Chasing the objective upper eyelid symmetry formula; R2, RMSE, POC, MAE, and MSE.

PURPOSE: Investigate the most appropriate mathematical formula to objectively express upper eyelid contour symmetry. METHODS: 62 eyes of 31 patients were included in the study. The upper eyelid contour symmetry of the patients was classified subjectively (independent of MRD1) as poor, acceptable, and good by three oculoplastic specialists (senior, expert, and junior surgeon). Bézier curves of the upper lid contour were drawn with ImageJ software (NIH, Bethesda, MA, USA). Using the algorithms created by Author SKC in Spyder (Python 3.7.9.), the symmetry of the Bézier curves of the left eyelids were obtained according to the y-axis, and the mid-pupils of both eyes were superimposed. The lower curve moved vertically to the equal height of the other curve to equalize MRD1's. R2 (Coefficient of determination), RMSE (Root-mean-square error), MSE (Mean squared error), POC (Percentage of co-efficiency), and MAE (Mean absolute error) were calculated. We evaluated the correlation between these objective formulas and the subjective grading of three surgeons using Spearman's rho (ρ). RESULTS: The correlation coefficient of RMSE and MSE were the same for all surgeons grading. There was a strong correlation between the senior surgeon's subjective scoring (N; poor = 8, acceptable = 16, good = 8) and R2, RMSE, POC, MAE (ρ = 0.643, p < 0.001, ρ = -0.607, p < 0.001, ρ = 0.562, p < 0.001, ρ = -0.517, p < 0.001, respectively). We found a strong relationship between the expert surgeon's subjective scoring (N; poor = 9, acceptable = 13, good:10) and R2 (ρ = 0.611, p < 0.001), RMSE (ρ = -0.549, p < 0.001), POC (ρ = 0.511, p < 0.001), and MAE (ρ = -0.450, p < 0.05). We found a strong correlation between junior surgeon's subjective scoring (N; poor = 6, acceptable = 18, good = 8) and R2, RMSE, and POC (ρ: -0.517, p < 0.001; ρ: -0.470, p < 0.001; ρ: 0.521, p < 0.001; respectively) and moderate correlation between MAE (ρ:-0.394, p < 0.05). The highest correlation is observed with R2. CONCLUSIONS: RMSE, MSE, POC, MAE, and especially R2, may quantitatively express upper eyelid contour symmetry, comparable with the oculoplastic surgeon. The highest correlation was observed between the senior surgeon and R2, and decreases with the experience of the surgeon.

Muller muscle conjunctival resection or external levator advancement; a quantitative comparison of symmetry in unilateral ptosis.

PURPOSE: To compare muller muscle conjunctival resection (MMCR) and external levator advancement (ELA) in terms of objective and subjective symmetry in unilateral ptosis. METHODS: The patients who underwent unilateral MMCR (group1, n = 25) and ELA (group2, n = 25) were reviewed retrospectively. With the written algorithm, margin reflex distance-1 (MRD1), localization of the contour peak, and the percentage of overlapping curvatures (POC) of both upper eyelid curves were calculated. Semi-automated measurements were compared with the manual measurements. The correlation between objective and subjective symmetry was evaluated. RESULTS: Preoperative levator functions were similar in both groups (13.93 ± 3.25 mm and 13.3 ± 2.86 mm, respectively). We found strong correlations between manual and semi-automated measurements (ICC: 0.942, 95% CI = 0.924-0.956, p < 0.001). Preoperative MRD1 (2.15 ± 0.90 vs 1.51 ± 1.01, p = 0.022) and POC was lower in group 2 (66% vs 47.2%, p = 0.01). In the postoperative period, the increase in MRD1 and POC were similar in both groups (p = 0.2 and p = 0.7 respectively), and the contour peak displaced temporally (p < 0.01) providing a symmetric peak in both groups. Subjective symmetry increased as the difference in MRD1 between two eyes decreased (r = -0.456, p = 0.001), and POC increased (r = 0.396, p = 0.004). CONCLUSIONS: Besides subjective symmetry, MMCR and ELA are equally effective in ensuring symmetry objectively, as measured with MRD1 and contour peak symmetry and POC in unilateral ptosis. POC may be used as a criterion of symmetry in the evaluation of ptosis.

A decision support system for scheduling the shifts of physicians during COVID-19 pandemic.

The rapidly spreading COVID-19 pandemic has affected many people worldwide. Due to the high infectivity, countries make calls to stay at home or take measures such as lockdowns to ensure that people are least affected by the virus. Meanwhile, infected people are getting treatments: people who are slightly affected are quarantined at home, and those who are heavily affected are treated in hospitals. Hence there is an excessive increase in the hospital workload. This causes physical fatigue in healthcare professionals. Along with the increasing workload, the fear of being infected and infecting the environment causes psychological problems in healthcare professionals. It is important to protect healthcare professionals and provide them with suitable working conditions. For this reason, besides the provision of protective equipment such as gloves, overalls, mask, and glasses that are necessary for the protection of healthcare workers from the virus, healthcare services should also be planned very carefully. One of the critical issues is planning the shift schedules of the physicians. In this study, we handle the preparation of a physician shift schedule of a hospital in Turkey during the COVID-19 pandemic. The hospital has established three new COVID-19 related departments and the aim is to provide continuous service in the new departments while maintaining the workload in the existing departments. We propose a mixed integer programming (MIP) model to address the shift scheduling problem and transform it into a decision support system (DSS). The resulting schedules minimize the exposure of the physicians to the virus with a balanced workload while maintaining the healthcare service in all departments.