models ; Male ; Middle Aged ; Predictive Value of Tests ; Retinal Ganglion Cells/*pathology ; Tomography, Optical Coherence/*methods

BACKGROUND: Malnutrition is common in hospitalized patients, especially in critically ill patients and affects their mortality and morbidity. However, the correlation between malnutrition and poor outcome is not fully understood. Our hypothesis is that the nutritional effect on the patient's prognosis would differ depending on the severity of the disease. METHODS: 3,758 patients admitted to the intensive care unit (ICU) were observed retrospectively. Patients were divided into well, moderate and severe groups, according to their nutritional status as assessed by their serum albumin level and total lymphocyte count (TLC). The severity of the disease was assessed by the Acute Physiologic and Chronic Health Evaluation (APACHE II score). All patients were followed clinically until discharge or death and ICU days, hospital days, ventilator days, and mortality rates were recorded. RESULTS: Depending on the definition used, the prevalence of hospital malnutrition is reported to be 68.3%. Hospital days, ICU days, as well as ventilator days of moderate and severe groups were longer than the well group. In patients exhibiting mild severity of disease, moderate and severe malnutrition groups have 3-5 times the mortality rate than the well group. CONCLUSIONS: Malnutrition affects the prognosis of patients who have an APACHE II score ranging from 4-29 points. Active nutritional support may be more effective for patients with a disease of mild severity.
APACHE ; Critical Illness ; Humans ; Intensive Care Units ; Lymphocyte Count ; Malnutrition ; Nutritional Status ; Nutritional Support ; Prevalence ; Prognosis ; Retrospective Studies ; Serum Albumin ; Ventilators, Mechanical

No abstract available.