Poor sleep quality is frequent among COPD patients and it has been related to worse outcomes. The objective of this study was to compare the COPD and Asthma Sleep Impact Scale (CASIS) and the generic ...Pittsburgh Sleep Quality Index (PSQI) questionnaires as reliable tools for evaluating sleep quality and its relationship with COPD characteristics and survival. Stable COPD patients were prospectively evaluated. Anthropometric, sociodemographic, comorbidity, lung function and treatment data were collected. All patients completed CASIS and PSQI, mMRC dyspnea severity scale, COPD Assessment Test (CAT), sleep apnoea STOP-Bang and Hospital Anxiety and Depression Scale (HADS) questionnaires. Body mass index, airflow Obstruction, Dyspnea and Exacerbations (BODEx) index was calculated. Life status was determined after a mean follow-up of 3.7 (SD 1) years. We included 200 patients, 69.5% male, mean age 65.8 (9) years. Poor sleep was detected in 100 (50%) and 84 patients (42%) according to PSQI and CASIS questionnaires, respectively, with an agreement of 63%. Poor sleep was related to female gender, more severe dyspnea and worse BODEx, HADS and CAT scores according to both questionnaires. PSQI was associated to chronic pain or inferior urinary tract symptoms and CASIS to exacerbations, shorter walked distance in the 6-min walking test and treatment with oral corticosteroids or chronic oxygen. Thirty nine (19.5%) patients died during follow-up. Mortality was not associated to PSQI nor CASIS results. Unlike PSQI, CASIS is more related to COPD severity and its results are not influenced by comorbidities with known impact on sleep quality. In our sample, poor sleep quality was not associated with increased mortality.
Retrospective chart audit.
Describing the respiratory complications and their predictive factors in patients with acute traumatic spinal cord injuries at C5-T5 level during the initial ...hospitalization.
Hospital Vall d'Hebron, Barcelona.
Data from patients admitted in a reference unit with acute traumatic injuries involving levels C5-T5. Respiratory complications were defined as: acute respiratory failure, respiratory infection, atelectasis, non-hemothorax pleural effusion, pulmonary embolism or haemoptysis. Candidate predictors of these complications were demographic data, comorbidity, smoking, history of respiratory disease, the spinal cord injury characteristics (level and ASIA Impairment Scale) and thoracic trauma. A logistic regression model was created to determine associations between potential predictors and respiratory complications.
We studied 174 patients with an age of 47.9 (19.7) years, mostly men (87%), with low comorbidity. Coexistent thoracic trauma was found in 24 (19%) patients with cervical and 35 (75%) with thoracic injuries (p < 0.001). Respiratory complications were frequent (53%) and were associated to longer hospital stay: 83.1 (61.3) and 45.3 (28.1) days in patients with and without respiratory complications (p < 0.001). The strongest predictors of respiratory complications were: previous respiratory disease (OR 5.4, 95% CI: 1.5-19.2), complete motor function impairment (AIS A-B) (OR 4.7, 95% CI: 2.4-9.5) and concurrent chest trauma (OR 3.73, 95% CI: 1.8-7.9).
Respiratory complications are common in traumatic spinal cord injuries between C5-T5. We identified previous respiratory disease, complete motor function impairment and the coexistence of thoracic trauma as predictors of respiratory complications. Identification of patients at risk might help clinicians to implement preventive strategies.
Although sleep apnea-hypopnea syndrome (SAHS) is highly prevalent in patients with type 2 diabetes (T2D), it is unknown whether or not subjects with and without T2D share the same sleep breathing ...pattern.
A cross-sectional study in patients with SAHS according to the presence (n = 132) or not (n = 264) of T2D. Both groups were matched by age, gender, BMI, and waist and neck circumferences. A subgroup of 125 subjects was also matched by AHI. The exclusion criteria included chronic respiratory disease, alcohol abuse, use of sedatives, and heart failure. A higher apnea hypopnea index (AHI) was observed in T2D patients 32.2 (10.2-114.0) vs. 25.6 (10.2-123.4) events/hours; p = 0.002). When sleep events were evaluated separately, patients with T2D showed a significant increase in apnea events 8.4 (0.1-87.7) vs. 6.3 (0.0-105.6) e/h; p = 0.044), as well as a two-fold increase in the percentage of time spent with oxygen saturation <90% 15.7 (0.0-97.0) vs. 7.9 (0.0-95.6) %; <0.001), higher rates of oxygen desaturation events, and also higher daily sleepiness 7.0 (0.0-21.0) vs. 5.0 (0.0-21.0); p = 0.006) than subjects without T2D. Significant positive correlations between fasting plasma glucose and AHI, the apnea events, and CT90 were observed. Finally, multiple linear regression analyses showed that T2D was independently associated with AHI (R2 = 0.217), the apnea index (R2 = 0.194), CT90 (R2 = 0.222), and desaturation events.
T2D patients present a different pattern of sleep breathing than subject without diabetes. The most important differences are the severity of hypoxemia and the number of apneas whereas the incidence of hypopnea episodes is similar.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Type 2 diabetes (T2D) is an independent risk factor for sleep breathing disorders. However, it is unknown whether T2D affects daily somnolence and quality of sleep independently of the impairment of ...polysomnographic parameters.
A case-control study including 413 patients with T2D and 413 non-diabetic subjects, matched by age, gender, BMI, and waist and neck circumferences. A polysomnography was performed and daytime sleepiness was evaluated using the Epworth Sleepiness Scale (ESS). In addition, 135 subjects with T2D and 45 controls matched by the same previous parameters were also evaluated through the Pittsburgh Sleep Quality Index (PSQI) to calculate sleep quality.
Daytime sleepiness was higher in T2D than in control subjects (p = 0.003), with 23.9% of subjects presenting an excessive daytime sleepiness (ESS>10). Patients with fasting plasma glucose (FPG ≥13.1 mmol/l) were identified as the group with a higher risk associated with an ESS>10 (OR 3.9, 95% CI 1.8-7.9, p = 0.0003). A stepwise regression analyses showed that the presence of T2D, baseline glucose levels and gender but not polysomnographic parameters (i.e apnea-hyoapnea index or sleeping time spent with oxigen saturation lower than 90%) independently predicted the ESS score. In addition, subjects with T2D showed higher sleep disturbances PSQI: 7.0 (1.0-18.0) vs. 4 (0.0-12.0), p<0.001.
The presence of T2D and high levels of FPG are independent risk factors for daytime sleepiness and adversely affect sleep quality. Prospective studies addressed to demonstrate whether glycemia optimization could improve the sleep quality in T2D patients seem warranted.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Sleep apnea, a condition that modifies sleep and circadian rhythms, is highly prevalent in patients with diabetes. However, it is not known if there is an association between sleep apnea, circadian ...alterations and glycemic regulation in this type of patient. Here, a polysomnographic study was carried out on 21 women and 25 men (mean age = 64.3 ± 1.46 years) with diagnoses of type 2 diabetes to detect the presence of sleep apnea. Moreover, patients wore an actigraph and a temperature sensor on the wrist for one week, to study the manifestation of the circadian rhythms. The correlations of circadian and polysomnographic variables with the severity of apnea, measured by the apnea-hypopnea index, and with glycemic dysregulation, measured by the percentage of glycated hemoglobin, were analyzed. The mean apnea-hypoapnea index of all the participants was 39.6 ± 4.3. Apnea-hypoapnea index correlated with % N1, negatively with % N3, and also the stability of the active circadian rhythm. However, no significant correlation was found between the apnea-hypopnea index and wrist temperature rhythm and glycated hemoglobin. Glycated hemoglobin levels were negatively associated with the percentage of variance explained by the wrist temperature circadian rhythm (calculated via 24 and 12 h rhythms). This association was independent of body mass index and was strongest in patients with severe apnea. In conclusion, patients with diabetes showed altered circadian rhythms associated with a poor glycemic control and this association could partially be related to the coexistence of sleep apnea.
The coordination between different levels of care is essential for the management of obstructive sleep apnea (OSA). The objective of this multicenter project was to develop a screening model for OSA ...in the primary care setting.
Anthropometric data, clinical history, and symptoms of OSA were recorded in randomly selected primary care patients, who also underwent a home sleep apnea test (HSAT). Respiratory polygraphy or polysomnography were performed at the sleep unit to establish definite indication for continuous positive airway pressure (CPAP). By means of cross-validation, a logistic regression model (CPAP yes/no) was designed, and with the clinical variables included in the model, a scoring system was established using the β coefficients (PASHOS Test). In a second stage, results of HSAT were added, and the final accuracy of the model was assessed.
194 patients completed the study. The clinical test included the body mass index, neck circumference and observed apneas during sleep (AUC 0.824, 95% CI 0.763-0.886, P < 0.001). In a second stage, the oxygen desaturation index (ODI) of 3% (ODI3% ≥ 15%) from the HSAT was added (AUC 0.911, 95% CI 0.863-0.960, P < 0.001), with a sensitivity of 85.5% (95% CI 74.7-92.1) and specificity of 67.8% (95% CI 55.1-78.3).
The use of this model would prevent referral to the sleep unit for 55.1% of the patients. The two-stage PASHOS model is a useful and practical screening tool for OSA in primary care for detecting candidates for CPAP treatment. Clinical Trial Registration Registry: ClinicalTrials.gov; Name: PASHOS Project: Advanced Platform for Sleep Apnea Syndrome Assessment; URL: https://clinicaltrials.gov/ct2/show/NCT02591979 ; Identifier: NCT02591979. Date of registration: October 30, 2015.
Type 2 diabetes mellitus (T2DM) and obesity have become two of the main threats to public health in the Western world. In addition, obesity is the most important determinant of the sleep ...apnea-hypopnea syndrome (SAHS), a condition that adversely affects glucose metabolism. However, it is unknown whether patients with diabetes have more severe SAHS than non-diabetic subjects. The aim of this cross-sectional case-control study was to evaluate whether obese patients with T2DM are more prone to severe SAHS than obese non-diabetic subjects.
Thirty obese T2DM and 60 non-diabetic women closely matched by age, body mass index, waist circumference, and smoking status were recruited from the outpatient Obesity Unit of a university hospital. The exclusion criteria included chronic respiratory disease, smoking habit, neuromuscular and cerebrovascular disease, alcohol abuse, use of sedatives, and pregnancy. Examinations included a non-attended respiratory polygraphy, pulmonary function testing, and an awake arterial gasometry. Oxygen saturation measures included the percentage of time spent at saturations below 90% (CT90). A high prevalence of SAHS was found in both groups (T2DM:80%, nondiabetic:78.3%). No differences in the number of sleep apnea-hypopnea events between diabetic and non-diabetic patients were observed. However, in diabetic patients, a significantly increase in the CT90 was detected (20.2+/-30.2% vs. 6.8+/-13,5%; p = 0.027). In addition, residual volume (RV) was significantly higher in T2DM (percentage of predicted: 79.7+/-18.1 vs. 100.1+/-22.8; p<0.001). Multiple linear regression analyses showed that T2DM but not RV was independently associated with CT90.
T2DM adversely affects breathing during sleep, becoming an independent risk factor for severe nocturnal hypoxemia in obese patients. Given that SAHS is a risk factor of cardiovascular disease, the screening for SAHS in T2DM patients seems mandatory.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Poor sleep and attention deficits are common in COPD.
To assess the relationship between self-reported poor sleep and attention deficits in COPD. We also studied the association between self-reported ...sleep and the attention tests with the objective characteristics of sleep.
Fifty-nine COPD patients were prospectively studied. Self-reported sleep quality was assessed using the Pittsburgh sleep quality index (PSQI). Objective characteristics of sleep were assessed by actigraphy and polysomnography. Attention was evaluated with the Oxford sleep resistance test (OSLER) and the Psychomotor vigilance test (PVT).
28 (47 %) patients referred poor sleep (PSQI >5). In the OSLER test they showed earlier sleep onset than patients with good sleep, median (Interquartil range): 31.2 min (25.4–40) vs 40 min (28.5–40), p: 0.048. They also spent more time making errors: 4.5 % (0.6–7.6) of total test time vs 0.7 % (0.2–5.3), p: 0.048. In PVT, patients with poor sleep presented a greater dispersion of the reaction time values with a higher value in the slowest 10 % of the reactions, 828 (609–1667) msec. vs 708 (601–993) msec, p: 0.028. No association was found between self-reported poor sleep and objective sleep variables. We found no correlation between OSLER and PVT results and polysomnographic variables except between sleep efficiency and PVT response speed (β: 0.309, p: 0.018).
Self-reported poor sleep in COPD is associated with attention deficits. Sleep quality should be included in future studies of this facet of cognition in COPD, as well as to assess its potential usefulness as a therapeutic target.
•Poor sleep quality is frequent in COPD patients.•Self-reported poor sleep is associated with attention deficits in COPD patients.•COPD patients with reported poor sleep make more errors and have slower reactions.•Pittsburgh questionnaire and polysomnographic variables are not related in COPD.
Obstructive Sleep Apnea and Thoracic Aorta Dissection Sampol, Gabriel; Romero, Odile; Salas, Armando ...
American journal of respiratory and critical care medicine,
12/2003, Letnik:
168, Številka:
12
Journal Article
Recenzirano
Obstructive sleep apnea syndrome (OSAS) is a process that is associated with the development of arterial hypertension, the main risk factor for aortic dissection and during obstructive episodes of ...the upper airways with marked increases in transmural pressure of the aorta wall. The aim of this work was to study the association between aortic dissection and OSAS. Nineteen consecutive patients with thoracic aorta dissection and 19 hypertensive patients of similar age, sex, and body mass index were studied by clinical questionnaire and polysomnography. Snoring and nonrefreshing sleep were common in both groups. Thirteen patients (68%) from each group showed an apnea-hypopnea index of more than 5 per hour. However, patients with aortic dissection presented a higher apnea-hypopnea index (28 30.3 versus 11.1 10.4, p=0.032). Seven patients with dissection presented an apnea-hypopnea index of more than 30 versus 1 patient in the control group (p=0.042). Patients with thoracic aorta dissection presented a high prevalence of previously undiagnosed and frequently severe OSAS. Further studies, including this diagnosis as a prognostic variable in the follow-up of patients with aortic dissection, are required. Our results suggest that in patients with aortic dissection and symptoms consistent with OSAS, a sleep study should be considered in their clinical management.
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