Background: While wearing face shields and other gears to protect the facial mucous membranes not covered by face masks are proven to decrease the odds of infection in the hospital setting, there is no concrete evidence of its efficacy in the general public. Objective: To determine the effectiveness of face shield use in the general public in the local setting. Methods: This study utilized an ecological study design, with the weeks when the policy was implemented serving as the exposure variable while the weeks when the policy was not in effect, whether prior to or after, serving as control. Primary outcomes were mean incidence of COVID-19 and case fatality rate (CFR) per week. Results: When the mandatory face shield use was implemented, the mean incidence of COVID-19 per week was higher compared to weeks when it was not implemented [93 cases per 1000 population per week (ptpw) vs 65 cases, relative risk:1.43, z=-3.79, p=0.0001]. Moreover, during weeks when only less than 50% of the population was vaccinated with first dose (93 cases ptpw vs 52 cases, RR: 1.79, z=-4.3, p<0.0001) and complete doses (93 cases ptpw vs 66 cases ptpw, RR:1.41, z=-3.69, p=0.0002), the mean incidence of COVID-19 per week were statistically higher in weeks when face shield use was in effect. Controlling the status of vaccination and the predominant strain, face shield use increased the incidence of COVID-19 cases ptpw by 38 (F=13, R2=39%, p=0.026) to 50 (F=3.06, R2=12.2%, p=0.032) compared to no face shield use. No difference in CFR between weeks with face shield use and no face shield use was seen (29 deaths ptpw vs 32 deaths per ptpw, p=1.0). Nevertheless, when the weeks with no vaccination (27 deaths ptpw vs 48 deaths ptpw, RR=0.56, p=0.0018), less than 50% of the population were vaccinated with f irst dose (30 deaths ptpw vs 50 deaths ptpw, RR:0.6, p=0.0005), and complete doses (30 deaths vs 47 deaths ptpw, RR:0.64, p=0.0042) were only considered, face shield use significantly decreased the mean CFR per week. Controlling the incidence rate of COVID-19, vaccination status, and prevalent strain, face shield use decreases the number of deaths by 26 per 1000 COVID-19 diagnosed cases (F=7.4, R2=28.3, p=0.010). Conclusions In general, although face shield use increased susceptibility to COVID-19, it decreased case fatality rate in the Philippines. However, a more robust and controlled study in the future may be needed to truly justify its recommendation for the public.
COVID-19 ; epidemiology ; public health ; Philippines

Introduction: Movement restrictions and changes in medical education around the world due to the Coronavirus 2019 pandemic have been sources of stress, which affect sleep and compound the demands of medical education. In the Philippines, stay-at-home orders were implemented in the National Capital Region on 15 March 2020, and despite various readjustments and re-definitions, remain in effect to date, March 2022. Objectives. This cross-sectional study aims to determine the sleep quality and daytime sleepiness of Filipino medical students during prolonged stay-at-home orders, to compare them with pre-pandemic evaluations, and to explore associations between scores and participant characteristics. Methods: The medical student population of a state-run university in the City of Manila was included, while those on a leave of absence were excluded. The Epworth Sleepiness Scale and the Pittsburgh Sleep Quality Index which measure excessive daytime sleepiness and sleep quality, respectively, were disseminated via Google Forms from April to May 2021. Results: Response rate was 87.75% (n=709) with a mean age of 22.9 ± 2.0 years and a 1:1.09 male-to-female ratio. Among the respondents, 41.18% had excessive daytime sleepiness, and was significantly higher for first-year premedicine students. Compared to pre-pandemic scores, daytime sleepiness decreased during the pandemic. On the other hand, 62.34% of the respondents had poor sleep quality, with global scores being significantly higher for the first-year pre-medicine students. Relationships between participants' characteristics and their scores were extremely weak, while a moderately significant correlation existed between global daytime sleepiness and sleep quality scores. Conclusion Both excessive daytime sleepiness and poor sleep quality remain prevalent during prolonged stay-athome orders. These reflect the effect of the pandemic on stress inherent to medical education, and may be additional facets to be regarded in evaluating the general well-being of medical students.
SARS-CoV-2

Introduction: Movement restrictions and changes in medical education around the world due to the Coronavirus 2019 pandemic have been sources of stress, which affect sleep and compound the demands of medical education. In the Philippines, stay-at-home orders were implemented in the National Capital Region on 15 March 2020, and despite various readjustments and re-definitions, remain in effect to date, March 2022. Objectives. This cross-sectional study aims to determine the sleep quality and daytime sleepiness of Filipino medical students during prolonged stay-at-home orders, to compare them with pre-pandemic evaluations, and to explore associations between scores and participant characteristics. Methods: The medical student population of a state-run university in the City of Manila was included, while those on a leave of absence were excluded. The Epworth Sleepiness Scale and the Pittsburgh Sleep Quality Index which measure excessive daytime sleepiness and sleep quality, respectively, were disseminated via Google Forms from April to May 2021. Results: Response rate was 87.75% (n=709) with a mean age of 22.9 ± 2.0 years and a 1:1.09 male-to-female ratio. Among the respondents, 41.18% had excessive daytime sleepiness, and was significantly higher for first-year premedicine students. Compared to pre-pandemic scores, daytime sleepiness decreased during the pandemic. On the other hand, 62.34% of the respondents had poor sleep quality, with global scores being significantly higher for the first-year pre-medicine students. Relationships between participants' characteristics and their scores were extremely weak, while a moderately significant correlation existed between global daytime sleepiness and sleep quality scores. Conclusion Both excessive daytime sleepiness and poor sleep quality remain prevalent during prolonged stay-athome orders. These reflect the effect of the pandemic on stress inherent to medical education, and may be additional facets to be regarded in evaluating the general well-being of medical students.
SARS-CoV-2

Background and Significance: Sleep is a vital facet of human existence that is vital to learning and memory; lack of sleep is associated with significant impairment in learning. Medical students are a special population because of the demands of medical school. They are very prone to sleep deprivation and poor quality of sleep, hence academic performance might be affected. Objectives: We determined the different sleeping habits of medical students using a descriptive tool, with variables chosen specifically for this study. The level of sleepiness was then correlated with the academic performance (using the general weighted average) among students in a state university run-medical school in the Philippines. Methods: The study is a prospective cross-sectional survey among medical students in a state university-run medical school enrolled for the academic year 2016-2017. The questionnaires used were the Epworth Sleepiness Score and specific questions about sleeping habits. The General Weighted Average (GWA) of those who participated were obtained from the student records section of the college. Descriptive statistics were used to describe the results on different sleeping habits, while the chi-squared test was used to determine any significant differences in the GWA versus level of sleepiness across all year levels. Results: A total of 426 medical students (or 60% of the total student population of the college) participated. However, of the 426, only 326 had complete GWAs and were therefore included in the final analysis for correlation. The average medical student is “sleep-deprived”, sleeping two hours less (six hours) than the recommended daily minimum duration of sleep (eight to 10 hours). For the correlation of sleepiness and academic performance, we found out that there is no significant difference in academic performance among those who are excessively sleepy (ESS greater than 10) versus those who are not, p-value = 0.892. Conclusion Increased level of sleepiness does not correlate with poorer academic performance among these medical students, despite them sleeping less than the general recommendation for adults. The study is limited however by the use of the GWA as the sole tool to measure academic performance, which is affected by many other factors. We recommend the performance of this study in a broader population and use more validated tools to measure sleepiness and academic performance.
Sleep ; Sleepiness ; Academic Performance ; Students, Medical

Objectives. We determined the prevalence of patients at risk for obstructive sleep apnea (OSA) with uncontrolled type 2 diabetes mellitus (T2DM) at the out-patient department (OPD) of the University of the Philippines-Philippine General Hospital (UP-PGH) from December 1, 2018 - February 28, 2019. We described the demographic characteristics of patients with uncontrolled T2DM and compared them with high and low OSA risk, its association, and correlation with the quality of sleep. Methods. This is a prospective cross-sectional study among uncontrolled T2DM. The questionnaires were Berlin Questionnaire (screen OSA-HR) and Epworth Sleepiness Score (level of sleepiness). Clinicodemographic profile and significant laboratory data were obtained. Descriptive statistics utilized. Chi-square test was used to compare categorical variables between patients with high vs low OSA risk and to determine if an association exists between OSA-HR and sleep quality. Results. A total of 240 participants, 88 males and 151 females, were included in the study. The overall prevalence of OSA-HR among patients with uncontrolled type 2DM is 58.33%. The majority of the OSA–HR patients (105/140) was 46 years old and above. There is a significant association of tonsillar grade, Mallampati score, BMI, HbA1c, hypercholesterolonemia, and Epworth sleepiness on OSA High risk. There is also a substantial association with age, BMI, Mallampati score, tonsillar grade, hypertension, asthma, HbA1c, and hypercholesterelonemia on the level of sleepiness of OSA-HR. Conclusion. There is a high prevalence of high OSA-risk among patients with uncontrolled DM. Factors associated with high OSA-risk among uncontrolled diabetes mellitus include HbA1c, dyslipidemia, BMI, Mallampati score, tonsillar grade, and Epworth score.
Sleep Apnea, Obstructive ; Diabetes Mellitus, Type 2

Objectives. We determined the prevalence of patients at risk for obstructive sleep apnea (OSA) with uncontrolled type 2 diabetes mellitus (T2DM) at the out-patient department (OPD) of the University of the Philippines-Philippine General Hospital (UP-PGH) from December 1, 2018 - February 28, 2019. We described the demographic characteristics of patients with uncontrolled T2DM and compared them with high and low OSA risk, its association, and correlation with the quality of sleep. Methods. This is a prospective cross-sectional study among uncontrolled T2DM. The questionnaires were Berlin Questionnaire (screen OSA-HR) and Epworth Sleepiness Score (level of sleepiness). Clinicodemographic profile and significant laboratory data were obtained. Descriptive statistics utilized. Chi-square test was used to compare categorical variables between patients with high vs low OSA risk and to determine if an association exists between OSA-HR and sleep quality. Results. A total of 240 participants, 88 males and 151 females, were included in the study. The overall prevalence of OSA-HR among patients with uncontrolled type 2DM is 58.33%. The majority of the OSA–HR patients (105 /140) was 46 years old and above. There is a significant association of tonsillar grade, Mallampati score, BMI, HbA1c, hypercholesterolonemia, and Epworth sleepiness on OSA High risk. There is also a substantial association with age, BMI, Mallampati score, tonsillar grade, hypertension, asthma, HbA1c, and hypercholesterelonemia on the level of sleepiness of OSA-HR. Conclusion. There is a high prevalence of high OSA-risk among patients with uncontrolled DM. Factors associated with high OSA-risk among uncontrolled diabetes mellitus include HbA1c, dyslipidemia, BMI, Mallampati score, tonsillar grade, and Epworth score.
Sleep Apnea, Obstructive ; Diabetes Mellitus, Type 2