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Fulltext Effects of sleep changes on pain-related health outcomes in the general population: A systematic review of longitudinal studies with exploratory meta-analysis

Afolalu EF, Ramlee F, Tang NKY

Sleep Med Rev, 2018 06;39:82-97.
PMID: 29056414 DOI: 10.1016/j.smrv.2017.08.001

Emerging longitudinal research has highlighted poor sleep as a risk factor of a range of adverse health outcomes, including disabling pain conditions. In establishing the causal role of sleep in pain, it remains to be clarified whether sleep deterioration over time is a driver of pain and whether sleep improvement can mitigate pain-related outcomes. A systematic literature search was performed using PubMed MEDLINE, Ovid EMBASE, and Proquest PsycINFO, to identify 16 longitudinal studies involving 61,000 participants. The studies evaluated the effect of sleep changes (simulating sleep deterioration, sleep stability, and sleep improvement) on subsequent pain-related outcomes in the general population. A decline in sleep quality and sleep quantity was associated with a two- to three-fold increase in risk of developing a pain condition, small elevations in levels of inflammatory markers, and a decline in self-reported physical health status. An exploratory meta-analysis further revealed that deterioration in sleep was associated with worse self-reported physical functioning (medium effect size), whilst improvement in sleep was associated with better physical functioning (small effect size). The review consolidates evidence that changes in sleep are prospectively associated with pain-related outcomes and highlights the need for further longitudinal investigations on the long-term impact of sleep improvements.

Matched MeSH terms: Sleep Initiation and Maintenance Disorders*; Sleep*
Fulltext SleepEEGNet: Automated sleep stage scoring with sequence to sequence deep learning approach

Mousavi S, Afghah F, Acharya UR

PLoS One, 2019;14(5):e0216456.
PMID: 31063501 DOI: 10.1371/journal.pone.0216456

Electroencephalogram (EEG) is a common base signal used to monitor brain activities and diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep experts and is limited by inter-rater reliability. In this paper, we propose an automatic sleep stage annotation method called SleepEEGNet using a single-channel EEG signal. The SleepEEGNet is composed of deep convolutional neural networks (CNNs) to extract time-invariant features, frequency information, and a sequence to sequence model to capture the complex and long short-term context dependencies between sleep epochs and scores. In addition, to reduce the effect of the class imbalance problem presented in the available sleep datasets, we applied novel loss functions to have an equal misclassified error for each sleep stage while training the network. We evaluated the performance of the proposed method on different single-EEG channels (i.e., Fpz-Cz and Pz-Oz EEG channels) from the Physionet Sleep-EDF datasets published in 2013 and 2018. The evaluation results demonstrate that the proposed method achieved the best annotation performance compared to current literature, with an overall accuracy of 84.26%, a macro F1-score of 79.66% and κ = 0.79. Our developed model can be applied to other sleep EEG signals and aid the sleep specialists to arrive at an accurate diagnosis. The source code is available at https://github.com/SajadMo/SleepEEGNet.

Matched MeSH terms: Sleep Wake Disorders/physiopathology*; Sleep Stages*
Prevalence of sleep disturbance in patients with ankylosing spondylitis: a systematic review and meta-analysis

Salari N, Sadeghi N, Hosseinian-Far A, Hasheminezhad R, Khazaie H, Shohaimi S, et al.

Adv Rheumatol, 2023 Jul 19;63(1):33.
PMID: 37468951 DOI: 10.1186/s42358-023-00315-1

BACKGROUND: Ankylosing Spondylitis (AS) patients face several challenges due to the nature of the disease and its physical and psychological complications. Sleep disorders are among the most important concerns. Sleep disorders can aggravate the signs and symptoms of the disease and ultimately reduce the quality of patients' lives. This study uses a systematic review and meta-analysis to pool the reported prevalence of sleep disorders among AS patients.
METHODS: To find related studies, the WoS, PubMed, ScienceDirect, Scopus, Embase, and Google Scholar databases were systematically searched without a lower time limit. Heterogeneity among the identified studies was checked using the I2 index, and the Begg and Mazumdar correlation test examined the existence of published bias. Comprehensive Meta-Analysis (v.2) software was adopted to analyze the data.
RESULTS: In the review of 18 studies with a sample size of 5,840, the overall pooled prevalence of sleep disorders among AS patients based on the random effects method was found to be 53% (95% CI: 44.9-61). The highest and lowest prevalence was in Egypt at 90% and Australia at 19.2%, respectively. Our meta-regression results show that with the increase in 'sample size' and 'year of publication', the overall prevalence of sleep disorders in patients with AS decreases (p sleep disorders among AS patients. Thus, health policymakers and healthcare providers must focus on timely diagnosis and effective educational and therapeutic interventions for the prevention and proper treatment of sleep disorders in this population of patients.

Matched MeSH terms: Sleep
Sleep quality in diabetic patients depends on numerous influencing factors

Finsterer J

Med J Malaysia, 2024 Jan;79(1):113.
PMID: 38287767

No abstract available.

Matched MeSH terms: Sleep
Fulltext Detecting driver drowsiness based on sensors: a review

Sahayadhas A, Sundaraj K, Murugappan M

Sensors (Basel), 2012 Dec 07;12(12):16937-53.
PMID: 23223151 DOI: 10.3390/s121216937

In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Researchers have attempted to determine driver drowsiness using the following measures: (1) vehicle-based measures; (2) behavioral measures and (3) physiological measures. A detailed review on these measures will provide insight on the present systems, issues associated with them and the enhancements that need to be done to make a robust system. In this paper, we review these three measures as to the sensors used and discuss the advantages and limitations of each. The various ways through which drowsiness has been experimentally manipulated is also discussed. We conclude that by designing a hybrid drowsiness detection system that combines non-intrusive physiological measures with other measures one would accurately determine the drowsiness level of a driver. A number of road accidents might then be avoided if an alert is sent to a driver that is deemed drowsy.

Matched MeSH terms: Sleep Stages/physiology*
Fulltext Sleep quality among pre-clinical medical students in Universiti Putra Malaysia and Universiti Malaya, Malaysia

Ngu ST, Masalamany K, Abd Manan N, Adam SK

Education in Medicine Journal, 2017;9(3):23-31.
MyJurnal DOI: 10.21315/eimj2017.9.3.3

Introduction: Poor sleep quality among university students has become an important issue to be concerned as it can hugely influence the students especially on their academic performance. However, there are inadequate studies published on the sleep quality of medical students in Malaysia.
Objective: This study aimed at determining the sleep quality of pre-clinical medical students in Universiti Putra Malaysia (UPM) and Universiti Malaya (UM). Methods: This is a cross-sectional study that used self-administered questionnaire to collect data from the pre-clinical medical students
of UPM and UM. Sleep quality of the students was measured using Pittsburgh Sleep Quality Index (PSQI) questionnaire. All data were analysed by SPSS version 21.
Results: Findings revealed that 63.9% respondents with poor sleep quality (PSQI score: more than 5). The prevalence of poor sleepers
in UM (67%) was slightly higher compared to UPM (60.9%). However, the comparison of PSQI score showed no significant difference between UPM and UM respondents (p = 0.082). Meanwhile, the average sleep duration per night among respondents was 5 hours 39 minutes (± 1.21 hrs), whereas
only 6.1% students practiced recommended sleep value per night (> 7 hrs). Significant association was found between caffeine intake and sleep quality. Besides, this present study showed no association between sleep quality with gender and year of study.
Conclusion: Majority of the pre-clinical students in UPM and UM had poor sleep quality and short sleep duration. Only a small number of students practiced recommended sleep value per night.

Matched MeSH terms: Sleep*
Fulltext Anti-citrullinated cyclic peptide antibody and functional disability are associated with poor sleep quality in rheumatoid arthritis

Rajalingam S, Sakthiswary R, Hussein H

Arch Rheumatol, 2017 Mar;32(1):15-20.
PMID: 30375543 DOI: 10.5606/ArchRheumatol.2017.5960

Objectives: This study aims to determine the predictors of poor sleep quality in rheumatoid arthritis (RA).

Patients and methods: This was a monocentric, cross sectional, case-control study which was conducted at the Putrajaya Hospital, Malaysia. We recruited 46 patients with RA (3 males; 43 females; mean age 48.15±14.96) and 46 age and sex-matched healthy controls (3 males; 43 females; mean age 47.11±12.22). RA patients were assessed for their disease activity based on disease activity score in 28 joints, disease damage based on radiographic erosions, and functional status based on Health Assessment Questionnaire Disability Index. The Pittsburgh Sleep Quality Index (PSQI) scores were determined by interviewing all the subjects. Subjects with RA were further subdivided based on their PSQI scores as "good sleepers" with PSQI scores of <5 and "poor sleepers" with PSQI scores of ≥5.

Results: The percentage of poor sleepers was significantly higher among RA patients (47.83% versus 9.57%). Median scores of 5 out of 7 components of the PSQI were higher among RA patients compared to controls. Among poor sleepers with RA, a significantly higher proportion tested positive for anti-citrullinated cyclic peptide autoantibodies (p=0.037). Besides, poor sleepers had significantly higher median Health Assessment Questionnaire Disability Index (p=0.017) than good sleepers. However, both Health Assessment Questionnaire Disability Index (p=0.968) and anti-citrullinated cyclic peptide (p=0.431) were insignificant when entered in the equation of a logistic regression model.

Conclusion: The findings of this study demonstrate a link between functional disability, anti-citrullinated cyclic peptide antibodies, and sleep quality in RA.

Matched MeSH terms: Sleep*
Fulltext A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability

Awais M, Badruddin N, Drieberg M

Sensors (Basel), 2017 Aug 31;17(9).
PMID: 28858220 DOI: 10.3390/s17091991

Driver drowsiness is a major cause of fatal accidents, injury, and property damage, and has become an area of substantial research attention in recent years. The present study proposes a method to detect drowsiness in drivers which integrates features of electrocardiography (ECG) and electroencephalography (EEG) to improve detection performance. The study measures differences between the alert and drowsy states from physiological data collected from 22 healthy subjects in a driving simulator-based study. A monotonous driving environment is used to induce drowsiness in the participants. Various time and frequency domain feature were extracted from EEG including time domain statistical descriptors, complexity measures and power spectral measures. Features extracted from the ECG signal included heart rate (HR) and heart rate variability (HRV), including low frequency (LF), high frequency (HF) and LF/HF ratio. Furthermore, subjective sleepiness scale is also assessed to study its relationship with drowsiness. We used paired t-tests to select only statistically significant features (p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features of both modalities (EEG and ECG) are then combined to investigate the improvement in performance using support vector machine (SVM) classifier. The other main contribution of this paper is the study on channel reduction and its impact to the performance of detection. The proposed method demonstrated that combining EEG and ECG has improved the system's performance in discriminating between alert and drowsy states, instead of using them alone. Our channel reduction analysis revealed that an acceptable level of accuracy (80%) could be achieved by combining just two electrodes (one EEG and one ECG), indicating the feasibility of a system with improved wearability compared with existing systems involving many electrodes. Overall, our results demonstrate that the proposed method can be a viable solution for a practical driver drowsiness system that is both accurate and comfortable to wear.

Matched MeSH terms: Sleep Stages*
Good News: Dentists are Competent in Diagnosing Undiagnosed Sleep Apnea

Chidambaram R

J Coll Physicians Surg Pak, 2017 May;27(5):321.
PMID: 28599700 DOI: 2624
Matched MeSH terms: Sleep Apnea Syndromes/diagnosis*
Fulltext Daytime sleepiness and sleep quality among Malaysian medical students

Zailinawati AH, Teng CL, Chung YC, Teow TL, Lee PN, Jagmohni KS

Med J Malaysia, 2009 Jun;64(2):108-10.
PMID: 20058567 MyJurnal

Poor sleep quality and daytime somnolence is reported to be associated with cardiovascular events, road traffic accident, poor academic performance and psychological distress. Some studies documented that it is prevalent in most populations but its frequency among medical students has not been documented in Malaysia. This is a self-administered questionnaire survey of medical students from International Medical University, Malaysia. Daytime sleepiness of medical students was assessed using Epworth Sleepiness Scale (ESS). Student scoring ESS > 11 was regarded as having excessive daytime sleepiness. Psychological distress was measured using 12-item General Health Questionnaire (GHQ-12). A total of 799 medical students participated in this survey (response rate 69.5%). Daytime sleepiness occurred in 35.5%, psychological distress was present in 41.8% and 16.1% reported bad sleep quality. Daytime sleepiness was significantly more common among the clinical students, those with self-reported bad sleep quality and psychological distress; but unrelated to the number of hours sleep at night. We have documented high prevalence of daytime sleepiness, poor sleep quality and psychological distress. Higher frequency among clinical students and the significant relationship with psychological distress suggest possible link to the stressful clinical training.

Matched MeSH terms: Sleep*; Sleep Deprivation/epidemiology; Sleep Wake Disorders/epidemiology*
Fulltext Relations of Bedtime Mobile Phone Use to Cognitive Functioning, Academic Performance, and Sleep Quality in Undergraduate Students

Ragupathi D, Ibrahim N, Tan KA, Andrew BN

Int J Environ Res Public Health, 2020 09 29;17(19).
PMID: 33003445 DOI: 10.3390/ijerph17197131

The present cross-sectional study examined the relations of bedtime mobile phone use to cognitive functioning, academic performance, and sleep quality in a sample of undergraduate students. Three hundred eighty-five undergraduate students completed a self-administered questionnaire containing sociodemographic variables, bedtime mobile phone use, the Pittsburgh Sleep Quality Index, and the Cambridge Neuropsychological Test Automated Battery (attention and verbal memory). At bivariate level, increased scores in bedtime mobile phone use were significantly correlated with decreased scores in academic performance and sleep quality. Our multivariate findings show that increased scores in bedtime mobile phone use uniquely predicted decreased scores in academic performance and sleep quality, while controlling for gender, age, and ethnicity. Further untangling the relations of bedtime mobile phone use to academic performance and sleep quality may prove complex. Future studies with longitudinal data are needed to examine the bidirectional effect that bedtime mobile phone use may have on academic performance and sleep quality.

Matched MeSH terms: Sleep/physiology*; Sleep Hygiene
Fulltext Sleep belief factors among Diploma students in UiTM Sabah

Nowyannie Willie D. Tamsin, Norah Tuah, Mazalan Sarahintu, Herniza Roxanne Marcus

Borneo Akademika, 2019;3(1):20-29.
MyJurnal

University students are known to have different sleeping schedules. Students’ sleep difficulties will affect their health and their performances in studies. Sleep hygiene is a collection of healthy sleep habits that can improve one’s ability to fall asleep and stay asleep. It is considered to be imperative to treat sleep disturbance especially among university students. The aim of this study is to examine the sleep beliefs among the students of UiTM Sabah based on gender and academic performance. This study was conducted on Diploma students between March and July 2018. The respondents were randomly selected from Diploma students of all faculties in UiTM Sabah: Accounting, Business Management, Public Administration, Science, Planting Industry Management, Hotel Management, and Tourism Management. This paper is based on the Sleep Belief Scale questionnaire to assess the sleep hygiene awareness. Questionnaires were distributed using online survey. Findings of this study were analyzed using SPSS statistical software. The result of findings showed that the Sleep Incompatible Behaviours (drinking coffee, taking sleep medication, smoking before sleep) is the highest contributor of the students’ sleep hygiene and therefore it affects the sleep quality. While the Sleep Wake Cycle Behaviours (going to bed & waking up always at the same hour, going to bed two hours earlier than the habitual hour) and Thoughts and Attitude to Sleep (over thinking before sleep, trying to fall asleep without having a sleep sensation)also contributed to the sleep hygiene of the students but not as high as the Sleep Incompatible Behaviours. Based on the results of the findings, the counseling department of UiTM Sabah may organise an education program to create awareness among students about the intervention and prevention strategies as well as the incorrect beliefs about sleep.

Matched MeSH terms: Sleep; Sleep Wake Disorders; Sleep Hygiene
Modified Munich chronotype questionnaire for application to short-interval split sleep of non-shift workers

Mazri FH, Manaf ZA, Shahar S, Mat Ludin AF, Karim NA, Ban AY, et al.

Chronobiol Int, 2021 05;38(5):659-665.
PMID: 33733959 DOI: 10.1080/07420528.2021.1887209

The Munich Chronotype Questionnaire (MCTQ) has been widely validated among various types of populations. However, determination of chronotype among individuals who have a split sleep pattern with short intervals between the first and second sleep bouts on free days has not yet been reported. This study aimed to validate the MCTQ modified for this purpose by assessing the actual sleep-wake timing against the Morningness-Eveningness Questionnaire (MEQ). The modified calculation for the midpoint of sleep on free days (MSF) of the split sleep pattern considers the second sleep bout as the total sleep duration on free days. We recruited 161 participants (mean age: 38.7 ± 7.8 years; 73% females, 29% with split sleep pattern) were recruited to administer the modified version of the MCTQ and MEQ. All of the MCTQ original parameters: midpoint of sleep on work days (MSW, r = -0.575), midpoint of sleep on free days (MSF, r = -0.568), and midpoint of sleep on free days corrected for sleep debt (MSFsc,r = -0.566) were significantly correlated with MEQ. The MEQ was further tested against MSF in four conditions of the split sleep pattern. The MSF modified for split sleep within 60 minutes after the first awakening showed highest correlation (r = -0.576) against MEQ score. The results demonstrate the modified version of MCTQ is valid to determine the chronotype in participants who practice consolidated and split sleep patterns.

Matched MeSH terms: Sleep*; Sleep Deprivation
Psychological state during pregnancy is associated with sleep quality: preliminary findings from MY-CARE cohort study

Teoh AN, Kaur S, Mohd Shukri NH, Shafie SR, Ahmad Bustami N, Takahashi M, et al.

Chronobiol Int, 2021 07;38(7):959-970.
PMID: 33779445 DOI: 10.1080/07420528.2021.1902338

Psychological distress during pregnancy may increase the risk of adverse maternal and infant outcomes. Past studies have demonstrated the association between circadian disturbances with psychological health. However, the roles of chronotype and social jetlag on psychological state during pregnancy are yet to be identified. We aimed to examine the psychological state in pregnant women and its relations to chronotype, social jetlag (SJL), sleep quality and cortisol rhythm. The current study included a subsample of participants from an ongoing cohort study. A total of 179 primigravidas (mean age 28.4 ± 4.0 years) were recruited. Chronotype and sleep quality during the second trimester were assessed using the Morning-Eveningness Questionnaire (MEQ) and Pittsburgh Sleep Quality Index (PSQI), respectively. SJL was calculated based on the difference between mid-sleep on workdays and free days. Psychological state of participants was evaluated using the Depression, Anxiety, and Stress Scale-21 (DASS-21). Subsamples (n = 70) provided salivary samples at 5 time points over a 24 h period during the second trimester for cortisol assay. A higher proportion of pregnant women experienced moderate to severe anxiety symptoms (n = 77, 43.0%), followed by depressive (n = 17, 9.5%) and stress (n = 14, 7.8%) symptoms. No association was observed between chronotype and psychological distress during pregnancy. There was no significant difference in cortisol rhythms in relation to psychological distress. SJL and sleep quality were significantly associated with stress symptoms among pregnant women in the second trimester. Poor sleep quality, particularly daytime dysfunction (β = 0.37, p = .006) and sleep disturbances (β = 0.23, p = .047), were significantly associated with psychological distress (depressive, anxiety and stress symptoms) during the second trimester. The findings suggest that sleep is a potential modifiable lifestyle factor that can be targeted to improve psychological health among pregnant women.

Matched MeSH terms: Sleep; Sleep Wake Disorders*
Fulltext Correlates between insomnia, psychological distress and daytime sleepiness of malaysian adults with symptoms of insomnia

Yasmin Othman Mydin, Norzarina Mohd Zaharim, Syed Hassan Ahmad Almashor

ASEAN Journal of Psychiatry, 2012;13(2):0-0.
MyJurnal

Objective: The objective of this study is to identify the correlation between psychological factors and insomnia and the impact of insomnia on daytime sleepiness. Methods and Results: The participants were recruited through convenient sampling and consist of 173 working adults in Georgetown, Penang, aged 20 to 60 years. Participants completed the General Health Questionnaire (GHQ), Athens Insomnia Scale (AIS) and Epworth Sleepiness Scale (ESS). The results revealed that the prevalent of insomnia was 34.7%. There was a positive correlation between psychological distress and insomnia r = .481, p < .001 and also a positive correlation between insomnia and daytime sleepiness r = .334, p < .001. Conclusion: It is concluded that psychological distress typically causes sleep difficulties, and sleep deprivation leads to daytime sleepiness.

Matched MeSH terms: Sleep Initiation and Maintenance Disorders; Sleep Deprivation; Sleep Stages
Fulltext A feasibility study: Use of actigraph to monitor and follow-up sleep/wake patterns in individuals attending community pharmacy with sleeping disorders

Noor ZM, Smith AJ, Smith SS, Nissen LM

J Pharm Bioallied Sci, 2016 Jul-Sep;8(3):173-80.
PMID: 27413344 DOI: 10.4103/0975-7406.171739

INTRODUCTION: Community pharmacists are in a suitable position to give advice and provide appropriate services related to sleep disorders to individuals who are unable to easily access sleep clinics. An intervention with proper objective measure can be used by the pharmacist to assist in consultation.
OBJECTIVES: The study objectives are to evaluate: (1) The effectiveness of a community pharmacy-based intervention in managing sleep disorders and (2) the role of actigraph as an objective measure to monitor and follow-up individuals with sleeping disorders.
METHODS AND INSTRUMENTS: The intervention care group (ICG) completed questionnaires to assess sleep scale scores (Epworth Sleepiness Scale [ESS] and Insomnia Severity Index [ISI]), wore a wrist actigraph, and completed a sleep diary. Sleep parameters (sleep efficiency in percentage [SE%], total sleep time, sleep onset latency, and number of nocturnal awakenings) from actigraphy sleep report were used for consultation and to validate sleep diary. The usual care group (UCG) completed similar questionnaires but received standard care.
RESULTS: Pre- and post-mean scores for sleep scales and sleep parameters were compared between and within groups. A significant difference was observed when comparing pre- and post-mean scores for ISI in the ICG, but not for ESS. For SE%, an increase was found in the number of subjects rated as "good sleepers" at post-assessment in the ICG.
CONCLUSIONS: ISI scores offer insights into the development of a community pharmacy-based intervention for sleeping disorders, particularly in those with symptoms of insomnia. It also demonstrates that actigraph could provide objective sleep/wake data to assist community pharmacists during the consultation.
KEYWORDS:
Actigraph; community pharmacy; intervention; pharmacist; sleeping disorders

Matched MeSH terms: Sleep Initiation and Maintenance Disorders; Sleep; Sleep Wake Disorders
Sleep problems among children with neurological disorders

Khoo, T.B., Muhammad Ismail, H.I., Abdul Manaf, A.M.

Malaysian Journal of Paediatrics and Child Health, 2000;12(1):22-28.
MyJurnal

A study was conducted to evaluate the extent of sleep problems among children aged between 6 to 15 years old who were followed up at Penang Hospital Paediatric Clinic for various neurological disorders and compared to those with other paediatric illnesses and their healthy siblings. A parental questionnaire was used to assess sleep problems in 48 children with neurological disorders and compared to 46 of their healthy siblings, 59 children with non-neurological paediatric illnesses and 67 of their healthy siblings. Sleep problems were clustered into five subscales: bedtime difficulties, parental involvement at time of sleep, sleep fragmentation, parasomnias and daytime drowsiness. Children with neurological disorders had significantly more sleep problems than did their siblings, those with non-neurological paediatric illnesses and their healthy siblings (p < 0.001). This was particularly so in areas of bedtime difficulties (p>0.001), the amount of parental involvement (p

Study site: Penang Hospital Paediatric Clinic

Matched MeSH terms: Sleep; Sleep Deprivation; Sleep Stages
Incidence of Prosthetic Complications associated with Implant-borne Prosthesis in a Sleep Disorder Center

Suneel VB, Kotian S, Jujare RH, Shetty AK, Nidhi S, Grover S

J Contemp Dent Pract, 2017 Sep 01;18(9):821-825.
PMID: 28874648

BACKGROUND: Obstructive sleep apnea (OSA) is one of the common prevalent conditions present worldwide. The process of abnormal habits related to clenching and grinding of teeth is referred to as bruxism and is characterized under the heading of parafunctional activity of the masticatory system. Osseointegrated dental implants represent advancements in the field of odontology. Despite its high success rate, failure and complications are often associated with dental implant treatment due to a number of factors. Hence, we aimed for the present study to assess the incidence of prosthetic complications in patients rehabilitated with implant-borne prosthesis in a sleep disorder unit.
MATERIALS AND METHODS: The present study included the assessment of all the patients who underwent prosthetic rehabilitation by dental implants. An experienced registered prosthodontist was given duty for examination of all the cases from the record file data. Prosthetic complications in the patients were identified using photographs, radiographs, and all other relevant data of the patients obtained from the record files. All types of complications and other factors were recorded separately and analyzed.
RESULTS: While correlating the prosthetic complications in OSA patients grouped based on number of dental implants, nonsignificant results were obtained. Significant correlation was observed while comparing the prosthetic complications divided based on type of prosthesis. Fracture of the porcelain was observed in four and eight cases respectively, of screwed and cemented dental implant cases.
CONCLUSION: Some amount of significant correlation existed between the incidences of prosthetic complications and OSA.
CLINICAL SIGNIFICANCE: Proper history of the patients undergoing dental implant procedures should be taken to avoid failure.

Matched MeSH terms: Sleep Apnea, Obstructive/etiology; Sleep Apnea, Obstructive/epidemiology*
The prevalence and predictors of poor sleep quality and excessive daytime sleepiness in epilepsy: A single tertiary centre experience in Malaysia

Chong CS, Tan JK, Ng BH, Lin ABY, Khoo CS, Rajah R, et al.

J Clin Neurosci, 2023 Dec;118:132-142.
PMID: 37935067 DOI: 10.1016/j.jocn.2023.10.012

BACKGROUND AND OBJECTIVE: People with epilepsy frequently encounter sleep disruptions that can stem from a variety of complex factors. Epilepsy-related sleep disturbance can lead to reduced quality of life and excessive daytime hypersomnolence. Identification of sleep disturbances may help in the overall management of epilepsy patients. This study was conducted to determine the prevalence and predictors of poor sleep quality and daytime sleepiness in epilepsy.
METHODS: A cross-sectional study on 284 epilepsy patients was performed in a local tertiary centre. The demographic and clinical epilepsy data were collected. The Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaires were utilised to determine the quality of life and daytime hypersomnolence of epilepsy patients, respectively.
RESULTS: Poor sleep quality was reported in 78 (27.5%) patients while daytime hypersomnolence was present in 17 (6%) patients. The predictors of poor sleep quality include structural causes (OR = 2.749; 95% CI: 1.436, 5.264, p = 0.002), generalised seizures (OR = 1.959, 95% CI: 1.04, 3.689, p = 0.037), and antiseizure medications such as Carbamazepine (OR = 2.34; 95% CI: 1.095, 5.001, p = 0.028) and Topiramate (OR 2.487; 95% CI: 1.028, 6.014, p = 0.043). Females are 3.797 times more likely score higher in ESS assessment (OR 3.797; 95% CI: 1.064, 13.555 p = 0.04).
DISCUSSION: Sleep disturbances frequently coexist with epilepsy. Patients should be actively evaluated using the PSQI and ESS questionnaires. It is imperative to identify the key factors that lead to reduced sleep quality and heightened daytime sleepiness in patients with epilepsy, as this is essential to properly manage their condition.

Matched MeSH terms: Sleep Initiation and Maintenance Disorders*; Sleep
Uncovering the sleep disorders among young doctors

Yasin R, Muntham D, Chirakalwasan N

Sleep Breath, 2016 Dec;20(4):1137-1144.
PMID: 27535070 DOI: 10.1007/s11325-016-1380-6

PURPOSE: Sleepiness and tiredness are common complaints among young doctors. Sleep deprivation is believed to be the main culprit. However, we believe that there may be other sleep disorders which may contribute to these symptoms such as occult obstructive sleep apnea (OSA).
METHODS: A prospective cross-sectional study was performed among young doctors less than 40 years old, working at King Chulalongkorn Memorial Hospital, Bangkok, Thailand, and Hospital Kuala Lumpur, Kuala Lumpur, Malaysia, using questionnaires and home sleep apnea testing (Apnealink™Plus). The primary objective of this study was to evaluate the prevalence of OSA (apnea-hypopnea index (AHI) ≥5). The secondary objectives were to evaluate the prevalence of obstructive sleep apnea syndrome (OSAS) defined by AHI ≥5 + excessive daytime sleepiness (EDS), sleep deprivation (the difference of weekend (non-workdays) and weekday (workdays) wake-up time of at least 2 h), EDS (Epworth Sleepiness Scale score ≥10), tiredness, and perception of inadequate sleep as well as to identify their predictors.
RESULTS: Total of 52 subjects completed the study. Mean age and mean body mass index (BMI) were 31.3 ± 4 and 23.3 ± 3.6, respectively. The prevalence of OSA and OSAS were 40.4 and 5.8 %, respectively. One third of OSA subjects were at least moderate OSA. Prevalence of sleep deprivation, EDS, tiredness, and perception of inadequate sleep were 44.2, 15.4, 65.4, and 61.5 %, respectively. History of snoring, being male, and perception of inadequate sleep were significant predictors for OSA with the odds ratio of 34.5 (p = 0.016, 95 % CI = 1.92-619.15), 18.8 (p = 0.001, 95 % CI = 3.10-113.41), and 7.4 (p = 0.037, 95 % CI = 1.13-48.30), respectively. Only observed apnea was a significant predictor for OSAS with odds ratio of 30.7 (p = 0.012, 95 % CI = 2.12-442.6). Number of naps per week was a significant predictor for EDS with the odds ratio of 1.78 (p = 0.007, 95 % CI = 1.17-2.71). OSA and total number of call days per month were significant predictors for tiredness with the odds ratio of 4.8 (p = 0.036, 95 % CI = 1.11-20.72) and 1.3 (p = 0.050, 95 % CI = 1.0004-1.61), respectively. OSA was the only significant predictor for perception of inadequate sleep with the odd ratios of 4.5 (p = 0.022, 95 % CI = 1.24-16.59).
CONCLUSIONS: Our results demonstrated relatively high prevalence of OSA and OSAS among young doctors. Snoring, being male, and perception of inadequate sleep were significant predictors for OSA. Observed apnea was a significant predictor for OSAS. OSA was a significant predictor for tiredness and perception of inadequate sleep.

Matched MeSH terms: Sleep Deprivation/diagnosis; Sleep Deprivation/epidemiology; Sleep Apnea, Obstructive/diagnosis*; Sleep Apnea, Obstructive/epidemiology*

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