scholarly journals Cancer-related fatigue presenting with excessive daytime sleepiness

2017 ◽  
Vol 5 ◽  
pp. 2050313X1774886
Author(s):  
Diwakar D Balachandran ◽  
Saadia A Faiz ◽  
Lara Bashoura ◽  
Ellen Manzullo

Cancer-related fatigue is a common symptom in cancer patients which commonly occurs in relation to sleep disturbance. We report a case of a 35-year-old breast cancer survivor, in whom polysomnography and multiple sleep latency testing were utilized to objectively quantify the contribution of excessive daytime sleepiness to the patient’s cancer-related fatigue.

Author(s):  
Jeny Jacob ◽  
Rajesh Venkataram ◽  
Nandakishore Baikunje ◽  
Rashmi Soori

AbstractNarcolepsy, a sleep disorder, has its onset in childhood and early adulthood but rarely in older adults. This case report focuses on a man in his late fifties who was noticed to have excessive daytime sleepiness during his stay in our hospital for an unrelated medical ailment. He was further evaluated with overnight polysomnography and next day multiple sleep latency test which confirmed the diagnosis of narcolepsy.


1978 ◽  
Vol 45 (5) ◽  
pp. 621-627 ◽  
Author(s):  
Gary S Richardson ◽  
Mary A Carskadon ◽  
Wayne Flagg ◽  
Johanna Van den Hoed ◽  
William C Dement ◽  
...  

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A477-A477
Author(s):  
Kamal Patel ◽  
Bianca J Lang

Abstract Introduction Presence of sleep onset REM episodes often raises concerns of narcolepsy. However other conditions have shown to have presence of sleep on REM episodes which include but not limited to obstructive sleep apnea, sleep wake schedule disturbance, alcoholism, neurodegenerative disorders, depression and anxiety Report of Case Here we present a case of 30 year old female with history of asthma, patent foraman ovale, migraine headache, and anxiety who presented with daytime sleepiness, falling asleep while at work, occasional scheduled naps, non-restorative sleep, sleep paralysis, and hypnopompic hallucination. Pertinent physical exam included; mallampati score of 4/4, retrognathia, high arched hard palate, crowded posterior oropharynx. She had a score of 16 on Epworth sleepiness scale. Patient previously had multiple sleep latency test at outside facility which revealed 4/5 SOREM, with mean sleep onset latency of 11.5 minutes. She however was diagnosed with narcolepsy and tried on modafinil which she failed to tolerate. She was tried on sertraline as well which was discontinued due to lack of benefit. She had repeat multiple sleep latency test work up which revealed 2/5 SOREM, with mean sleep onset latency was 13.1 minutes. Her overnight polysomnogram prior to repeat MSLT showed SOREM with sleep onset latency of 10 minutes. Actigraphy showed consistent sleep pattern overall with sufficient sleep time but was taking hydroxyzine and herbal medication. Patient did not meet criteria for hypersomnolence disorder and sleep disordered breathing. Conclusion There is possibility her medication may have played pivotal role with her daytime symptoms. We also emphasize SOREMs can be present in other disorders such as anxiety in this case and not solely in narcolepsy


SLEEP ◽  
2020 ◽  
Vol 43 (12) ◽  
Author(s):  
Sami Nikkonen ◽  
Henri Korkalainen ◽  
Samu Kainulainen ◽  
Sami Myllymaa ◽  
Akseli Leino ◽  
...  

Abstract A common symptom of obstructive sleep apnea (OSA) is excessive daytime sleepiness (EDS). The gold standard test for EDS is the multiple sleep latency test (MSLT). However, due to its high cost, MSLT is not routinely conducted for OSA patients and EDS is instead evaluated using sleep questionnaires. This is problematic however, since sleep questionnaires are subjective and correlate poorly with the MSLT. Therefore, new objective tools are needed for reliable evaluation of EDS. The aim of this study was to test our hypothesis that EDS can be estimated with neural network analysis of previous night polysomnographic signals. We trained a convolutional neural network (CNN) classifier using electroencephalography, electrooculography, and chin electromyography signals from 2,014 patients with suspected OSA. The CNN was trained to classify the patients into four sleepiness categories based on their mean sleep latency (MSL); severe (MSL < 5min), moderate (5 ≤ MSL < 10), mild (10 ≤ MSL < 15), and normal (MSL ≥ 15). The CNN classified patients to the four sleepiness categories with an overall accuracy of 60.6% and Cohen’s kappa value of 0.464. In two-group classification scheme with sleepy (MSL < 10 min) and non-sleepy (MSL ≥ 10) patients, the CNN achieved an accuracy of 77.2%, with sensitivity of 76.5%, and specificity of 77.9%. Our results show that previous night’s polysomnographic signals can be used for objective estimation of EDS with at least moderate accuracy. Since the diagnosis of OSA is currently confirmed by polysomnography, the classifier could be used simultaneously to get an objective estimate of the daytime sleepiness with minimal extra workload.


2020 ◽  
Vol 19 ◽  
pp. 153473542096378
Author(s):  
Friedemann Schad ◽  
Anja Thronicke ◽  
Phillipp von Trott ◽  
Shiao Li Oei

Introduction: Cancer-related fatigue (CRF) occurs frequently in breast cancer patients. The aim of this real-world study was to analyze the longitudinal changes of CRF in breast cancer patients receiving an integrative medicine program, which includes the application of non-pharmacological interventions (NPIs) and Viscum album L. (VA) extracts. Methods: All data were collected from the clinical register of the Network Oncology of a German certified breast cancer center of the Gemeinschaftskrankenhaus Havelhöhe (GKH). Primary breast cancer patients, treated upon initial diagnosis with integrated NPIs, comprising art and exercise therapy, nursing interventions, and educational components, during their hospital stay, and who had answered the German Cancer-Fatigue Scale (CFS-D) questionnaire at first diagnosis and 12 months later, were included. The associations between NPIs and CFS-D changes were analyzed with adjusted multivariable regression analyses, considering received treatment regimens and demographic variables, using the software R. Results: 231 female breast cancer patients of all tumor stages were evaluated. While chemotherapy exhibited significant severe deterioration, add-on VA applications seem to partially mitigate this impairment on CRF. 36 separate multivariable regression analyses for all NPIs showed that in particular significant associations between CFS-D improvements and the interventions nursing compresses (6 point change; P = .0002; R² = 28%) or elaborate consultations and life review (ECLR) (4 point change; P = .0002; R² = 25%) were observed. Conclusions: Breast cancer patients benefit from a hospital-based integrative medicine program. To alleviate fatigue symptoms during oncological therapy, an expansion of this concept should be developed in the future.


SLEEP ◽  
2012 ◽  
Vol 35 (11) ◽  
pp. 1467-1473 ◽  
Author(s):  
R. Nisha Aurora ◽  
Carin I. Lamm ◽  
Rochelle S. Zak ◽  
David A. Kristo ◽  
Sabin R. Bista ◽  
...  

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