New polynomial regression formula to improve second-eye refractive outcomes in sequential bilateral cataract surgery.

PURPOSE: To assess a new polynomial regression formula integrating the refractive prediction error of the first-operated eye to improve the intraocular lens power calculation of the second eye in cataract surgery. SETTING: Centre Hospitalier Universitaire, Toulouse, France. DESIGN: Retrospective multicentric dataset study. METHODS: A polynomial regression formula, WeOptimeye2nd (WO2nd), was developed using a machine-learning algorithm trained on a dataset of 534 patients who underwent sequential bilateral cataract surgery. A separate multicentric dataset was used to retrospectively calculate predicted refraction with WO2nd, SRK/T and Barrett Universal II formulas, and 3 other methods of constant factors (CFs) second-eye refinement (CF0.38, CF0.35, and CF0.5). Mean absolute errors (MAEs) and percentage of eyes within ±0.25, ±0.5, and ±1.0 diopter (D) from predicted spherical equivalent were compared between formulas. RESULTS: The study comprised data on 722 patients. In the overall population, WO2nd had the lowest MAE: 0.339 vs 0.347 (P = .137), 0.340 (P = .956), 0.350 (P = .066), 0.399 (P < .001), and 0.410 (P < .001), with CF0.38, CF0.5, and CF0.35, Barrett II, and SRK/T, respectively. WO2nd had the highest percentage of eyes within ±0.5 D of the predicted refraction, and the difference was statistically significant vs SRK/T and Barrett II formulas but not vs CF0.38, CF0.5, and CF0.35. WO2nd performed the best in axial length (AL) < 22 mm with the lowest MAE and a statistically significant difference vs any other formula. CONCLUSIONS: WO2nd improved the refractive outcome of the second-operated eye and performed well in extreme AL and mean keratometry subgroups.

Prevalence of metabolic syndrome components in a population of bank employees from St. Petersburg, Russia.

BACKGROUND: The aim of this study was to assess prevalence of metabolic syndrome and its components according to different criteria in the population of bank employees in St. Petersburg, Russia. METHODS: A total of 1,600 office workers were screened at their working places from the Sberbank state bank in St. Petersburg. All subjects were interviewed by a special questionnaire that included personal data, smoking status, physical activity, alcohol consumption, and medical history. Anthropometry measurements, vital signs, and fasting blood samples were obtained. Serum lipids and plasma glucose were measured. RESULTS: In all, 1,561 responders were included in the final analysis. Hypertension (HTN) was observed in 35.2% of subjects (64% in males and 25.4% in females), abdominal obesity (AO) according to Internation Diabetes Federation (IDF) criteria in 45.6% (51.5% in males and 44.0% in females), high triglyceride levels in 28.4%, low high-density lipoprotein cholesterol (HDL-C) levels in 23.9%, and elevated fasting glucose over 5.6 mmol/L in 28.4% of subjects. AO associated with HTN was observed in 24.3%. Metabolic syndrome according to IDF criteria was diagnosed in 21.5% (17.9% in females and 34.6% in males, P<0.01), and according to Adult Treatment Panel III (ATP III) (2005) criteria in 18.8% of subjects (16.2% in females and 28.4% in males, P<0.01). The correlation between criteria was ρ(S)=0.79. Low physical activity, smoking, and alcohol abuse were associated with metabolic syndrome. CONCLUSIONS: Metabolic syndrome and its distinct components were very prevalent in Russian bank office workers. AO was most prevalent component for females with metabolic syndrome, whereas HTN was most prevalent for males. Coexistence of HTN and AO was the most frequent coupling of metabolic syndrome components. Unhealthy lifestyle characterized the selected group and was associated with metabolic syndrome, especially low physical activity.