Background Previous studies have shown that a high body mass index (BMI) is a risk factor for severe COVID-19. The aim of the present study was to assess whether a high BMI affects the risk of death or prolonged length of stay (LOS) in patients with COVID-19 during intensive care in Sweden. Methods and findings In this observational, register-based study, we included patients with COVID-19 from the Swedish Intensive Care Registry admitted to intensive care units (ICUs) in Sweden. Outcomes assessed were death during intensive care and ICU LOS ≥14 days. We used logistic regression models to evaluate the association (odds ratio [OR] and 95% confidence interval [CI]) between BMI and the outcomes. Valid weight and height information could be retrieved in 1,649 patients (1,227 (74.4%) males) with COVID-19. We found a significant association between BMI and the risk of the composite outcome death or LOS ≥14 days in survivors (OR per standard deviation [SD] increase 1.30, 95%CI 1.16–1.44, adjusted for sex, age and comorbidities), and this association remained after further adjustment for severity of illness (simplified acute physiology score; SAPS3) at ICU admission (OR 1.30 per SD, 95%CI 1.17–1.45). Individuals with a BMI ≥ 35 kg/m2 had a doubled risk of the composite outcome. A high BMI was also associated with death during intensive care and a prolonged LOS in survivors assessed as separate outcomes. The main limitations were the restriction to the first wave of the pandemic, and the lack of information on socioeconomic status as well as smoking. Conclusions In this large cohort of Swedish ICU patients with COVID-19, a high BMI was associated with increasing risk of death and prolonged length of stay in the ICU. Based on our findings, we suggest that individuals with obesity should be more closely monitored when hospitalized for COVID-19.

Background There has been in increase in the use of systems for organizing lay responders for suspected out-of-hospital cardiac arrests (OHCAs) dispatch using smartphone-based technology. The purpose is to increase survival rates; however, such systems are dependent on people’s commitment to becoming a lay responder. Knowledge about the characteristics of such volunteers and their motivational factors is lacking. Therefore, we explored characteristics and quantified the underlying motivational factors for joining a smartphone-based cardiopulmonary resuscitation (CPR) lay responder system. Methods In this descriptive cross-sectional study, 800 consecutively recruited lay responders in a smartphone-based mobile positioning first-responder system (SMS-lifesavers) were surveyed. Data on characteristics and motivational factors were collected, the latter through a modified version of the validated survey “Volunteer Motivation Inventory” (VMI). The statements in the VMI, ranked on a Likert scale (1–5), corresponded to(a) intrinsic (an inner belief of doing good for others) or (b) extrinsic (earning some kind of reward from the act) motivational factors. Results A total of 461 participants were included in the final analysis. Among respondents, 59% were women, 48% between 25 and 39 years of age, 37% worked within health care, and 66% had undergone post-secondary school. The most common way (44%) to learn about the lay responder system was from a CPR instructor. A majority (77%) had undergone CPR training at their workplace. In terms of motivation, where higher scores reflect greater importance to the participant, intrinsic factors scored highest, represented by the category values (mean 3.97) followed by extrinsic categories reciprocity (mean 3.88) and self-esteem (mean 3.22). Conclusion This study indicates that motivation to join a first responder system mainly depends on intrinsic factors, i.e. an inner belief of doing good, but there are also extrinsic factors, such as earning some kind of reward from the act, to consider. Focusing information campaigns on intrinsic factors may be the most important factor for successful recruitment. When implementing a smartphone-based lay responder system, CPR instructors, as a main information source to potential lay responders, as well as the workplace, are crucial for successful recruitment.

Background Anoxic‐ischemic brain injury is the most common cause of death after cardiac arrest (CA). Robust methods to detect severe injury with a low false positive rate (FPR) for poor neurological outcome include the pupillary light reflex (PLR) and somatosensory evoked potentials (SSEP). The PLR can be assessed manually or with automated pupillometry which provides the neurological pupil index (NPi). We aim to describe the interrelation between NPi values and the absence of SSEP cortical response and to evaluate the capacity of NPi to predict the absence of cortical SSEP response in comatose patients after CA. Methods A total of 50 patients will be included in an explorative, prospective, observational study of adult (>18 years) comatose survivors of CA admitted to intensive care in a university hospital. NPi assessed with a hand‐held pupillometer will be compared to SSEP signals recorded >48 hours after CA. Primary outcomes are sensitivity, specificity, and odds ratio for NPi to predict bilateral absence of the SSEP N20 signal, with NPi values corresponding to <5% FPRs of SSEP absence. Secondary outcomes are the PLR and SSEP sensitivity, specificity, and odds ratio for poor neurological outcome at hospital discharge and death at 30 days. Discussion The PLR and SSEP may have a systematic interrelation, and a certain NPi threshold could potentially predict the absence of cortical SSEP response. If this can be concluded from the present study, SSEP testing could be excluded in certain patients to save resources in the multimodal prognostication after CA. The interrelation between loss of the pupillary light reflex (PLR) and the loss of cortical response to a somatosensory evoked potential (SSEP) in comatose cardiac arrest patients is not known. This exploratory prospective study is designed to evaluate whether a specific degree of attenuated PLR, as measured by semiautomated pupillometry, can predict the bilateral loss of cortical SSEP response in severe anoxic/ischemic brain injury. Such an interrelation between the two methods would enable the use of pupillometry rather than the more resource demanding SSEP for neurologic prognostication in post cardiac arrest patients. Trial registration ClinicalTrials.gov, NCT04720482, Registered 21 January 2021, retrospectively registered.

Background: Electroencephalography (EEG) patterns are predictive of neurological prognosis in comatose survivors from cardiac arrest but intensive care clinicians are dependent of neurophysiologist reports to identify specific patterns. We hypothesized that the proportion of correct assessment of neurological prognosis would be higher from short statements confirming specific EEG patterns compared with descriptive plain text reports.Methods: Volunteering intensive care clinicians at two university hospitals were asked to assess the neurological prognosis of a fictional patient with high neuron specific enolase. They were presented with 17 authentic plain text reports and three short statements, confirming whether a "highly malignant", "malignant" or "benign" EEG pattern was present. Primary outcome was the proportion of clinicians who correctly identified poor neurological prognosis from reports consistent with highly malignant EEG patterns. Secondary outcomes were how the prognosis was assessed from reports consistent with malignant and benign patterns.Results: Out of 57 participants, poor prognosis was correctly identified by 61% from plain text reports and by 93% from the short statement "highly malignant" EEG patterns. Unaffected prognosis was correctly identified by 28% from plain text reports and by 40% from the short statement "malignant" patterns. Good prognosis was correctly identified by 64% from plain text reports and by 93% from the short statement "benign" pattern. Conclusion:Standardized short statement, "highly malignant EEG pattern present", as compared to plain text EEG descriptions in neurophysiologist reports, is associated with more accurate identification of poor neurological prognosis in comatose survivors of cardiac arrest.

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