Management of Post Traumatic Stress Disorder (PTSD) in Patients’ Relatives and Intensive Care Personnel in a Teaching Hospital

Post-traumatic stress disorder (PTSD) is a condition triggered by the experience of traumatic events and it can lead to long-term difficulties for patients and relatives in regards with their quality of life. There is growing body of evidence regarding the prevalence of PTSD amongst intensive care personnel. We set out to investigate whether there is a need for psychological support for both critically ill patients’ relatives and the intensive care unit (ICU) personnel. Method: A prospective two-stage survey was conducted in the ICU of a teaching hospital in the United Kingdom. Two predefined questionnaires composed of closed and open questions focusing on emotional needs and individual views of psychological support were distributed to Group 1 formed by families members (Group 1A) and ICU personnel (Group 1B) in the surveySupporting Families Emotional Needs, and to Group 2 composed by ICU personnel in the survey Supporting Staff Emotional Needs. Results: There were 77 questionnaires completed. In Group 1 there were 41 questionnaires completed on the “Supporting Families Emotional Needs” survey (16 by Group 1A and 25 by Group 1B members) and in Group 2 there were 36 questionnaires completed on the “Supporting Staff Emotional Needs” survey. Both surveys highlighted the need for a psychological support service. The design of this type of service was also investigated and was formed by opinions of the participants. Conclusion: There is a need for additional emotion support within the ICU. Yet further work is needed to identify strategies in order to provide this support

Perioperative Research into Memory (PRiMe): Cognitive impairment following a severe burn injury and critical care admission, part 1

Introduction An investigation into long-term cognitive impairment and Quality of Life (QoL) after severe burns. Methods A proof of principle, cohort design, prospective, observational clinical study. Patients with severe burns (>15% TBSA) admitted to Burns ICU for invasive ventilation were recruited for psychocognitive assessment with a convenience sample of age and sex-matched controls. Participants completed psychological and QoL questionnaires, the Cogstate® electronic battery, Hopkins Verbal Learning, Verbal Fluency and Trail making tasks. Results 15 patients (11M, 4F; 41 ± 14 years; TBSA 38.4% ± 18.5) and comparators (11M, 4F; 40 ± 13 years) were recruited. Burns patients reported worse QoL (Neuro-QoL Short Form v2, patient 30.1 ± 8.2, control 38.7 ± 3.2, p = 0.0004) and cognitive function (patient composite z-score 0.01, IQR −0.11 to 0.33, control 0.13, IQR 0.47–0.73, p = 0.02). Compared to estimated premorbid FSIQ, patients dropped an equivalent of 8 IQ points (p = 0.002). Cognitive function negatively correlated with burn severity (rBaux score, p = 0.04). QoL strongly correlated with depressive symptoms (Rho = −0.67, p = 0.009) but not cognitive function. Conclusions Severe burns injuries are associated with a significant, global, cognitive deficit. Patients also report worse QoL, depression and post-traumatic stress. Perceived QoL from cognitive impairment was more closely associated with depression than cognitive impairment

Development and implementation of a COVID-19 near real time traffic light system in an acute hospital setting

Common causes of death in COVID-19 due to SARS-CoV-2 include thromboembolic disease, cytokine storm and adult respiratory distress syndrome (ARDS). Our aim was to develop a system for early detection of disease pattern in the emergency department (ED) that would enhance opportunities for personalised accelerated care to prevent disease progression. A single Trust’s COVID-19 response control command was established, and a reporting team with bioinformaticians was deployed to develop a real-time traffic light system to support clinical and operational teams. An attempt was made to identify predictive elements for thromboembolism, cytokine storm and ARDS based on physiological measurements and blood tests, and to communicate to clinicians managing the patient, initially via single consultants. The input variables were age, sex, and first recorded blood pressure, respiratory rate, temperature, heart rate, indices of oxygenation and C-reactive protein. Early admissions were used to refine the predictors used in the traffic lights. Of 923 consecutive patients who tested COVID-19 positive, 592 (64%) flagged at risk for thromboembolism, 241/923 (26%) for cytokine storm and 361/923 (39%) for ARDS. Thromboembolism and cytokine storm flags were met in the ED for 342 (37.1%) patients. Of the 318 (34.5%) patients receiving thromboembolism flags, 49 (5.3% of all patients) were for suspected thromboembolism, 103 (11.1%) were high-risk and 166 (18.0%) were medium-risk. Of the 89 (9.6%) who received a cytokine storm flag from the ED, 18 (2.0% of all patients) were for suspected cytokine storm, 13 (1.4%) were high-risk and 58 (6.3%) were medium-risk. Males were more likely to receive a specific traffic light flag. In conclusion, ED predictors were used to identify high proportions of COVID-19 admissions at risk of clinical deterioration due to severity of disease, enabling accelerated care targeted to those more likely to benefit. Larger prospective studies are encouraged

Increase in COVID-19 inpatient survival following detection of Thromboembolic and Cytokine storm risk from the point of admission to hospital by a near real time Traffic-light System (TraCe-Tic)

Introduction Our goal was to evaluate if traffic-light driven personalized care for COVID-19 was associated with improved survival in acute hospital settings. Methods Discharge outcomes were evaluated before and after prospective implementation of a real-time dashboard with feedback to ward-based clinicians. Thromboembolic categories were “medium-risk” (D-dimer >1000 ng/mL or CRP >200 mg/L); “high-risk” (D-dimer >3000 ng/mL or CRP >250 mg/L) or “suspected” (D-dimer >5000 ng/mL). Cytokine storm risk was categorized by ferritin. Results 939/1039 COVID-19 positive patients (median age 69 years, 563/939 (60%) male) completed hospital encounters to death or discharge by 21st May 2020. Thromboembolic flag criteria were reached by 568/939 (60.4%), including 238/275 (86.6%) of the patients who died, and 330/664 (49.7%) of the patients who survived to discharge, p < 0.0001. Cytokine storm flag criteria were reached by 212 (22.5%) of admissions, including 80/275 (29.0%) of the patients who died, and 132/664 (19.9%) of the patients who survived, p < 0.0001. The maximum thromboembolic flag discriminated completed encounter mortality (no flag: 37/371 [9.97%] died; medium-risk: 68/239 [28.5%]; high-risk: 105/205 [51.2%]; and suspected thromboembolism: 65/124 [52.4%], p < 0.0001). Flag criteria were reached by 535 consecutive COVID-19 positive patients whose hospital encounter completed before traffic-light introduction: 173/535 (32.3% [95% confidence intervals 28.0, 36.0]) died. For the 200 consecutive admissions after implementation of real-time traffic light flags, 46/200 (23.0% [95% confidence intervals 17.1–28.9]) died, p = 0.013. Adjusted for age and sex, the probability of death was 0.33 (95% confidence intervals 0.30–0.37) before traffic light implementation, 0.22 (0.17–0.27) after implementation, p < 0.001. In subgroup analyses, older patients, males, and patients with hypertension (p ≤ 0.01), and/or diabetes (p = 0.05) derived the greatest benefit from admission under the traffic light system. Conclusion Personalized early interventions were associated with a 33% reduction in early mortality. We suggest benefit predominantly resulted from early triggers to review/enhance anticoagulation management, without exposing lower-risk patients to potential risks of full anticoagulation therapy