Taiwanese Journal of Psychiatry

: 2021  |  Volume : 35  |  Issue : 2  |  Page : 76--81

A pilot study of antidepressant therapy on sleep architecture in patients with depression in Congo

Harpreet Singh Dhillon1, Shibu Sasidharan2,  
1 Department of Psychiatry, Pain and Critical Care, Level III Hospital, Street-RVA Land, Goma, Democratic Republic of Congo
2 Department of Anaesthesiology, Pain and Critical Care, Level III Hospital; United Nations Organization Stabilization Mission, Street-RVA Land, Goma, Democratic Republic of Congo

Correspondence Address:
M.D., D.N.B Shibu Sasidharan
Goma 400140
Democratic Republic of Congo


Background: A pilot prospective cohort study was conducted to study the sleep architecture and correlated perceived sleep disturbances in depressed Congolese patients with objective changes in sleep architecture using polysomnography (PSG) before and after antidepressant therapy. Methods: Patients were recruited into the study after applying strict inclusion and exclusion criterion to rule out other comorbidities which could influence sleep. A diagnosis of depressive episode was made based on the International Classification of Diseases-10 Edition DCR. Patients were evaluated using Beck Depressive inventory (BDI) and (Hamilton Depression Rating Scale (HAM-D) insomnia subscale on day 1 of admission. Patients also received sleep study using polysomnography on day 3 of the hospitalization. Patients were started on antidepressant treatment after polysomnography. Patients received an eight-week adequate trial of antidepressants, and BDI score being lower than 9 was considered as being remitted from depression. Polysomnography was repeated after that the patients achieved remission. Statistical analysis was done using Kruskal–Wallis test and Pearson's correlation coefficient. Results: The study results showed that significantly improved polysomnographic findings existed in total sleep time (p < 0.001), sleep efficiency (p < 0.001), wake after sleep onset (p < 0.001), and percentage wake time (p < 0.001) after taking antidepressants. HAM-D insomnia subscale was correlated with total sleep time (p < 0.001), sleep efficiency (p < 0.001), wake after sleep onset (p < 0.001), total wake time (p < 0.001), and N2 stage percentage (p < 0.001). Conclusion: Antidepressant treatment effectively improved sleep architecture in depressive disorder. HAM-D insomnia subscale was correlated with objective findings of total sleep time, sleep efficiency, wake after sleep onset, as well as total wake time and duration of N2 stage of nonrapid eye movement (NREM).

How to cite this article:
Dhillon HS, Sasidharan S. A pilot study of antidepressant therapy on sleep architecture in patients with depression in Congo.Taiwan J Psychiatry 2021;35:76-81

How to cite this URL:
Dhillon HS, Sasidharan S. A pilot study of antidepressant therapy on sleep architecture in patients with depression in Congo. Taiwan J Psychiatry [serial online] 2021 [cited 2021 Dec 6 ];35:76-81
Available from: http://www.e-tjp.org/text.asp?2021/35/2/76/318961

Full Text


Sleep is a complex behavior which continues to be an evolutionary enigma. Every living being engages in some form of sleep or sleep-like behavior [1]. Carskadon and Dement defined sleep as “recurring, reversible neuro-behavioral state of relative perceptual disengagement from and unresponsiveness to the environment. Sleep is typically accompanied (in humans) by postural recumbence, behavioral quiescence, and closed eyes” [2]. Sleep repairs the physical body to improve and maintain general health, consolidate learning and memory, and recharge the psychological batteries to maintain emotional balance and well-being. Lack of sleep leads to various mental and physical illnesses including an increased risk of hypertension, diabetes, obesity, heart attack, stroke, and depression [3]. Sleep disturbances are widespread in patients with psychiatric disorders and hence have been integrated in the official diagnostic criteria for many psychiatric disorders, such as major depressive disorder, generalized anxiety disorder, posttraumatic stress disorder, and substance-related disorder [4]. Depression and sleep disturbances have a complex interaction with sleep disturbances presenting as the most commonly observed physical complaint [5] in depressed patients with roughly 80% complaining of insomnia and the remaining 20% of hypersomnia. Furthermore, the prevalence of depressive symptoms has been shown to be high in patients with insomnia [6].

Currently, rapid eye movement (REM) sleep disturbances are considered to be markers or “true” endophenotypes of depression [7]. Effective pharmacologic management of the mood disorders does not always dissipate insomnia. In fact, less than 20% of full responders to antidepressants are free of every symptom and nearly half the responders have persistent sleep disturbances and changes in sleep architecture.

A study in the general population revealed that 40% of subjects with insomnia presented themselves with a mental illness within six months versus 16% of those without insomnia [8]. Diagnosis of insomnia is based on the patient's perception of sleep quality, whereas diagnosis of many other sleep-related disorders [9],[10], e.g., restless legs syndrome, periodic limb movements, REM sleep behavior disorder, obstructive sleep apnea, and excessive daytime sleepiness, is defined with polysomnographic data. But these laboratory tests are highly demanding in cost, human resources, and other required logistics. Therefore, questionnaire and scales have been developed for screening patients.

This study was planned with the objective of testing the use of a quick, cost-effective, and practical psychometry tool (HAM-D insomnia subscale) as an alternative to expensive and time-consuming tests such as polysomnographic examination to assess and monitor the sleep disturbances in depressed patients, especially in outpatient settings in a resource-constraint country. The Democratic Republic of the Congo [Figure 1] is one of the worst hit countries in Africa with poverty, infectious diseases, war, and insufficient resources, and hence, no such study was conducted in the past, thus making it a pilot study on this population [12].{Figure 1}

In this pilot prospective study, we intended to study (a)whether any polysomnographic changes occurs in sleep architecture with antidepressant therapy in depressed patients. (b) whether HAM-D insomnia subscale correlates with the changes in sleep architecture in depressed patients.


Study patients

To be eligible for this, study patients included those (a) who were admitted in psychiatry ward within the age range of 18 to 50 years and (b) who met the ICD-10 diagnostic criteria for research of depressive episode. Excluded were those who (a) did not consent for the study; (b) had a history of sleep disorder before onset of depression; (c) had other psychiatric comorbidities; (d) being actively consuming alcohol, other psychoactive substances, and psychotropic medications; and (e) had other comorbid active medical and surgical illness.

The institutional review board of our hospital approved the study protocol (IRB protocol number = 211/14 and the date of approval = June 5, 2018) with the need to obtain the signed informed consent from the study participants.

Study procedures

The study was carried out at a tertiary care hospital in Congo, Africa. The subjects were evaluated using structured as well as unstructured clinical interview for the diagnosis of depressive disorder as per the ICD-10 Diagnostic Criteria for Research [13]. On day 1 of admission, psychiatric rating scales such as the Beck Depression Inventory-II (1996) (BDI) [14] and Hamilton Rating Scale for Depression (HAM-D) [15],[16],[17] were used. HAM-D is one of the longest standing, most widely used measures of depression severity in research and clinical practice with good sensitivity and specificity. It is a clinician-administered 21-item scale and takes 20–30 minutes to complete the test. Items 4, 5, and 6 refer specifically to sleep, inquiring about insomnia before sleep onset, disturbed sleep in the middle of the night, and trouble falling back sleep in the early morning, respectively [18]. Other items may be peripherally involved with sleep difficulties as they refer to fatigue, retardation, and somatic symptoms in general. Patients were kept drug free till the third day of admission. Polysomnography was conducted by the an anathesiologist on day 3 after allowing patients to get accustomed to ward environment. All patients who completed study were followed up till eight weeks and after treatment. Benzodiazepines (BZDs) in the lowest possible doses for shortest time were used for few patients. Polysomnography was done after achieving full remission as indicated by BDI score of 9 or less and HAM-D insomnia subscale score of 0.

The various sleep parameters [19] studied were as follows:

Total sleep time: The total time spent asleep during the sleep episode which is equal to the time in bed less the awake time.Sleep efficiency: The ratio of total sleep time to time in bed expressed as a percentage of time spent asleep during the recording period. Normal values are typically above 90% in young and above 85% in elderly patients.Sleep latency: Time from start of the recording (“lights out”) to the onset of sleep. Normal values are typically below 30 minutes in young and below 45 minutes in elderly patients.Wake after sleep onset: The total time scored as awake occurring after the sleep onset. Typically, wake after sleep onset should not exceed 30 minutes.N3 latency: Total duration in minutes and as percentage relative to total sleep time of sleep stage N3. The amount of stage N3 decreases with older age; normal values are around 10% for elderly and 20–25% for young subjects.REM%: Total duration in minutes and as percentage relative to total sleep time of sleep stage REM. Normal values are 20%–25%.REM latency: The number of minutes from the onset of sleep to the onset of the first REM sleep period. Reduced values are typically below 65 min in young and 50 min in elderly patients.

Statistical analysis

Considering 90% prevalence [20] of sleep disturbances in depression and 10% variation, the sample size [21] was calculated to be 43. Application of Shapiro–Wilk test showed that data were not normally distributed. Hence, paired comparison between before and after treatment for BDI score, HAM-D insomnia subscale, and sleep architecture parameters was done using the help of Kruskal–Wallis test. Correlation of HAM-D insomnia subscale with polysomnography was done using Pearson's correlation coefficient.

Data analysis was done using Statistical Package for the Social Science software version 21 (SPSS Inc., Chicago, Illinois, USA). The differences between the groups were considered significant if p-value was less than 0.05.


We recruited 77 male patients. Of them, 9 patients met the exclusion criteria, and 11 were not willing to participate. Consequently, 57 patients were included in the study.

Out of them, 8 patients were lost to follow-up, and 6 did not improve with treatment. Finally, those remaining 43 patients completed the study. The range of the age group was 22 - 46 years with mean age ± standard deviation (SD) being 31.28 ± 5.56 years.

As per ICD-10 DCR, 16.3% of patients were categorized into mild depression, 62.8% into moderate, and remaining, i.e., 20.09% into severe depression. Severity classification as per BDI score revealed 76.74% moderate and remaining 23.26% falling in severe depression category. Sertraline was the most commonly prescribed medicine (41.9%) and escitalopram was the least commonly prescribed antidepressant (9.3%).

As shown in [Table 1], mean ± SD for BDI score before treatment was 26.08 ± 7.33 and after treatment was 4.98 ± 2.44. This difference was significant (p < 0.001). Mean ± SD for HAM-D insomnia subscale score before treatment was 3.40 ± 1.12 and after treatment was 0. This difference also was statistically significant (p < 0.001).{Table 1}{Table 2}

[Table 2] illustrates that the mean ± SD value for total sleep time before treatment was 263.08 ± 93.93 minutes and after treatment was 325.65 ± 43.12 minutes. The difference was statistically significant (p < 0.001). The mean ± SD for sleep efficiency before treatment was 60.94 ± 20.34 30 minutes and after treatment was 76.19 ± 9.18 30 minutes. The difference was significant (p < 0.001). The mean ± SD for wake after sleep onset before treatment was 143.89 ± 93.18 minutes and after treatment was 80.79 ± 48.28 minutes. The difference was statistically (p < 0.001).{Table 2}

[Table 3] illustrates the correlation of HAM-D insomnia subscale with polysomnography. Significant correlation existed between HAM-D insomnia subscale score and total sleep time (p < 0.001). A significant correlation existed between perceived sleep difficulty and sleep efficiency (p < 0.001), wake after sleep onset (p < 0.001), total wake time (p < 0.001), or N2% (p < 0.001). A significant correlation was seen between insomnia and percentage wake time (p < 0.001), N3% (p < 0.01), or N1 latency (p < 0.001).{Table 3}


Patients with depression show abnormalities of almost all sleep parameters. Disrupted sleep continuity manifests as prolongation of sleep latency, increased number and duration of awakenings from sleep expressed as increased wake after sleep onset time, decreased sleep efficiency and early morning awakenings. The distribution of deep sleep scored in polysomnograph as sleep stage N3. It is also called delta or slow-wave sleep, which is also altered in depressed patients [19]. REM sleep disturbances (REM sleep latency, increased REM sleep time, and increased REM sleep density) are considered a biological marker of circadian rhythm disturbances in depression with melancholic features [22]. Antidepressant therapy in the long-term use shows improvement in sleep parameters secondary to improvement of mood and daytime activity [19].

The antidepressant medicines prescribed during our study were escitalopram, fluoxetine, paroxetine, sertraline, and mirtazapine (88.4% of the patients were prescribed SSRIs and 11.6% mirtazapine). The different antidepressants used in the study have different pharmacological profiles and hence might have impacted the improvement of sleep architecture differently. But the prescription pattern in our study is consistent with a recent multicentric study in which 62.2% of patients were prescribed SSRIs and hence is more consistent with real-world clinical practice [23]. Antidepressant drugs improve the sleep architecture through modulating neurotransmitters and their receptors, particularly serotonin, norepinephrine, histamine, muscarinic, and acetylcholine. Paroxetine is potent inhibitor of muscarinic and histamine receptors leading to sedation [24]. The mechanism of action for mirtazapine is unique as it inhibits presynaptic alpha-2 adrenergic receptors and blocks postsynaptic serotonin (5HT2) and histamine (H1) receptors. The antagonism of 5HT2 and H1 leads to improving sleep latency and total sleep time. Mirtazapine is, hence, used in clinical practice either alone or to augment other antidepressants in depressed patients with obvious sleep disturbances [25].

As shown in [Table 1], the BDI score (p < 0.001) and HAM-D insomnia subscale scores (p < 0.001) showed a significant improvement before and after treatment with antidepressants. These findings are consistent with those in previous studies on effects of antidepressants on sleep [26],[27],[28].

[Table 2] shows that significant changes of total sleep time occurred before and after treatment in total sleep time (263.08 ± 93.93 min vs. 325.65 ± 43.12 min, p < 0.001). Pillai et al. [7] and Baglioni et al. [4] have found similar findings with increase in total sleep time after treatment with antidepressants in studies of two different meta-analyses.

The change of sleep efficiency [Table 2] before and after treatment was significant (60.94 ± 20.34 vs. 76.19 ± 9.18, p < 0.001). This finding indicates that treatment of depression significantly improved sleep efficiency. Wichniak et al. have reported similar results with increase in sleep continuity (sleep efficiency and total sleep time) after treatment with antidepressants [19].

As shown in [Table 2], sleep latency was improved after the treatment, but the results were not significant. Significant improvement after treatment was found in wake after sleep onset (p < 0.001), total wake time (p < 0.001), and percentage wake time (p < 0.001). Our study also observed reduced N1 and N2 stages of sleep and increased in N3 stage of sleep, although the differences of these findings were not significant [Table 2]. These findings are consistent with those in many other studies, showing that all antidepressants improve sleep parameters over long-term periods despite the fact that some of them may impair sleep initially due to the activating effects [19],[28].

Effective treatment with antidepressants increases REM latency and suppresses REM sleep [29]. But in our study [Table 2], REM% was significantly increased after treatment with antidepressant therapy (18.54 ± 11.57 vs. 24.53 ± 14.74, p < 0.01). This finding can be attributed to the activating effects of predominantly used SSRIs (88.4% of the patients were prescribed SSRIs and 11.6% mirtazapine) over a short duration of time. The duration of REM latency was not significantly decreased after treatment (118.80 ± 86.13 vs. 111.67 ± 50.67) in current study. This finding is similar to those found in most other sleep studies [7],[19],[29].

As shown in [Table 3], a significant correlation existed between perceived sleep disturbances and total sleep time (p < 0.001). There was a significant correlation between perceived sleep disturbance and sleep efficiency (p < 0.001). Significant correlations also existed between perceived sleep disturbance and wake after sleep onset (p < 0.001), total wake time (p < 0.001), and N2% (p < 0.001). A significant correlation was also noted between perceived sleep disturbance and percentage wake time (p < 0.001), N3% (p < 0.01), and N1 latency (p < 0.001). In a study by Vitiello and Larsen consisting of large group of healthy 150 men and 95 women, to understand the relationship between self-reported subjective and objectively measured sleep quality, the results have shown a considerable correspondence between subjective and objective sleep quality for men but not for women, despite women more frequently endorsing the presence of remarkable sleep disturbance [30]. This finding coincides with our study, which consisted of all male patients. But a pilot study conducted by Moshkani Farahani et al. [31] does not find any significant correlation between perceived sleep disturbances and polysomnographic findings in depressed patients.

Study limitations

The readers are warned not to overinterpret the study findings because the current study has following limitations:

We used BZDs in depressed patients at least initially during the treatment. Being known as having potent REM inhibition among others, BZDs influence the sleep architecture.In dissenting findings, the present evidence in this area is somewhat inconsistent. Such resemblances/differences can be largely disparate in various populations. The study results obtained with specific populations cannot be completely generalized.We did not prescribe serotonin and norepinephrine reuptake inhibitors (SNRIs, i.e., venlafaxine, milnacipran, and duloxetine) for our patients with depression although 11.6% of study patients received mirtazapine. Like mirtazapine, SNRIs belong to “dual action” antidepressants [32],[33] which work much better and quicker for generalized anxiety disorder than an SSRI [34],[35].The levels of patients' exercise or activities were not controlled in recruiting study patients as indicated in patients' inclusion or exclusion criteria in this study. Both antidepressant and exercise can increase brain-derived neurotrophic factor of the brain, resulting in improving insomnia and depressive symptoms [32],[33].

Hence, in an idealistic scenario, a concurrent use of objective and subjective sleep measures can provide more valid and reliable information of the patient's sleep health. Using a practical and easy-to-use psychometric tool can be practiced routinely at least in outpatient settings. All these above-listed limitations in fact bring this study more close to the real-world clinical practice. In the future study, SNRIs should be used to better demonstrate the benefit in patients with sleep disturbances.


Antidepressant treatment effectively improves sleep architecture in depressive disorder and HAM-D insomnia subscale correlates with the objective findings of total sleep time, sleep efficiency, wake after sleep onset, total wake time, and duration of N2 stage of NREM. Therefore, to gain a comprehensive understanding, both subjective and objective sleep measures should be used, but HAM-D insomnia subscale being a simple and inexpensive tool can be a used as a substitute, especially in the outpatient setting.


The authors would like to thank all the patients who consented to participate in this study.

 Financial Support and Sponsorship


 Conflicts of Interest

All authors have none to declare.


1Allada R, Siegel J: Unearthing the phylogenetic roots of sleep. Curr Biol 2008; 18: R670-9.
2Hirshkowitz M: Normal human sleep: an overview. Med Clin North Am 2004; 88: 551-65.
3Harding K, Feldman M: Sleep disorders and sleep deprivation: an unmet public health problem. J Am Acad Child Adolesc Psychiatry 2008; 47: 473-4.
4Baglioni C, Nanovska S, Regen W, et al.: Sleep and mental disorders: a meta-analysis of polysomnographic research. Psychol Bull 2016; 142: 969-90.
5Bixler EO, Vgontzas AN, Lin HM, et al.: Excessive daytime sleepiness in a general population sample: the role of sleep apnea, age, obesity, diabetes, and depression. J Clin Endocrinol Metab 2005; 90: 4510-15.
6Hohagen F, Rink K, Kappler C, et al.: Prevalence and treatment of insomnia in general practice. A longitudinal study. Eur Arch Psychiatry Clin Neurosci 1993; 242: 329-36.
7Pillai V, Kalmbach D, Ciesla J: A meta-analysis of electroencephalographic sleep in depression: evidence for genetic biomarkers. Biol Psychiatry 2011; 70: 912-9.
8Ford D: Epidemiologic study of sleep disturbances and psychiatric disorders. JAMA 1989; 262: 1479-84.
9Kurtis MM, Balestrino R, Rodriguez-Blazquez C, et al.: A review of scales to evaluate sleep disturbances in movement disorders. Front Neurol 2018; 9: 369.
10Gutierrez CT, Lomeli HA, Reyes RE, et al.: Sleep evaluation scales and questionaries: a review. Actas Esp Psiquiatr 2008; 36: 50-9.
11Sasidharan S, Singh V, Babitha M, Dhillon H. COVID19-A report from the Democratic Republic of the Congo. Developing World Bioethics. 2020.
12Sasidharan S, Dhillon HS: Ebola, COVID-19 and Africa: what we expected and what we got. Developing World Bioethics 2021;21:51-4.
13World Health Organization: The ICD-10 Classification of Mental and Behavioral Disorders: Diagnostic Criteria for Research. Geneva, Switzerland: World Health Organization, 1993.
14Joe S, Woolley ME, Brown GK, et al.: Psychometric properties of the Beck Depression Inventory–II in low-income, African American suicide attempters. J Pers Assess 2008; 90: 521-3.
15Rohan KJ, Rough JN, Evans M, et al.: A protocol for the Hamilton rating scale for depression: item scoring rules, rater training, and outcome accuracy with data on its application in a clinical trial. J Affect Disord 2016; 200: 111-8.
16Mottram P, Wilson K, Copeland J: Validation of the hamilton depression rating scale and montgommery and asberg rating scales in terms of AGECAT depression cases. Int J Geriatr Psychiatry 2000; 15: 1113-9.
17Todorova KS, Velikova VS: The validity of the Hamilton depression rating scale as a screening and diagnostic instrument for depression in patients with epilepsy. J IMAB Ann Proc Sci Pap 2012; 18: 305-7.
18Shahid A, Wilkinson K, Marcu S, et al.: Hamilton Rating Scale for Depression (HAM-D). In STOP, THAT and One Hundred Other Sleep Scales. New York, NY: Springer, 2011: 187-90.
19Wichniak A, Wierzbicka A, Walęcka M, et al.: Effects of antidepressants on sleep. Curr Psychiatry Rep 2017; 19: 63.
20Mccall W, Reboussin B, Cohen W: Subjective measurement of insomnia and quality of life in depressed inpatients. J Sleep Res 2000; 9: 43-8.
21Charan J, Biswas T: How to calculate sample size for different study designs in medical research. Indian J Psychol Med 2013; 35: 121-6.
22Wichniak A, Wierzbicka A, Jernajczyk W: Sleep as a biomarker for depression. Int Rev Psychiatry 2013; 25: 632-45.
23Tripathi A, Avasthi A, Desousa A, et al.: Prescription pattern of antidepressants in five tertiary care psychiatric centres of India. Indian J Med Res 2016; 143: 507.
24Winokur A, Gary KA, Rodner S, et al.: Depression, sleep physiology, and antidepressant drugs. Depress Anxiety 2001; 14: 19-28.
25Winokur A, DeMartinis NA 3rd, McNally DP, et al.: Comparative effects of mirtazapine and fluoxetine on sleep physiology measures in patients with major depression and insomnia. J Clin Psychiatry 2003; 64: 1224-9.
26Neckelmann D, Bjorvatn B, Bjørkum A, et al.: Citalopram: differential sleep/wake and EEG power spectrum effects after single dose and chronic administration. Behav Brain Res 1996; 79: 183-92.
27Vasar V, Appelberg B, Rimón R, et al.: The effect of fluoxetine on sleep. Int Clin Psychopharmacol 1994; 9: 203-6.
28Oberndorfer S, Saletu-Zyhlarz G, Saletu B: Effects of selective serotonin reuptake inhibitors on objective and subjective sleep quality. Neuropsychobiology 2000; 42: 69-81.
29Wilson S, Argyropoulos S: Antidepressants and sleep: a qualitative review of the literature. Drugs 2005; 65: 927-47.
30Vitiello MV, Larsen LH, Moe KE: Age-related sleep change: gender and estrogen effects on the subjective- objective sleep quality relationships of healthy, noncomplaining older men and women. J Psychosom Res 2004; 56: 503-10.
31Moshkani Farahani D, Tavallaie A, Vahedi E, et al.: The relationship between perceived sleep quality, polysomnographic measures and depressive symptoms in chemically injured veterans: a pilot study. Iran J Psychiatry 2014; 9: 169-74.
32Shen WW: Antidepressant therapy. Aino J (Osaka) 2016; 15: 1-13.
33Shen WW: Rehabilitative and habilitative perspectives of exercise in treating patients with major depressive disorder. Cogn Rehabil (Osaka) 2020; 1: 102-11.
34Allgulander C, Hackett D, Salinas E: Venlafaxine extended release (ER) in the treatment of generalised anxiety disorder: twenty-four-week placebo-controlled dose-ranging study. Br J Psychiatry 2001; 179: 15-22.
35Allgulander C, Dahl AA, Carol Austin C, et al.: Efficacy of sertraline in a 12-week trial for generalized anxiety disorder. Am J Psychiatry 2004; 161: 1642-9.