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Background Previous studies have reported high prognostic accuracy of circulating neurofilament light (NfL) at 24–72 h after out-of-hospital cardiac arrest (OHCA), but performance at earlier time points and after in-hospital cardiac arrest (IHCA) is less investigated. We aimed to assess plasma NfL during the first 48 h after OHCA and IHCA to predict long-term outcomes. Methods Observational multicentre cohort study in adults admitted to intensive care after cardiac arrest. NfL was retrospectively analysed in plasma collected on admission to intensive care, 12 and 48 h after cardiac arrest. The outcome was assessed at two to six months using the Cerebral Performance Category (CPC) scale, where CPC 1–2 was considered a good outcome and CPC 3–5 a poor outcome. Predictive performance was measured with the area under the receiver operating characteristic curve (AUROC). Results Of 428 patients, 328 (77%) suffered OHCA and 100 (23%) IHCA. Poor outcome was found in 68% of OHCA and 55% of IHCA patients. The overall prognostic performance of NfL was excellent at 12 and 48 h after OHCA, with AUROCs of 0.93 and 0.97, respectively. The predictive ability was lower after IHCA than OHCA at 12 and 48 h, with AUROCs of 0.81 and 0.86 ( p  ≤ 0.03). AUROCs on admission were 0.77 and 0.67 after OHCA and IHCA, respectively. At 12 and 48 h after OHCA, high NfL levels predicted poor outcome at 95% specificity with 70 and 89% sensitivity, while low NfL levels predicted good outcome at 95% sensitivity with 71 and 74% specificity and negative predictive values of 86 and 88%. Conclusions The prognostic accuracy of NfL for predicting good and poor outcomes is excellent as early as 12 h after OHCA. NfL is less reliable for the prediction of outcome after IHCA.

Background Biomarkers can be of help to understand critical illness and to identify and stratify sepsis. Adrenomedullin is a vasoactive hormone, with reported prognostic and potentially therapeutic value in sepsis. The primary aim of this study was to investigate the association of circulating bioactive adrenomedullin (bio-ADM) levels at intensive care unit (ICU) admission with mortality in sepsis patients and in a general ICU population. Secondary aims included the association of bio-ADM with organ failure and the ability of bio-ADM to identify sepsis. Methods In this retrospective observational study, adult patients admitted to one of four ICUs during 2016 had admission bio-ADM levels analysed. Age-adjusted odds ratios (OR) with 95% CI for log-2 transformed bio-ADM, and Youden’s index derived cut-offs were calculated. The primary outcome was 30-day mortality, and secondary outcomes included the need for organ support and the ability to identify sepsis. Results Bio-ADM in 1867 consecutive patients were analysed; 632 patients fulfilled the sepsis-3 criteria of whom 267 had septic shock. The median bio-ADM in the entire ICU population was 40 pg/mL, 74 pg/mL in sepsis patients, 107 pg/mL in septic shock and 29 pg/mL in non-septic patients. The association of elevated bio-ADM and mortality in sepsis patients and the ICU population resulted in ORs of 1.23 (95% CI 1.07–1.41) and 1.22 (95% CI 1.12–1.32), respectively. The association with mortality remained after additional adjustment for lactate in sepsis patients. Elevated bio-ADM was associated with an increased need for dialysis with ORs of 2.28 (95% CI 2.01–2.59) and 1.97 (95% CI 1.64–2.36) for the ICU population and sepsis patients, respectively, and with increased need of vasopressors, OR 1.33 (95% CI 1.23–1.42) (95% CI 1.17–1.50) for both populations. Sepsis was identified with an OR of 1.78 (95% CI 1.64–1.94) for bio-ADM, after additional adjustment for severity of disease. A bio-ADM cut-off of 70 pg/mL differentiated between survivors and non-survivors in sepsis, but a Youden’s index derived threshold of 108 pg/mL performed better. Conclusions Admission bio-ADM is associated with 30-day mortality and organ failure in sepsis patients as well as in a general ICU population. Bio-ADM may be a morbidity-independent sepsis biomarker.

Background Our aim was to investigate the prognostic potential of circulating dipeptidyl peptidase 3 (cDPP3) to predict mortality and development of organ dysfunction in a mixed intensive care unit (ICU) population, and for this reason, we analysed prospectively collected admission blood samples from adult ICU patients at four Swedish hospitals. Blood samples were stored in a biobank for later batch analysis. The association of cDPP3 levels with 30-day mortality and Sequential Organ Failure Assessment (SOFA) scores on day two was investigated before and after adjustment for the simplified acute physiology score III (SAPS-3), using multivariable (ordinal) logistic regression. The predictive power of cDPP3 was assessed using the area under the receiver operating characteristic curve (AUROC). Results Of 1978 included consecutive patients in 1 year (2016), 632 fulfilled the sepsis 3-criteria, 190 were admitted after cardiac arrest, and 157 because of trauma. Admission cDPP3 was independently (of SAPS-3) associated with 30-day mortality with odds ratios of 1.45 (95% confidence interval (CI) 1.28–1.64) in the entire ICU population, 1.30 (95% CI 1.08–1.57) in the sepsis subgroup and 2.28 (95% CI 1.50–3.62) in cardiac arrest. For trauma, there was no clear association. Circulating DPP3 alone was a moderate predictor of 30-day mortality with AUROCs of 0.68, 0.62, and 0.72 in the entire group, the sepsis subgroup, and the cardiac arrest subgroup, respectively. By adding cDPP3 to SAPS-3, AUROC improved for the entire group, the sepsis subgroup, and the cardiac arrest subgroup (p = 0.023). Conclusion Circulating DPP3 on admission is a SAPS-3 independent prognostic factor of day-two organ dysfunction and 30-day mortality in a mixed ICU population and needs further evaluation.

BackgroundDefinition of temporal serum proteome profiles after out-of-hospital cardiac arrest may identify biological processes associated with severe hypoxia–ischaemia and reperfusion. It may further explore intervention effects for new mechanistic insights, identify candidate prognostic protein biomarkers and potential therapeutic targets. This pilot study aimed to investigate serum proteome profiles from unconscious patients admitted to hospital after out-of-hospital cardiac arrest according to temperature treatment and neurological outcome.MethodsSerum samples at 24, 48, and 72 h after cardiac arrest at three centres included in the Target Temperature Management after out-of-hospital cardiac arrest trial underwent data-independent acquisition mass spectrometry analysis (DIA-MS) to find changes in serum protein concentrations associated with neurological outcome at 6-month follow-up and targeted temperature management (TTM) at 33 °C as compared to 36 °C. Neurological outcome was defined according to Cerebral Performance Category (CPC) scale as “good” (CPC 1–2, good cerebral performance or moderate disability) or “poor” (CPC 3–5, severe disability, unresponsive wakefulness syndrome, or death).ResultsOf 78 included patients [mean age 66 ± 12 years, 62 (80.0%) male], 37 (47.4%) were randomised to TTM at 36 °C. Six-month outcome was poor in 47 (60.3%) patients. The DIA-MS analysis identified and quantified 403 unique human proteins. Differential protein abundance testing comparing poor to good outcome showed 19 elevated proteins in patients with poor outcome (log2-fold change (FC) range 0.28–1.17) and 16 reduced proteins (log2(FC) between − 0.22 and − 0.68), involved in inflammatory/immune responses and apoptotic signalling pathways for poor outcome and proteolysis for good outcome. Analysis according to level of TTM showed a significant protein abundance difference for six proteins [five elevated proteins in TTM 36 °C (log2(FC) between 0.33 and 0.88), one reduced protein (log2(FC) − 0.6)] mainly involved in inflammatory/immune responses only at 48 h after cardiac arrest.ConclusionsSerum proteome profiling revealed an increase in inflammatory/immune responses and apoptosis in patients with poor outcome. In patients with good outcome, an increase in proteolysis was observed, whereas TTM-level only had a modest effect on the proteome profiles. Further validation of the differentially abundant proteins in response to neurological outcome is necessary to validate novel biomarker candidates that may predict prognosis after cardiac arrest.

BackgroundProenkephalin A 119-159 (penKid) has been suggested as a marker of renal failure and poor outcome. We aimed to investigate the association of penKid on ICU admission with organ dysfunction and mortality in a mixed ICU population. In this retrospective, observational study, admission penKid levels from prospectively collected blood samples of consecutive patients admitted to four Swedish ICUs were analysed. The association of penKid with day-two sequential organ failure assessment (SOFA) scores and 30-day mortality was investigated using (ordinal) logistic regression. The predictive power of penKid for 30-day mortality and dialysis was assessed using the area under the receiver operating characteristic curve (AUC).ResultsOf 1978 included patients, 632 fulfilled the sepsis 3-criteria, 190 had a cardiac arrest, and 157 had experienced trauma. Admission penKid was positively associated with 30-day mortality with an odds ratio of 1.95 (95% confidence interval 1.75–2.18, p < 0.001), and predicted 30-day mortality in the entire ICU population with an AUC of 0.71 (95% confidence interval 0.68–0.73) as well as in the sepsis, cardiac arrest and trauma subgroups (AUCs of 0.61–0.84). Correction for admission plasma creatinine revealed that penKid correlated with neurological dysfunction.ConclusionPlasma penKid on ICU admission is associated with day-two organ dysfunction and predictive of 30-day mortality in a mixed ICU-population, as well as in sepsis, cardiac arrest and trauma subgroups. In addition to being a marker of renal dysfunction, plasma penKid is associated with neurologic dysfunction in the entire ICU population, and cardiovascular dysfunction in sepsis.

Background The purpose was to evaluate glial fibrillary acidic protein (GFAP) and total-tau in plasma as predictors of poor neurological outcome after out-of-hospital (OHCA) and in-hospital cardiac arrest (IHCA), including comparisons with neurofilament light (NFL) and neuron-specific enolase (NSE). Methods Retrospective multicentre observational study of patients admitted to an intensive care unit (ICU) in three hospitals in Sweden 2014–2018. Blood samples were collected at ICU admission, 12 h, and 48 h post-cardiac arrest. Poor neurological outcome was defined as Cerebral Performance Category 3–5 at 2–6 months after cardiac arrest. Plasma samples were retrospectively analysed for GFAP, tau, and NFL. Serum NSE was analysed in clinical care. Prognostic performances were tested with the area under the receiver operating characteristics curve (AUC). Results Of the 428 included patients, 328 were OHCA, and 100 were IHCA. At ICU admission, 12 h and 48 h post-cardiac arrest, GFAP predicted neurological outcome after OHCA with AUC (95% CI) 0.76 (0.70–0.82), 0.86 (0.81–0.90) and 0.91 (0.87–0.96), and after IHCA with AUC (95% CI) 0.77 (0.66–0.87), 0.83 (0.74–0.92) and 0.83 (0.71–0.95). At the same time points, tau predicted outcome after OHCA with AUC (95% CI) 0.72 (0.66–0.79), 0.75 (0.69–0.81), and 0.93 (0.89–0.96) and after IHCA with AUC (95% CI) 0.61 (0.49–0.74), 0.68 (0.56–0.79), and 0.77 (0.65–0.90). Adding the change in biomarker levels between time points did not improve predictive accuracy compared to the last time point. In a subset of patients, GFAP at 12 h and 48 h, as well as tau at 48 h, offered similar predictive value as NSE at 48 h (the earliest time point NSE is recommended in guidelines) after both OHCA and IHCA. The predictive performance of NFL was similar or superior to GFAP and tau at all time points after OHCA and IHCA. Conclusion GFAP and tau are promising biomarkers for neuroprognostication, with the highest predictive performance at 48 h after OHCA, but not superior to NFL. The predictive ability of GFAP may be sufficiently high for clinical use at 12 h after cardiac arrest.

PurposeApplication of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest.MethodsProspective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h ≤ 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey–white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4–6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated.Results140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59–76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90–100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77–0.91) did not significantly differ from manually obtained GWR.ConclusionStandardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.

IntroductionAfter resuscitation from out of hospital cardiac arrest (OHCA), mechanical ventilation (MV) and respiratory management are fundamental to support patients in the intensive care unit (ICU) and to minimise secondary brain injury. Best practices for MV and association with clinical outcomes in patients with OHCA remain unclear.Methods and analysisThis protocol describes a pre-planned respiratory-focused series of sub-analyses within the Sedation, Temperature and Pressure after Cardiac Arrest and Resuscitation (STEPCARE) trial, an ongoing interventional study evaluating 6-month mortality after randomisation in patients admitted to ICUs following OHCA. The primary aim is to describe real-world ventilator settings and gas-exchange targets during the first 72 hours after ICU admission in patients receiving invasive mechanical ventilation after OHCA. Secondary aims include to estimate the incidence of respiratory complications during ICU stay (eg, ventilator-associated pneumonia, acute respiratory distress syndrome, barotrauma); and to explore the association between early ventilator settings/gas-exchange parameters and 6-month outcomes (mortality and neurological status). Exploratory aim is to characterise weaning and extubation practices, including timing and failure rates.Eligible patients will include adult STEPCARE participants receiving invasive MV after return of spontaneous circulation with available respiratory data recorded within the STEPCARE database.Data collected in the STEPCARE trial that will be analysed include patients’ prehospital characteristics; clinical examination at hospital admission and at ICU admission; ventilator settings and arterial blood gases recorded at predefined time points during ICU stay. In particular: MV setting (mode, tidal volume, positive end-expiratory pressure, fraction of inspired oxygen, tidal volume, mechanical power, plateau/driving pressures), gas-exchange values (arterial partial pressure of oxygen and carbon dioxide, pH, arterial saturation of oxygen), timing of measurements and the occurrence/timing of respiratory complications and weaning outcomes.Ethics and disseminationThe STEPCARE study has been approved by the regional ethics committee at Lund University (Dnr 2022-02425-01, Approved IRB on 2022-06-18) and by all ethics boards in the participating countries. No additional ethical approval is required for this predefined secondary analysis, as no further data collection or interventions will be performed. Findings will be disseminated through publication in peer-reviewed journals and, where appropriate, conference abstracts and presentations. Patients and the public were not involved.ClinicalTrials.govNCT05564754.

Background To date, targeted temperature management (TTM) is the only neuroprotective intervention after resuscitation from cardiac arrest that is recommended by guidelines. The evidence on the effects of TTM is unclear. Methods/design The Targeted Hypothermia Versus Targeted Normothermia After Out-of-hospital Cardiac Arrest (TTM2) trial is an international, multicentre, parallel group, investigator-initiated, randomised, superiority trial in which TTM with a target temperature of 33 °C after cardiac arrest will be compared with a strategy to maintain normothermia and active treatment of fever (≥ 37.8 °C). Prognosticators, outcome assessors, the steering group, the trial coordinating team, and trial statisticians will be blinded to treatment allocation. The primary outcome will be all-cause mortality at 180 days after randomisation. We estimate a 55% mortality in the targeted normothermia group. To detect an absolute risk reduction of 7.5% with an alpha of 0.05 and 90% power, 1900 participants will be enrolled. The secondary neurological outcome will be poor functional outcome (modified Rankin scale 4–6) at 180 days after cardiac arrest. In this paper, a detailed statistical analysis plan is presented, including a comprehensive description of the statistical analyses, handling of missing data, and assessments of underlying statistical assumptions. Final analyses will be conducted independently by two qualified statisticians following the present plan. Discussion This SAP, which was prepared before completion of enrolment, should increase the validity of the TTM trial by mitigation of analysis-bias.

Glioblastoma multiform (GBM) is the most common brain tumor characterized by a dismal prognosis. GBM cancer stem cells (gCSC) or tumor-initiating cells are the cell population within the tumor-driving therapy resistance and recurrence. While temozolomide (TMZ), an alkylating agent, constitutes the first-line chemotherapeutic significantly improving survival in GBM patients, resistance against this compound commonly leads to GBM recurrence and treatment failure. Although the roles of protein-coding transcripts, proteins and microRNA in gCSC, and therapy resistance have been comprehensively investigated, very little is known about the role of long noncoding RNAs (lncRNAs) in this context. Using nonoverlapping, independent RNA sequencing and gene expression profiling datasets, we reveal that TP73-AS1 constitutes a clinically relevant lncRNA in GBM. Specifically, we demonstrate significant overexpression of TP73-AS1 in primary GBM samples, which is particularly increased in the gCSC. More importantly, we demonstrate that TP73-AS1 comprises a prognostic biomarker in glioma and in GBM with high expression identifying patients with particularly poor prognosis. Using CRISPRi to downregulate our candidate lncRNA in gCSC, we demonstrate that TP73-AS1 promotes TMZ resistance in gCSC and is linked to regulation of the expression of metabolism- related genes and ALDH1A1, a protein known to be expressed in cancer stem cell markers and protects gCSC from TMZ treatment. Taken together, our results reveal that high TP73-AS1 predicts poor prognosis in primary GBM cohorts and that this lncRNA promotes tumor aggressiveness and TMZ resistance in gCSC.