IntroductionPostoperative delirium is a common complication of cardiac surgery associated with increased mortality, morbidity, and long-term cognitive dysfunction. The aim of this study was to identify incidence and risk factors of delirium in elderly (≥65 years) and very elderly (≥80 years) patients undergoing major cardiac surgery.Materials and methodsWe performed a retrospective cohort analysis of prospectively collected data from a register of the cardiac surgery department of a tertiary referral university hospital between 2014 and 2016. Analysis was performed in two groups, ≥65 years and ≥80 years.ResultsWe analyzed 1,797 patients ≥65 years, including 230 (7.24%) patients ≥80 years. Delirium was diagnosed in 21.4% (384/1,797) of patients above 65 years, and in 33.5% (77/230) of octogenarians. Early mortality did not differ between patients with and without delirium. Intensive care unit (ICU) stay (p<0.001), hospital stay (p<0.001), and intubation time (p=0.002) were significantly longer in patients undergoing cardiac surgery ≥65 years with delirium. According to multivariable analysis, <65 years, age (odds ratio [OR] 1.036, p=0.002), low ejection fraction (OR 1.634, p=0.035), diabetes (1.346, p=0.019), and extracardiac arteriopathy (OR 1.564, p=0.007) were found to be independent predictors of post-cardiac surgery delirium. Postoperative risk factors for developing delirium ≥65 years were atrial fibrillation (1.563, p=0.001), postoperative pneumonia (OR 1.896, p=0.022), elevated postoperative creatinine (OR 1.384, p=0.004), and prolonged hospitalization (OR 1.019, p=0.009).ConclusionPatients above 65 years of age with postoperative delirium have poorer outcome and are more likely to have prolonged hospitalization and ICU stay, and longer intubation times, but 30-day mortality is not increased. In our study, eight independent risk factors for development of post-cardiac surgery delirium were age, low ejection fraction, diabetes, extracardiac arteriopathy, postoperative atrial fibrillation, pneumonia, elevated creatinine, and prolonged hospitalization time.

It seems that the medical personnel in contact with patients infected with SARS-CoV-2 are at an especially high risk of adverse psychological effects. Therefore, the aim of this study was to assess the mental health factors among healthcare workers by quantifying the severity of anxiety, depression, and sleep disorders during the current SARS-CoV-2 pandemic, while taking into account coexisting diseases. The study involved 441 healthcare professionals including 206 healthcare workers at emergency wards, infectious wards, and intensive care units. The control group consisted of 235 healthcare workers working in wards other than those where individuals from the study group worked. Regression adjusted by age, gender, the occurrence of hypertension, diabetes mellitus, dyslipidemia, asthma, autoimmune diseases, and cigarette smoking showed the elevated risk of anxiety on the Generalized Anxiety Disorder (GAD-7) scale (OR = 1.934; p < 0.001), depression on the Patient Health Questionnaire (PHQ-9) scale (OR = 2.623; p < 0.001), and sleep disorders on the Insomnia Severity Index (ISI) scale (OR = 3.078; p < 0.001). Our study showed that healthcare workers who are exposed to SARS-CoV-2-infected patients at emergency wards, infectious wards, and intensive care units are at a much higher risk of showing symptoms of anxiety, depression, and sleep disorders than healthcare workers working in other wards.

Introduction: Postoperative delirium (POD) is associated with unfavorable outcomes. It may result from neuroinflammation and oxidative stress. The aim of this study was to evaluate the role of routinely available inflammatory markers derived from white blood cell count (WBC), for prognostic value in diagnosing delirium after cardiac surgery. Methods: We performed an analysis of data collected from patients undergoing planned coronary artery bypass grafting (CABG). Differential WBC and CRP (C-reactive protein) concentration were evaluated preoperatively (T0) and postoperatively at day 1 (T1), 3 (T3), 5 (T5) after CABG. Differences in neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and platelet-to-WBC ratio (PWR) between patients with (Del +) and without delirium (Del −) were evaluated. Patients were screened using CAM-ICU. Results: We included 968 patients in the study. Incidence of delirium was 13.3%. In the group with POD, the majority of patients were men (87/129, 67.44%), and the mean age was 72 years. Preoperative WBC (8.21 ± 3.04 G/l vs. 7.55 ± 1.86 G/l, p = 0.029) were higher and mean platelet count was lower (217.7 ± 69.07 G/l vs. 227.44 ± 59.31 G/l, p = 0.031) in patients with POD. Lower pre-operative PLR values (109.87 ± 46.38 vs. 120.36 ± 52.98, p = 0.026) and PWR values (27.69 ± 7.50 vs. 31.32 ± 9.88 p < 0.001) were found in patients with POD. Association was strongest for PWR and remained significant at T1 (p < 0.001), T3 (p < 0.001) and T5 (p < 0.001). Basing on coefficients of logistic regression a model for optimal prediction of POD was calculated: CARDEL Index (CARdiac DELirium Index) = 0.108 × Age + 0.341 × HBA1C − 0.049 × PWR with AUC of 0.742 (p < 0.001). Conclusions: The results of this study show that lower pre-operative levels of PLR and PWR were associated with POD after cardiac surgery. Pre-operative PWR showed strongest correlation with POD and may be a potential new biomarker associated with postoperative delirium. CARDEL prognosis index composed of age, HbA1c and PWR is good at predicting development of delirium after CABG.

Delirium is an acute brain disorder that commonly occurs in patients with acute ischemic stroke (AIS). Pathomechanism of delirium is related to the neuroinflammatory process and oxidative stress. Search for readily available diagnostic marker that will aid clinicians in early identification of delirium is ongoing. The aim of this study was to investigate whether neutrophil-to-lymphocyte ratio (NLR) could serve as a potential marker for delirium prediction in patients with AIS and to find an easy diagnostic tool using laboratory and clinical parameters to predict delirium. Prospective observational study (NCT03944694) included patients with AIS admitted to the neurology department of a district general hospital. All patients were screened for delirium using CAM-ICU (Confusion Assessment Method for Intensive Care Unit). Demographic and medical history data and admission lab results, including differential white blood cell analysis, were collected from all patients. We included 1001 patients in the final analysis. The mean age of the sample was 71 years, and 52% of patients were males. The incidence of early-onset delirium was 17.2%. The NLR was elevated in delirious patients (6.39 ± 8.60 vs. 4.61 ± 5.61, p < 0.001). The best cut-off value of NLR to predict delirium using the receiver operating characteristics (ROC) was determined at 4.86. Multivariable logistic regression analysis showed that the odds ratio (OR) for developing delirium with NLR > 4.86 (adjusted for age, sex, body mass index (BMI), comorbidities, and baseline neurology) was 1.875 (95% CI 1.314–2.675, p = 0.001). As a result of different combinations of markers and clinical parameters based on logistic regression, a formula—DELirium in Acute Ischemic Stroke (DELIAS score)—was obtained with the area under the ROC curve of 0.801 (p < 0.001). After regression of the cut-off points of the obtained curve, a significant correlation of the DELIAS score was observed with the occurrence of early-onset delirium (OR = 8.976, p < 0.001) and with delirium until the fifth day after AIS (OR = 7.744, p < 0.001). In conclusion, NLR can be regarded as a potential marker for prediction of early-onset delirium after AIS. On the basis of combined laboratory and clinical parameters, the DELIAS score was calculated, which gave the highest predictive value for delirium in the analyzed group of patients after ischemic stroke. However, further studies are needed to validate these findings.

BackgroundVirtual reality (VR) training using modern game consoles is an innovative rehabilitation method for fall-prone elderly people. The aim of this study was to assess the effectiveness of VR training using the “Xbox 360 Kinect” in people over 60 years of age.Materials and methodsThe study involved 23 people, including 19 women and 4 men (mean age 75.74±8.09 years). The following functional tests were employed as research instruments: the 6-minute walking test (6MWT), the Dynamic Gait Index (DGI), the tandem stance test (TST), the tandem walk test (TWT), and the Beck Depression Inventory (BDI). A “spring hand dynamometer” was also used. The participants underwent 30-day VR training using an Xbox 360 Kinect. They trained 3 times a week, with each exercise lasting 30 minutes.ResultsThe 6MWT (P<0.001), the DGI (P=0.008), the TST (P<0.001), the TWT (P=0.002), and the BDI (P<0.001) outcomes were significantly improved. There were differences in the results for the strength of the “pressing muscles” in the right (P=0.106) and left (P=0.043) hands of the participants. Both participants under 80 years of age and those aged 80 years and over had visibly better results on the 6MWT (P<0.001 and P=0.008, respectively), the TST (P<0.001 and P=0.008, respectively), and the BDI (P=0.003 and P=0.012, respectively).ConclusionTraining based on VR increases the possibilities of motor training and can help reduce the risk of falls by improving the static and dynamic balance.