Purpose: Semantic segmentation is a fundamental part of the surgical application of deep learning. Traditionally, segmentation in vision tasks has been performed using convolutional neural networks (CNNs), but the transformer architecture has recently been introduced and widely investigated. We aimed to investigate the performance of deep learning models in segmentation in robot-assisted radical prostatectomy (RARP) and identify which of the architectures is superior for segmentation in robotic surgery. Materials and Methods: Intraoperative images during RARP were obtained. The dataset was randomly split into training and validation data. Segmentation of the surgical instruments, bladder, prostate, vas and seminal vesicle was performed using three CNN models (DeepLabv3, MANet, and U-Net++) and three transformers (SegFormer, BEiT, and DPT), and their performances were analyzed. Results: The overall segmentation performance during RARP varied across different model architectures. For the CNN models, DeepLabV3 achieved a mean Dice score of 0.938, MANet scored 0.944, and U-Net++ reached 0.930. For the transformer architectures, SegFormer attained a mean Dice score of 0.919, BEiT scored 0.916, and DPT achieved 0.940. The performance of CNN models was superior to that of transformer models in segmenting the prostate, vas, and seminal vesicle. Conclusions Deep learning models provided accurate segmentation of the surgical instruments and anatomical structures observed during RARP. Both CNN and transformer models showed reliable predictions in the segmentation task; however, CNN models may be more suitable than transformer models for organ segmentation and may be more applicable in unusual cases. Further research with large datasets is needed.

Objective: Emergency medical system reform is an important part of the 4th Emergency Medical Care 5-year plan in Korea, published in 2023. However, little is known about the current emergency department (ED) utilization status of local emergency medical agencies (EMAs). We sought to compare the ED utilization code between the emergency medical centers (EMCs) (n=58) and the local EMAs (n=152) based on parameters such as the admission rate or transfer rate in patients with a critical illness. Methods: Consecutive emergency patients registered on the National Emergency Department Information System from January 2022 to December 2022 were included in this study and their records were analyzed. The study included critically ill patients who were defined as having a critical illness code. Results: Among 590,878 (EMC of 450,007; local EMA of 140,871) critical illness code patients, the admission rate was 76.2% for EMCs and 52.9% for local EMAs. Of the critical illness code patients who visited local EMAs, 89.4% were Korean Triage and Acuity Scale (KTAS) grade 3-5 patients. The hospitalization volume of critical illness code patients in the local EMAs was 74,571, mostly major trauma (47.5%) and ischemic stroke (11.5%). If KTAS grade 1 or 2 patients could not be transferred to the local EMAs, the EMCs covered up to 14,989 ED patients and 74,571 admitted patients additionally. Conclusion If the local EMAs maintain their current roles in the areas of major trauma and ischemic stroke, and take charge of the admission of patients with critical illness codes transferred from the EMC after emergency treatment, then the local EMAs can still maintain their functions even after the proposed emergency medical system reform.

Background: Various regional analgesia techniques are used to reduce postoperative pain in patients undergoing video-assisted thoracic surgery (VATS). This study aimed to determine the relative efficacy of regional analgesic interventions for VATS using a network meta-analysis (NMA). Methods: We searched the Medline, EMBASE, Cochrane Controlled Trial Register, Web of Science, and Google Scholar databases to identify all randomized controlled trials (RCTs) that compared the analgesic effects of the following interventions: control, thoracic paravertebral block (TPVB), erector spinae plane block (ESPB), serratus plane block (SPB), and intercostal nerve block (INB). The primary outcome was opioid consumption during the first 24-h postoperative period. Pain scores were also collected during three different postoperative periods: the early (0–6 h), middle (6–18 h), and late (18–24 h) periods. Results: A total of 21 RCTs (1391 patients) were included. TPVB showed the greatest effect on opioid consumption compared with the control (mean difference [MD] = −13.2 mg; 95% CI [−16.2, −10.1]). In terms of pain scores in the early period, ESPB had the greatest effect compared to control (MD = −1.6; 95% CI [−2.3, −0.9]). In the middle and late periods, pain scores showed that TPVB, ESPB and INB had superior analgesic effects compared to controls, while SPB did not. Conclusions TPVB had the best analgesic efficacy following VATS, though the analgesic efficacy of ESPBs was comparable. However, further studies are needed to determine the optimal regional analgesia technique to improve postoperative pain control following VATS.

Purpose: To seek Pearson correlations of tear film osmolarity measured by the I-PEN® (I-MED Pharma Inc., Dollard-des-Ormeaux, Canada) with Schirmer test result, tear break-up time, and Ocular Surface Disease Index score in patients with mild dry eye syndrome. Methods: Patients with mild dry eye syndrome were divided into two groups according to Ocular Staining Score: group 1 (50 patients; 67 eyes) and group 2 (59 patients; 91 eyes), 90 patients and 158 eyes in total. The above mentioned correlations were derived. Results: No significant correlations were observed between tear film osmolarity and Schirmer test result (r < -0.01, p = 0.97), tear break-up time (r = 0.05, p = 0.54), or Ocular Surface Disease Index score (r = 0.03, p = 0.76). When the two groups were compared, the Ocular Surface Disease Index score significantly differed between groups (p < 0.01), whereas the Schirmer test result (p = 0.31), tear break-up time (p = 0.11), and tear film osmolarity (p = 0.12) did not. Conclusions No significant correlations were found between tear film osmolarity and other dry eye indicators in patients with mild dry eye syndrome. The diagnostic utility of tear film osmolarity in patients with moderate dry eye syndrome is should be evaluated.

Purpose: To seek Pearson correlations of tear film osmolarity measured by the I-PEN® (I-MED Pharma Inc., Dollard-des-Ormeaux, Canada) with Schirmer test result, tear break-up time, and Ocular Surface Disease Index score in patients with mild dry eye syndrome. Methods: Patients with mild dry eye syndrome were divided into two groups according to Ocular Staining Score: group 1 (50 patients; 67 eyes) and group 2 (59 patients; 91 eyes), 90 patients and 158 eyes in total. The above mentioned correlations were derived. Results: No significant correlations were observed between tear film osmolarity and Schirmer test result (r < -0.01, p = 0.97), tear break-up time (r = 0.05, p = 0.54), or Ocular Surface Disease Index score (r = 0.03, p = 0.76). When the two groups were compared, the Ocular Surface Disease Index score significantly differed between groups (p < 0.01), whereas the Schirmer test result (p = 0.31), tear break-up time (p = 0.11), and tear film osmolarity (p = 0.12) did not. Conclusions No significant correlations were found between tear film osmolarity and other dry eye indicators in patients with mild dry eye syndrome. The diagnostic utility of tear film osmolarity in patients with moderate dry eye syndrome is should be evaluated.

Purpose: To calculate the intraocular lens (IOL) power using the Shammas-PL formula after laser in-situ keratomileusis (LASIK). Methods: Forty-one eyes of 29 patients that had undergone cataract surgery from September 2018 to September 2019 after LASIK were enrolled in this study. A preoperative AL-Scan® (Nidek Co., Gamagori, Japan) was used to measure the axial length, anterior chamber depth, and corneal curvature. An IOL power calculation was performed using the Shammas-PL (post LASIK) formula. Mean absolute error (MAE) and mean arithmetic error (MARE) were calculated using preoperative manifest refraction and postoperative manifest refraction. Results: Of the 41 eyes, 15 eyes (36.6%) were relatively hyperopic-shifted after surgery compared to the predicted refractive error before surgery, 25 eyes (61%) showed a relative myopic shift, and one eye (2.4%) showed no change with respect to the previous refractive predicted error. Refractive errors before cataract surgery were not related to myopic, emmetropic, or hyperopic shifting after surgery (p > 0.05). Conclusions When cataract surgery using the Shammas-PL formula was performed after LASIK, myopic shifting was more common than hyperopic shifting. The MAE was greater in myopic-shifted cases than that of hyperopic-shifted cases. Thus, it is better to determine IOL power toward the hyperopic side than the target refractive prediction.

Purpose: To investigate the safety of laser epithelial keratomileusis (LASEK) by drawing a comparison between two groups divided according to age (18-19 vs. 20-21 years old). Methods: The study was conducted as a retrospective analysis including 339 patients (678 eyes) who underwent LASEK between January 2017 and April 2020. Patients were divided by age group, group I (18-19 years old) and group II (20-21 years old). The objectives of the study included determination of visual acuity and refractive errors before and at 1, 3, and 6 months after the procedure. Results: The preoperative mean spherical equivalents (SEs) were -4.73 ± 0.88 diopters (D) in group I and -4.58 ± 0.87 D in group II (p = 0.34). At 1 month postoperatively, mean SEs were 0.32 ± 0.46 D in group I and 0.26 ± 0.59 D in group II (p = 0.18). At 3 months postoperatively, the mean SEs were 0.30 ± 0.47 D in group I and 0.28 ± 0.50 D in group II (p = 0.67). At 6 months postoperatively, the mean SEs were 0.15 ± 0.47 D in group I and 0.14 ± 0.50 D in group II (p = 0.89). There were no significant differences in postoperative best corrected visual acuity between group I and group II at 1, 3, or 6 months (p = 0.20, p = 0.13, and p = 0.11, respectively). Conclusions There were no significant differences in postoperative mean SE or safety of LASEK between moderate myopia patients 18-19 years old and those 20-21 years old.

Purpose: To compare the accuracy of standard and total keratometry data obtained using the Barrett Universal II and Barrett Toric Calculator. Methods: In total, 111 eyes of 111 patients who visited our hospital for cataract surgery from February 2019 to September 2019 were included in this study. Total keratometry and standard keratometry data were obtained using the Barrett Universal II and the Barrett Toric Calculator; mean absolute errors were derived by using preoperative IOL Master 700® (Carl Zeiss Meditech AG, Jena, Germany) data and 2-month postoperative manifest refraction data. The mean absolute errors of the two methods were compared in terms of a posterior corneal astigmatism greater than 0.3 diopter (D) in patients fitted with Toric intraocular lenses. Results: Using the Barrett Universal II formula, the mean absolute error spherical equivalent difference between total keratometry and standard keratometry was 0.021 ± 0.102 D (p = 0.65) when the Barrett Toric Calculator was used. The mean absolute error differences between the two methods were 0.015 ± 0.121 D for the spherical equivalent (p = 0.80) and 0.005 ± 0.870 D for the cylinder measurement (p = 0.94). In terms of a posterior corneal astigmatism greater than 0.3 D, the mean absolute error spherical equivalent and cylinder measurement differences were -0.020 ± 0.107 D (p = 0.70) and -0.023 ± 0.055 D (p = 0.50) in patients fitted with Toric intraocular lenses. Conclusions The total keratometry method, which directly measures posterior corneal curvature, yields data comparable to those of the standard keratometry method. When the posterior corneal astigmatism was greater than 0.3 D, we found no significant difference between the total keratometry and standard keratometry data of patients fitted with Toric intraocular lenses.

Purpose: The Eyelike K-flex Aspheric® (Koryoeyetech, Seoul, Korea) is manufactured in 0.25-diopter (D) intervals, which allows the target refractive error after surgery to be achieved. We here evaluate the refractive power outcomes. Methods: We retrospectively studied 95 eyes of 72 patients who underwent cataract surgery with implantation of the Eyelike K-flex Aspheric®. Refractive error was measured at 1 and 2 months postoperatively (33 eyes of 27 patients) and compared to that of patients fitted with 0.50-D-interval lenses (62 eyes of 49 patients). Results: At 1 month postoperatively, the mean absolute error between the spherical equivalent and planned value was 0.33 ± 0.28 and 0.41 ± 0.39 D in the 0.25- and 0.50 D-interval lens groups, respectively (p = 0.318). At 2 months postoperatively, the respective values were 0.21 ± 0.15 and 0.34 ± 0.29 D (p = 0.009). Conclusions The Eyelike K-flex Aspheric® shows excellent refractive predictability; use of 0.25-D-interval intraocular lenses close to the target refractive power allows the desired spherical equivalent to be achieved.

Purpose: To compare the accuracy of standard and total keratometry data obtained using the Barrett Universal II and Barrett Toric Calculator. Methods: In total, 111 eyes of 111 patients who visited our hospital for cataract surgery from February 2019 to September 2019 were included in this study. Total keratometry and standard keratometry data were obtained using the Barrett Universal II and the Barrett Toric Calculator; mean absolute errors were derived by using preoperative IOL Master 700® (Carl Zeiss Meditech AG, Jena, Germany) data and 2-month postoperative manifest refraction data. The mean absolute errors of the two methods were compared in terms of a posterior corneal astigmatism greater than 0.3 diopter (D) in patients fitted with Toric intraocular lenses. Results: Using the Barrett Universal II formula, the mean absolute error spherical equivalent difference between total keratometry and standard keratometry was 0.021 ± 0.102 D (p = 0.65) when the Barrett Toric Calculator was used. The mean absolute error differences between the two methods were 0.015 ± 0.121 D for the spherical equivalent (p = 0.80) and 0.005 ± 0.870 D for the cylinder measurement (p = 0.94). In terms of a posterior corneal astigmatism greater than 0.3 D, the mean absolute error spherical equivalent and cylinder measurement differences were -0.020 ± 0.107 D (p = 0.70) and -0.023 ± 0.055 D (p = 0.50) in patients fitted with Toric intraocular lenses. Conclusions The total keratometry method, which directly measures posterior corneal curvature, yields data comparable to those of the standard keratometry method. When the posterior corneal astigmatism was greater than 0.3 D, we found no significant difference between the total keratometry and standard keratometry data of patients fitted with Toric intraocular lenses.