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.

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.

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.

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