Fatigue has a prominent impact on health lasting 12-weeks after COVID-19 infection.

Background: While the amount of information on many issues related to COVID-19 has increased, the long-term consequences of illness and disability remain largely unclear. In previous studies on COVID-19 infections, long-lasting functional and symptomatic abnormalities have also been shown. It is predicted that survivors of COVID-19 may have to deal with physical or psychological problems later. Aim: We aimed to evaluate long-lasting symptoms including fatigue and investigate the associated risk factors. Methods: In this prospective cohort study, 132 consecutive COVID-19 patients who were previously diagnosed and admitted 13±1 weeks after diagnosis were included. The Functional Assessment of Chronic Illness Therapy (FACIT) - Fatigue Scale, the Beck Anxiety Inventory, the Beck Depression Inventory, and the Lawton Instrumental Activities of Daily Living (IADL) Scale were applied in the follow-up visit. Results: The median age of the patients (76 male, 56 female) was 52. Eighty (61%) of the patients were hospitalized, while 52 (39%) of them were not hospitalized. At least one symptom persisted in 103 (78%) patients, with fatigue (n=48, 36%) being the most common symptom. Both dyspnea and fatigue were more prominent in women than in men (34% vs. 11%, p=0.001 and 46% vs 29%, p=0.03; respectively). Persisted symptoms including fatigue were not significantly associated with hospitalization status. The FACIT scores of the patients at 12 weeks were positively associated with their depression and anxiety levels (R: 0.55, p=0.0001 and R: 0.42, p=0.0001), while they were negatively associated with their IADL scores (R: -0.25, p=0.004). Conclusions: Fatigue was the most frequent persistent symptom. The initial fatigue scores were higher in the severely ill patients. Persistent fatigue was not associated with disease severity but was closely associated with anxiety and depression.

Does smoking impair sleep hygiene?

BACKGROUND: Sleep architecture and sleep hygiene might be disrupted by several pathogenetic mechanisms, and the effect of smoking has not been evaluated. OBJECTIVE: To investigate the effect of smoking on sleep hygiene behaviors that might be associated with the deterioration of quality-of-life (QoL) parameters. METHODS: In a prospective cross-sectional study, smokers (n=114) and nonsmokers (n=119) were included. The Pittsburgh Sleep Quality Index (PSQI), the Epworth Daytime Sleepiness Scale (ESS), the Sleep Hygiene Index (SHI), and the Short Form-36 quality of life scale (SF-36) were applied. RESULTS: We found that none of the components, as well as the PSQI total score were affected in smokers compared with the nonsmoker controls (65.5% of smokers had poor sleep compared to 62.5% of nonsmokers). Although smokers tend to get out of bed at different times from day to day and do important work before bedtime (components of the SHI) more often than non-smokers, no significant differences were detected between groups in any component and SHI total score (27.91±6.72 for smokers and 29.23±8.0 for non-smokers). ESS, depression and anxiety symptoms, and SHI scores in smokers with poor sleep quality were significantly different compared with smokers that had normal sleep quality. Both PSQI and SHI scores were inversely associated with QoL parameters. CONCLUSIONS: Our results suggest that smoking by itself is not associated with poor sleep hygiene or sleep quality. It can be concluded that worse SHI and quality of sleep negatively affect QoL, depression, and anxiety in smokers.

Does smoking impair sleep hygiene? / O tabagismo prejudica a higiene do sono?

ABSTRACT Background: Sleep architecture and sleep hygiene might be disrupted by several pathogenetic mechanisms, and the effect of smoking has not been evaluated. Objective: To investigate the effect of smoking on sleep hygiene behaviors that might be associated with the deterioration of quality-of-life (QoL) parameters. Methods: In a prospective cross-sectional study, smokers (n=114) and nonsmokers (n=119) were included. The Pittsburgh Sleep Quality İndex (PSQI), the Epworth Daytime Sleepiness Scale (ESS), the Sleep Hygiene Index (SHI), and the Short Form-36 quality of life scale (SF-36) were applied. Results: We found that none of the components, as well as the PSQI total score were affected in smokers compared with the nonsmoker controls (65.5% of smokers had poor sleep compared to 62.5% of nonsmokers). Although smokers tend to get out of bed at different times from day to day and do important work before bedtime (components of the SHI) more often than non-smokers, no significant differences were detected between groups in any component and SHI total score (27.91±6.72 for smokers and 29.23±8.0 for non-smokers). ESS, depression and anxiety symptoms, and SHI scores in smokers with poor sleep quality were significantly different compared with smokers that had normal sleep quality. Both PSQI and SHI scores were inversely associated with QoL parameters. Conclusions: Our results suggest that smoking by itself is not associated with poor sleep hygiene or sleep quality. It can be concluded that worse SHI and quality of sleep negatively affect QoL, depression, and anxiety in smokers.

RESUMO Antecedentes: A arquitetura e a higiene do sono podem ser interrompidas por vários mecanismos patogenéticos, e o efeito do tabagismo ainda não foi avaliado. Objetivo: Investigar o efeito do tabagismo nos comportamentos de higiene do sono que podem estar associados à deterioração dos parâmetros de qualidade de vida (QV). Métodos: Em um estudo transversal prospectivo, foram incluídos fumantes (n=114) e não fumantes (n=119). Foram aplicados o índice de qualidade do sono de Pittsburgh (Pittsburgh Sleep Quality İndex - PSQI), a escala de sonolência diurna de Epworth (ESS), o índice de higiene do sono (Sleep Hygiene Index - SHI) e a escala de qualidade de vida Short Form-36 (SF-36). Resultados: Descobrimos que nenhum dos componentes, assim como o escore total do PSQI, foram afetados em fumantes em comparação com os controles não fumantes (65,5% dos fumantes dormiam mal em comparação com 62,5% dos não fumantes). Embora os fumantes tendam a sair da cama em horários diferentes do dia a dia e fazer trabalhos importantes antes de dormir (componentes do SHI) com mais frequência do que os não fumantes, não foram detectadas diferenças significativas entre os grupos em qualquer componente e pontuação total do SHI (27,91±6,72 para fumantes e 29,23±8,0 para não fumantes). A ESS, os sintomas de depressão e ansiedade e os escores SHI em fumantes com má qualidade de sono foram significativamente diferentes em comparação com fumantes com qualidade de sono normal. Os escores do PSQI e SHI foram inversamente associados aos parâmetros de QV. Conclusões: Nossos resultados sugerem que o tabagismo por si só não está associado à má higiene ou qualidade do sono. Pode-se concluir que o pior SHI e a qualidade do sono afetam negativamente a QV, a depressão e a ansiedade em fumantes.

Comparison of clinical and biochemical features of hospitalized COVID-19 and influenza pneumonia patients.

Both severe acute respiratory syndrome coronavirus 2 and influenza viruses cause similar clinical presentations. It is essential to assess severely ill patients presenting with a viral syndrome for diagnostic and prognostic purposes. We aimed to compare clinical and biochemical features between pneumonia patients with coronavirus disease 2019 (COVID-19) and H1N1. Sixty patients diagnosed with COVID-19 pneumonia and 61 patients diagnosed with influenza pneumonia were hospitalized between October 2020-January 2021 and October 2017-December 2019, respectively. All the clinical data and laboratory results, chest computed tomography scans, intensive care unit admission, invasive mechanical ventilation, and outcomes were retrospectively evaluated. The median age was 65 (range 32-96) years for patients with a COVID-19 diagnosis and 58 (range 18-83) years for patients with influenza (p = 0.002). The comorbidity index was significantly higher in patients with COVID-19 (p = 0.010). Diabetes mellitus and hypertension were statistically significantly more common in patients with COVID-19 (p = 0.019, p = 0.008, respectively). The distribution of severe disease and mortality was not significantly different among patients with COVID-19 than influenza patients (p = 0.096, p = 0.049).). In comparison with inflammation markers; C-reactive protein (CRP) levels were significantly higher in influenza patients than patients with COVID-19 (p = 0.033). The presence of sputum was predictive for influenza (odds ratio [OR] 0.342 [95% confidence interval [CI], 2.1.130-0.899]). CRP and platelet were also predictive for COVID-19 (OR 4.764 [95% CI, 1.003-1.012] and OR 0.991 [95% CI 0.984-0.998], respectively. We conclude that sputum symptoms by itself are much more detected in influenza patients. Besides that, lower CRP and higher PLT count would be discriminative for COVID-19.

The Effect of Sleep Hygiene and Sleep Deterioration on Quality of Life in Shiftworking Healthcare Professionals.

INTRODUCTION: Deterioration in sleep quality and sleep hygiene may result in impairments on mental and physical health leading to deterioration of quality of life (QoL) in healthcare shift workers. We aimed to determine the presence of sleep deterioration as well as poor sleep hygiene, and if any, the effects of these on health-related outcomes. METHODS: This study prospectively included healthcare professionals who did and did not work shifts (n=90 and n=66, respectively). The participants completed the Pittsburgh Sleep Quality Index (PSQI), Sleep Hygiene Index (SHI), Epworth Daytime Sleepiness Scale (EDSS), Short Form-36 quality of life scale (SF-36), and the Beck depression (BD) and Beck anxiety (BA) scales. RESULTS: Although the total PSQI scores showed a tendency to increase in shift workers, no significant differences were observed in total scores as well as subdivisions, except for an increase in sleep latency. Increased SHI total score in shift workers were represent more deteriorated sleep hygiene behavior (p=0.002). Increased needs of daytime nap, variability of both go and get out of bed and stay in bed longer than usual were recorded respectively (p: 0.001, p: 0.001, p: 0.001, p: 0.001, p: 0.001). SHI had prominent effects on QoL parameters such as vitality (r=-0.284, p=0.007), social function (r=-0.323, p=0.002), mental health (r=-0.274, p=0.009), and calculated mental component total score (r=-0.302, p=0.004). CONCLUSION: In our study, we clearly detected prolonged sleep latency and poor sleep hygiene in shift workers which should be responsible for the deterioration of QoL.

D-dimer/Fibrinogen ratio and recurrent exacerbations might have a potential impact to predict 90-day mortality in patients with COPD exacerbation.

Background: According to the World Health Organisation reports (WHO), COPD is the third leading cause of overall in the World by 2020. Aim: We aimed to determine the prognostic predictors of 90-day mortality after an initial exacerbation in patients with acute exacerbation of COPD (AECOPD). Results: Increased Charlson Comorbidity Score(CCS) (HR:1.47; p<0.05), readmission after initial exacerbation (HR:1.47; p<0.05) were predictive risk factors for 30-day mortality in multivariable regression model. The 90-day mortality rate was %11.8. Hypertension, increased median age, nutrition risk score (NRS), CCS, CAT score, and mMRC 4th level were possible risk factors for 90-day mortality. There was a significant difference in the mortality of patients with D-dimer/Fibrinogen ratios>0.11 and ≤0.11 (HR:2.47; p<0.05). Recurrent exacerbations after discharge were predictive risk factors for 90-day mortality in the multivariable regression model (HR:2.25; p<0.001) with the increased mortality risk 4.73 times (HR:4.73; p=0.002). Furthermore, a 1-unit increment of acute exacerbation increased the mortality risk 3.39 times (HR:3.39; p<0.001). Conclusion: Our study showed that D-dimer/Fibrinogen ratio but not D-dimer and recurrent exacerbations after discharge might have a critical impact on 90-day mortality.

The role of typical and atypical pathogens in acute exacerbations of chronic obstructive pulmonary disease.

OBJECTIVES: The exact role of Mycoplasma pneumoniae, Chlamydophila pneumoniae, and Legionella pneumophila in the development of chronic obstructive pulmonary disease exacerbations remains to be elucidated. This study was conducted to identify nonspecific and atypical pathogens associated with acute exacerbations of COPD. MATERIALS AND METHODS: Between February 2013 and February 2015, 107 patients were analyzed. Sixty-nine comprised the inpatient and 38 comprised the outpatient treatment group. RESULTS: When nonspecific culture results were taken into consideration only a causative organism could be detected in 46.7% of the patients. The detection rate increased to 85.1% with the additional use of polymerase chain reaction (PCR), direct fluorescent antibody (DFA) test, and culture methods. More than one causative agent was responsible for COPD exacerbation in 53.3% of patients: two agents in 37.3%, three agents in 15%, and four agents in 0.9%. H. influenzae was detected in 63 (58.9%) patients, S. pneumoniae in 57 (53.2%), P. aeruginosa in 15 (14.0%), and L. pneumophila in 11 (10%). L. pneumophila was the more commonly isolated agent in the inpatient group (P = 0.002). Patients receiving continuous oxygen therapy and noninvasive mechanical ventilation were more likely to have an exacerbation associated with P. aeruginosa (P = 0.008 and P = 0.009, respectively). CONCLUSION: The additional use of DFA for Legionella and multiplex PCR in combination with nonspecific microbiological culturing methods greatly improves the ability to identify infectious agents in acute exacerbations of COPD. There should be a high index of suspicion for P.aeruginosa as a causative organism, particularly in subjects receiving continuous oxygen therapy and/or using NIV and L. pneumophila should certainly be taken into consideration in severe COPD exacerbations.

The Adverse Effects and Treatment Results of Smoking Cessation Pharmacotherapy During Fasting/Non-Fasting State.

BACKGROUND: Cigarette smoking is one of the most common addictions worldwide. Muslim smokers reduce the number of cigarettes they smoke during Ramadan due to the long fasting hours. OBJECTIVES: We aimed to share our experience in a smoking cessation clinic during Ramadan by analyzing the efficacy and adverse effects of once-daily dosing of bupropion or varenicline in a fasting group compared with conventional dosing in a non-fasting group. METHODS: We analyzed 57 patients who attended our smoking cessation clinic during Ramadan of 2014 and 2015, and at least one follow-up visit. For the fasting patients, we prescribed bupropion or varenicline after dinner (once daily) as the maintenance therapy. We recorded demographic characteristics of the patients, fasting state, drugs taken for smoking cessation, and the dosage of the medication. At the first follow-up visit, adverse effects seen with the treatment were recorded. We conducted telephone interviews 6 months after the first visits of the patients to learn the current smoking status of the groups. RESULTS: Of the total 57 patients, 20 (35.1%) were fasting and 37 (64.9%) were not fasting. Fasting and non-fasting patients were similar for sex, age, smoking pack-years, marital status, educational status, and mean Fagerström scores (p >.05). Adverse effects and quit rates after 6 months of follow-up were similar between the fasting and non-fasting groups (p >.05). CONCLUSION: Although our sample size was small, we found no difference in the rates of adverse effects or smoking cessation using a single daily oral dose of bupropion or varenicline between a fasting group and a non-fasting group that received conventional dosing.

Does Short Message Service Increase Adherence to Smoking Cessation Clinic Appointments and Quitting Smoking?

BACKGROUND: Using innovative and scientific methods increases the rate of quitting in smokers. Short message service (SMS) is a communication tool widely used and well integrated in many people's daily lives. To increase adherence to appointments in smoking cessation clinics (SCC), it is thought that increased compliance could be achieved by falling outside the traditional methods. SMS has been shown to increase the compliance of patients with SCC appointments. AIMS: In this study, we aimed to evaluate the effect of SMS in the compliance of patients with SCC follow-up visits and smoking cessation success. STUDY DESIGN: Case-control study. METHODS: Our study was a controlled, open, prospective study. We enrolled 436 cases applied to SCC of Yedikule Training and Research Hospital between 01.10.2013-30.06.2014 and agreed to follow-up with SMS. SMS was sent to the patients to remind them of appointments at the SCC and to query their smoking state. RESULTS: Two hundred-and-eighty seven (65.8%) of the patients were male and 149 (34.2%) were female. The mean age was 45±12 years. In this study, 296 (67.9%) patients had graduated from primary school. Our patients' smoking state was queried by telephone at the 6-month follow-up and we contacted 348 patients. According to this, 88 (25.3%) patients were not smoking, and 260 (74.7%) patients were smokers. Therefore, the smoking cessation rate was 24% (n=60) in patients who did not respond to SMS reminders at all, and 28.6% (n=28) in patients answering any SMS at least once (p=0.377). Smoking cessation rate of the patients invited by SMS but who did not attend any control visits was 19.1%, and it was 34.5% in patients coming to a control visit at least once. This difference was statistically significant (p=0.001). CONCLUSION: In our study, there was increased success of smoking cessation in patients coming to control visits. We think that this may result from the possibly increased compliance to SCC appointments following reminders by SMS, and that this may also increase smoking cessation success.