Sleep deprivation and its consequences on house officers and postgraduate trainees.
ABSTRACT To determine sleep deprivation and its consequences on doctors in tertiary care hospitals.
The cross-sectional study was conducted from February to May 2012 and comprised house officers and postgraduate trainees at 4 public and 1 private tertiary care hospitals in Karachi. The subjects were posted in wards, out-patient departments and emergencies. A proforma was designed with questions about duration of duty hours, sleep deprivation and its effects on quality of performance, and presence of anxiety, depression, medical errors, frequent cold and infections, accidents, weight changes, and insomnia. Duration of 1 hour was given to fill the proforma. SPSS 20 was used for data analysis.
The study comprised 364 subjects: 187 (51.37%) house officers and 177 (48.62%) postgraduate trainees. There were 274 (75.27%) females and 90 (24.72%) males. Of those who admitted to being sleep deprived (287; 78.84%), also complained of generalised weakness and poor performance (n = 115; 40%), anxiety (n = 110; 38%), frequent cold and infections (n = 107; 37%), personality changes (n = 93; 32%), depression (n = 86; 30%), risk of accidents (n = 68; 23.7%), medical errors (n = 58; 20%) and insomnia (n = 52; 18%).
Having to spend 80-90 hours per week in hospitals causes sleep deprivation and negative work performance among doctors. Also, there is anxiety, depression and risk of accidents in their personal lives.
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ABSTRACT: Analysis of brain recurrence (ABR) is a novel computational method that uses two variables for sleep depth and two for sleep fragmentation to quantify temporal changes in non-random brain electrical activity. We postulated that ABR of the sleep-staged EEG could identify an EEG signature specific for the presence of mental health symptoms. Using the Mental Health Inventory Questionnaire (MHI-5) as ground truth, psychological distress was assessed in a study cohort obtained from the Sleep Heart Health Study. Subjects with MHI-5 <50 (N=34) were matched for sex, BMI, age, and race with 34 subjects who had MHI-5 scores >50. Sixteen ABR markers derived from the EEG were analyzed using linear discriminant analysis to identify marker combinations that reliably classified individual subjects. A biomarker function computed from 12 of the markers accurately classified the subjects based on their MHI-5 scores (AUROC=82%). Use of additional markers did not improve classification accuracy. Subgroup analysis (20 highest and 20 lowest MHI-5 scores) improved classification accuracy (AUROC=89%). Biomarker values for individual subjects were significantly correlated with MHI-5 score (r=0.36, 0.54 for N=68, 40, respectively). ABR of EEGs obtained during sleep successfully classified subjects with regard to the severity of mental health symptoms, indicating that mood systems were reflected in brain electrical activity.Psychiatry Research Neuroimaging 10/2014; · 2.83 Impact Factor