No abstract available.
Cerebral Palsy*

This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.

This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.

This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.

This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.

To compare mortality rate, the adjustment of case-mix variables is needed. The Pediatric Index of Mortality (PIM) 3 score is a widely used case-mix adjustment system of a pediatric intensive care unit (ICU), but there has been no validation study of it in Korea. We aim to validate the PIM3 in a Korean pediatric ICU, and extend the validation of the score from those aged 0–16 to 0–18 years, as patients aged 16–18 years are admitted to pediatric ICU in Korea. A retrospective cohort study of 1,710 patients was conducted in a tertiary pediatric ICU. To validate the score, the discriminatory power was assessed by calculating the area under the receiver-operating characteristic (ROC) curve, and calibration was evaluated by the Hosmer-Lemeshow goodness-of-fit (GOF) test. The observed mortality rate was 8.47%, and the predicted mortality rate was 6.57%. For patients aged < 18 years, the discrimination was acceptable (c-index = 0.76) and the calibration was good, with a χ² of 9.4 in the GOF test (P = 0.313). The observed mortality rate in the hemato-oncological subgroup was high (18.73%), as compared to the predicted mortality rate (7.13%), and the discrimination was unacceptable (c-index = 0.66). In conclusion, the PIM3 performed well in a Korean pediatric ICU. However, the application of the PIM3 to a hemato-oncological subgroup needs to be cautioned. Further studies on the performance of PIM3 in pediatric patients in adult ICUs and pediatric ICUs of primary and secondary hospitals are needed.
Adult ; Benchmarking ; Calibration ; Child ; Cohort Studies ; Critical Care* ; Discrimination (Psychology) ; Humans ; Intensive Care Units* ; Korea* ; Mortality* ; Retrospective Studies ; Risk Adjustment

OBJECTIVE: To investigate the serum vitamin D level and its determinant factors in stroke patients. METHODS: Fifty-one stroke patients who had documented serum level of 25-hydroxyvitamin D(25(OH)D) were included. Patients were divided into subacute (n=23) and chronic groups (n=28). The mean levels of 25(OH)D of the two groups were compared. Correlations between each 25(OH)D level and post-stroke duration were also analyzed. To assess other possible influencing factors, patients were subdivided by ambulation ability and feeding methods for comparison of 25(OH)D level. RESULTS: The mean level of 25(OH)D was significantly lower in the chronic group than in the subacute group (12.3 vs. 16.3 ng/mL; p < 0.05). The serum 25(OH)D level decreased according to the duration after stroke (r=−0.52, p=0.01). Patients with a history of total parenteral nutrition had lower 25(OH)D levels than subjects who had enteral nutrition in the subacute group (7.3 vs. 18.8 ng/mL; p < 0.01). However, the levels of 25(OH)D were not different between the oral feeding and tube feeding groups. Among the chronic group subjects, patients who could walk without assistance had higher 25(OH)D levels than non-ambulatory patients (ambulatory vs. non-ambulatory group; 18.3 vs. 11.3 ng/mL; p < 0.05). CONCLUSION: After stroke onset, serum vitamin D level decreases with time regardless of feeding methods, and total parenteral nutrition may aggravate its deficiency. In terms of long-term care, non-ambulatory patients might be at a higher risk of vitamin D deficiency. Supplementation of vitamin D should be considered especially for stroke patients who are non-ambulatory and on total parenteral nutrition.
Enteral Nutrition ; Feeding Methods ; Humans ; Long-Term Care ; Parenteral Nutrition, Total ; Stroke* ; Vitamin D Deficiency ; Vitamin D* ; Vitamins* ; Walking

OBJECTIVE: To investigate the serum vitamin D level and its determinant factors in stroke patients. METHODS: Fifty-one stroke patients who had documented serum level of 25-hydroxyvitamin D(25(OH)D) were included. Patients were divided into subacute (n=23) and chronic groups (n=28). The mean levels of 25(OH)D of the two groups were compared. Correlations between each 25(OH)D level and post-stroke duration were also analyzed. To assess other possible influencing factors, patients were subdivided by ambulation ability and feeding methods for comparison of 25(OH)D level. RESULTS: The mean level of 25(OH)D was significantly lower in the chronic group than in the subacute group (12.3 vs. 16.3 ng/mL; p < 0.05). The serum 25(OH)D level decreased according to the duration after stroke (r=−0.52, p=0.01). Patients with a history of total parenteral nutrition had lower 25(OH)D levels than subjects who had enteral nutrition in the subacute group (7.3 vs. 18.8 ng/mL; p < 0.01). However, the levels of 25(OH)D were not different between the oral feeding and tube feeding groups. Among the chronic group subjects, patients who could walk without assistance had higher 25(OH)D levels than non-ambulatory patients (ambulatory vs. non-ambulatory group; 18.3 vs. 11.3 ng/mL; p < 0.05). CONCLUSION: After stroke onset, serum vitamin D level decreases with time regardless of feeding methods, and total parenteral nutrition may aggravate its deficiency. In terms of long-term care, non-ambulatory patients might be at a higher risk of vitamin D deficiency. Supplementation of vitamin D should be considered especially for stroke patients who are non-ambulatory and on total parenteral nutrition.
Enteral Nutrition ; Feeding Methods ; Humans ; Long-Term Care ; Parenteral Nutrition, Total ; Stroke* ; Vitamin D Deficiency ; Vitamin D* ; Vitamins* ; Walking

PURPOSE: Comorbidities have been considered a mortality risk factor in pediatric critical care patients. We studied the characteristics and prognostic factors of children without comorbidities who were admitted to the intensive care unit (ICU) due to respiratory failure. METHODS: We reviewed the medical charts of patients (< 18 years) admitted to the ICU for respiratory support in a single tertiary center between January 2006 and December 2016. Patients with comorbidities and perioperative statuses were excluded. RESULTS: Of the 4,712 ICU patients, 73 (1.5%) were included in this study. The median age was 31 months (8–57) and 51 (69.9%) were boys. Twenty-nine patients (39.7%) presented with pneumonia, 14 (19.2%) with acute respiratory distress syndrome (ARDS), and 11 (15.1%) with obstructive airway disease. The median duration of ICU hospitalization was 5 days (2–14.5), and 45 of the 73 patients (61.6%) needed mechanical ventilation. Mortality was 13.7% (10/73). None of the patients with pneumonia or obstructive airway disease died. The most frequent cause of death was ARDS (5 of 10, 50%). In adjusted analysis, the extent of extrapulmonary organ dysfunction was significantly associated with mortality (odds ratio, 2.89; 95% confidence interval, 1.17–7.11; P=0.023). CONCLUSION: The mortality rate of previously healthy pediatric patients needing respiratory support in the ICU should not be negligible. Multiple organ dysfunctions might be a significant risk factor for mortality in such patients.
Cause of Death ; Child* ; Comorbidity ; Critical Care* ; Hospitalization ; Humans ; Intensive Care Units* ; Mortality ; Pneumonia ; Respiration, Artificial ; Respiratory Distress Syndrome, Adult ; Respiratory Insufficiency ; Risk Factors

Objective: To establish and evaluate the validity of the recently developed Korean version of the Oxford Cognitive Screen (K-OCS), this study verified its reliability, validity, and diagnostic accuracy. Methods: Between November 2021 and December 2023, we recruited 72 patients with stroke from our hospital who agreed to participate in the study. The patients were repeatedly tested using K-OCS by the same or different assessors to estimate inter- and intra-rater reliability. To demonstrate the validity and usability of K-OCS, the test results of screening tools currently used in clinical practice, including the Korean-Mini Mental State Examination and the Korean version of the Montreal Cognitive Assessment, were used in comparison analyses. Results: The subtests of K-OCS demonstrated excellent inter-rater reliability (intra-class correlation coefficient [ICC]=0.914–0.998) and test–retest reliability (ICC=0.913–0.994). We found moderate-to-strong correlations for convergent validity for the subsets (r=0.378– 0.979, p<0.01), and low-to-moderate discriminant validity correlations. The optimal cut-offs estimated for the subtests of the K-OCS showed a good-to-high range of specificity (94.8%– 100%). The positive predictive value was 58.2%–100% and negative predictive value was 65.6%–98.4%. Sensitivity was estimated at 25.6%–86.9%. Conclusion The results of this study indicate that K-OCS is a reliable and valid tool for screening cognitive impairment in patients post-stroke.