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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Commonly used methods for both clinical diagnosis of SARS-CoV-2 infection and management of infected patients involve the detection of viral RNA, but the presence of infectious virus particles is unknown. Viability PCR (v-PCR) uses a photoreactive dye to bind non-infectious RNA, ideally resulting in the detection of RNA only from intact virions. This study aimed to develop and validate a rapid v-PCR assay for distinguishing intact and compromised SARS-CoV-2. Propidium monoazide (PMAxx) was used as a photoreactive dye. Mixtures with decreasing percentages of intact SARS-CoV-2 (from 100% to 0%) were prepared from SARS-CoV-2 virus stock and a clinical sample. Each sample was divided into a PMAxx-treated part and a non-PMAxx-treated part. Reverse transcription-PCR (RT-PCR) using an in-house developed SARS-CoV-2 viability assay was then applied to both sample sets. The difference in intact SARS-CoV-2 was determined by subtracting the cycle threshold (Ct) value of the PMAxx-treated sample from the non-PMAxx-treated sample. Mixtures with decreasing concentrations of intact SARS-CoV-2 showed increasingly lower delta Ct values as the percentage of intact SARS-CoV-2 decreased, as expected. This relationship was observed in both high and low viral load samples prepared from cultured SARS-CoV-2 virus stock, as well as for a clinical sample prepared directly from a SARS-CoV-2 positive nasopharyngeal swab. In this study, a rapid v-PCR assay has been validated that can distinguish intact from compromised SARS-CoV-2. The presence of intact virus particles, as determined by v-PCR, may indicate SARS-CoV-2 infectiousness. IMPORTANCE: This study developed a novel method that can help determine whether someone who has been diagnosed with coronavirus disease 2019 (COVID-19) is still capable of spreading the virus to others. Current tests only detect the presence of severe acute res

BACKGROUND: Cerebral perfusion may change depending on arterial cannulation site and may affect the incidence of neurologic adverse events in post-cardiotomy extracorporeal life support (ECLS). The current study compares patients' neurologic outcomes with three commonly used arterial cannulation strategies (aortic vs. subclavian/axillary vs. femoral artery) to evaluate if each ECLS configuration is associated with different rates of neurologic complications. METHODS: This retrospective, multicenter (34 centers), observational study included adults requiring post-cardiotomy ECLS between January 2000 and December 2020 present in the Post-Cardiotomy Extracorporeal Life Support (PELS) Study database. Patients with Aortic, Subclavian/Axillary and Femoral cannulation were compared on the incidence of a composite neurological end-point (ischemic stroke, cerebral hemorrhage, brain edema). Secondary outcomes were overall in-hospital mortality, neurologic complications as cause of in-hospital death, and post-operative minor neurologic complications (seizures). Association between cannulation and neurological outcomes were investigated through linear mixed-effects models. RESULTS: This study included 1897 patients comprising 26.5% Aortic (n = 503), 20.9% Subclavian/Axillary (n = 397) and 52.6% Femoral (n = 997) cannulations. The Subclavian/Axillary group featured a more frequent history of hypertension, smoking, diabetes, previous myocardial infarction, dialysis, peripheral artery disease and previous stroke. Neuro-monitoring was used infrequently in all groups. Major neurologic complications were more frequent in Subclavian/Axillary (Aortic: n = 79, 15.8%; Subclavian/Axillary: n = 78, 19.6%; Femoral: n = 118, 11.9%; p < 0.001) also after mixed-effects model adjustment (OR 1.53 [95% CI 1.02-2.31], p = 0.041). Seizures were more common in Subclavian/Axillary (n = 13, 3.4%) than Aortic (n = 9, 1.8%) and Femoral cannul

Background Extracorporeal membrane oxygenation (ECMO) has been increasingly used for postcardiotomy cardiogenic shock, but without a concomitant reduction in observed in-hospital mortality. Long-term outcomes are unknown. This study describes patients' characteristics, in-hospital outcome, and 10-year survival after postcardiotomy ECMO. Variables associated with in-hospital and postdischarge mortality are investigated and reported. Methods and Results The retrospective international multicenter observational PELS-1 (Postcardiotomy Extracorporeal Life Support) study includes data on adults requiring ECMO for postcardiotomy cardiogenic shock between 2000 and 2020 from 34 centers. Variables associated with mortality were estimated preoperatively, intraoperatively, during ECMO, and after the occurrence of any complications, and then analyzed at different time points during a patient's clinical course, through mixed Cox proportional hazards models containing fixed and random effects. Follow-up was established by institutional chart review or contacting patients. This analysis included 2058 patients (59% were men; median [interquartile range] age, 65.0 [55.0-72.0] years). In-hospital mortality was 60.5%. Independent variables associated with in-hospital mortality were age (hazard ratio [HR], 1.02 [95% CI, 1.01-1.02]) and preoperative cardiac arrest (HR, 1.41 [95% CI, 1.15-1.73]). In the subgroup of hospital survivors, the overall 1-, 2-, 5-, and 10-year survival rates were 89.5% (95% CI, 87.0%-92.0%), 85.4% (95% CI, 82.5%-88.3%), 76.4% (95% CI, 72.5%-80.5%), and 65.9% (95% CI, 60.3%-72.0%), respectively. Variables associated with postdischarge mortality included older age, atrial fibrillation, emergency surgery, type of surgery, postoperative acute kidney injury, and postoperative septic shock. Conclusions In adults, in-hospital mortality after postcardiotomy ECMO remains high; however, two-thirds of those who are discharged from hospital survive up to 10 years. Patien

Background:High-quality evidence for post-cardiotomy extracorporeal life support (PC-ECLS) management is lacking. This study investigated real-world PC-ECLS clinical practices. Methods: This cross-sectional, multi-institutional, international pilot survey explored center organization, anticoagulation management, left ventricular unloading, distal limb perfusion, PC-ECLS monitoring, and transfusion practices. Twenty-nine questions were distributed among 34 hospitals participating in the Post-cardiotomy Extra-Corporeal Life Support Study. Results: Of the 32 centers [16 low-volume (50%); 16 high-volume (50%)] that responded, 16 (50%) had dedicated ECLS specialists. Twenty-six centers (81.3%) reported using additional mechanical circulatory supports. Anticoagulation practices were highly heterogeneous: 24 hospitals (75%) reported using patients bleeding status as a guide, without a specific threshold in 54.2% of cases. Transfusion targets ranged from 7 to 10 g/dL. Most centers used cardiac venting on a case-by-case basis (78.1%) and regular distal limb perfusion (84.4%). Nineteen (54.9%) centers reported dedicated monitoring protocols, including daily echocardiography (87.5%), Swan-Ganz catheterization (40.6%), cerebral near-infrared spectroscopy (53.1%), and multimodal assessment of limb ischemia. Inspection of the circuit (71.9%), oxygenator pressure drop (68.8%), plasma free hemoglobin (75%), d-dimer (59.4%), lactate dehydrogenase (56.3%), and fibrinogen (46.9%) are used to diagnose hemolysis and thrombosis. Conclusions: This study shows remarkable heterogeneity in clinical practices for PC-ECLS management. More standardized protocols and better implementation of the available evidence are recommended.

Objectives: Postcardiotomy extracorporeal membrane oxygenation (ECMO) can be initiated intraoperatively or postoperatively based on indications, settings, patient profile, and conditions. The topic of implantation timing only recently gained attention from the clinical community. We compare patient characteristics as well as in-hospital and long-term survival between intraoperative and postoperative ECMO.Methods: The retrospective, multicenter, observational Postcardiotomy Extracorporeal Life Support (PELS-1) study includes adults who required ECMO due to postcardiotomy shock between 2000 and 2020. We compared patients who received ECMO in the operating theater (intraoperative) with those in the intensive care unit (postoperative) on in-hospital and postdischarge outcomes. Results: We studied 2003 patients (women: 41.1%; median age: 65 years; interquartile range [IQR], 55.0-72.0). Intraoperative ECMO patients (n = 1287) compared with postoperative ECMO patients (n = 716) had worse preoperative risk profiles. Cardiogenic shock (45.3%), right ventricular failure (15.9%), and cardiac arrest (14.3%) were the main indications for postoperative ECMO initiation, with cannulation occurring after (median) 1 day (IQR, 1-3 days). Compared with intraoperative application, patients who received postoperative ECMO showed more complications, cardiac reoperations (intraoperative: 19.7%; postoperative: 24.8%, P = .011), percutaneous coronary interventions (intraoperative: 1.8%; postoperative: 3.6%, P = .026), and had greater in-hospital mortality (intraoperative: 57.5%; postoperative: 64.5%, P = .002). Among hospital survivors, ECMO duration was shorter after intraoperative ECMO (median, 104; IQR, 67.8-164.2 hours) compared with postoperative ECMO (median, 139.7; IQR, 95.8-192 hours, P < .001), whereas postdischarge long-term survival was similar between the 2 groups (P = .86). Conclusions: Intraopera

Sharing healthcare data is increasingly essential for developing data-driven improvements in patient care at the Intensive Care Unit (ICU). However, it is also very challenging under the strict privacy legislation of the European Union (EU). Therefore, we explored four successful open ICU healthcare databases to determine how open healthcare data can be shared appropriately in the EU. A questionnaire was constructed based on the Delphi method. Then, follow-up questions were discussed with experts from the four databases. These experts encountered similar challenges and regarded ethical and legal aspects to be the most challenging. Based on the approaches of the databases, expert opinion, and literature research, we outline four distinct approaches to openly sharing healthcare data, each with varying implications regarding data security, ease of use, sustainability, and implementability. Ultimately, we formulate seven recommendations for sharing open healthcare data to guide future initiatives in sharing open healthcare data to improve patient care and advance healthcare.

Objectives: Extracorporeal membrane oxygenation (ECMO) for postcardiotomy cardiogenic shock has been increasingly used without concomitant mortality reduction. This study aims to investigate determinants of in-hospital and postdischarge mortality in patients requiring postcardiotomy ECMO in the Netherlands. Methods: The Netherlands Heart Registration collects nationwide prospective data from cardiac surgery units. Adults receiving intraoperative or postoperative ECMO included in the register from January 2013 to December 2019 were studied. Survival status was established through the national Personal Records Database. Multivariable logistic regression analyses were used to investigate determinants of in-hospital (3 models) and 12-month postdischarge mortality (4 models). Each model was developed to target specific time points during a patient's clinical course. Results: Overall, 406 patients (67.2% men, median age, 66.0 years [interquartile range, 55.0-72.0 years]) were included. In-hospital mortality was 51.7%, with death occurring in a median of 5 days (interquartile range, 2-14 days) after surgery. Hospital survivors (n = 196) experienced considerable rates of pulmonary infections, respiratory failure, arrhythmias, and deep sternal wound infections during a hospitalization of median 29 days (interquartile range, 17-51 days). Older age (odds ratio [OR], 1.02; 95% CI, 1.0-1.04) and preoperative higher body mass index (OR, 1.08; 95% CI, 1.02-1.14) were associated with in-hospital death. Within 12 months after discharge, 35.1% of hospital survivors (n = 63) died. Postoperative renal failure (OR, 2.3; 95% CI, 1.6-4.9), respiratory failure (OR, 3.6; 95% CI, 1.3-9.9), and re-thoracotomy (OR, 2.9; 95% CI, 1.3-6.5) were associated with 12-month postdischarge mortality. Conclusions: In-hospital and postdischarge mortality after postcardiotomy ECMO in adults remains high in the Netherlands. ECMO support in patients with higher age and body mass index, which drive associa

OBJECTIVES: In a recent scoping review, we identified 43 mortality prediction models for critically ill patients. We aimed to assess the performances of these models through external validation. DESIGN: Multicenter study. SETTING: External validation of models was performed in the Simple Intensive Care Studies-I (SICS-I) and the Finnish Acute Kidney Injury (FINNAKI) study. PATIENTS: The SICS-I study consisted of 1,075 patients, and the FINNAKI study consisted of 2,901 critically ill patients. MEASUREMENTS AND MAIN RESULTS: For each model, we assessed: 1) the original publications for the data needed for model reconstruction, 2) availability of the variables, 3) model performance in two independent cohorts, and 4) the effects of recalibration on model performance. The models were recalibrated using data of the SICS-I and subsequently validated using data of the FINNAKI study. We evaluated overall model performance using various indexes, including the (scaled) Brier score, discrimination (area under the curve of the receiver operating characteristics), calibration (intercepts and slopes), and decision curves. Eleven models (26%) could be externally validated. The Acute Physiology And Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS)-Reduced (SAPS-R)‚ and Simplified Mortality Score for the ICU models showed the best scaled Brier scores of 0.11‚ 0.10‚ 0.10‚ and 0.06‚ respectively. SAPS II, APACHE II, and APACHE IV discriminated best; overall discrimination of models ranged from area under the curve of the receiver operating characteristics of 0.63 (0.61–0.66) to 0.83 (0.81–0.85). We observed poor calibration in most models, which improved to at least moderate after recalibration of intercepts and slopes. The decision curve showed a positive net benefit in the 0–60% threshold probability range for APACHE IV and SAPS-R. CONCLUSIONS: In only 11 out of 43 avai, OBJECTIVES: In a recent scoping review, we identified 43 mortality prediction models for critically ill patients. We aimed to assess the performances of these models through external validation. DESIGN: Multicenter study. SETTING: External validation of models was performed in the Simple Intensive Care Studies-I (SICS-I) and the Finnish Acute Kidney Injury (FINNAKI) study. PATIENTS: The SICS-I study consisted of 1,075 patients, and the FINNAKI study consisted of 2,901 critically ill patients. MEASUREMENTS AND MAIN RESULTS: For each model, we assessed: 1) the original publications for the data needed for model reconstruction, 2) availability of the variables, 3) model performance in two independent cohorts, and 4) the effects of recalibration on model performance. The models were recalibrated using data of the SICS-I and subsequently validated using data of the FINNAKI study. We evaluated overall model performance using various indexes, including the (scaled) Brier score, discrimination (area under the curve of the receiver operating characteristics), calibration (intercepts and slopes), and decision curves. Eleven models (26%) could be externally validated. The Acute Physiology And Chronic Health Evaluation (APACHE) II, APACHE IV, Simplified Acute Physiology Score (SAPS)-Reduced (SAPS-R)‚ and Simplified Mortality Score for the ICU models showed the best scaled Brier scores of 0.11‚ 0.10‚ 0.10‚ and 0.06‚ respectively. SAPS II, APACHE II, and APACHE IV discriminated best; overall discrimination of models ranged from area under the curve of the receiver operating characteristics of 0.63 (0.61-0.66) to 0.83 (0.81-0.85). We observed poor calibration in most models, which improved to at least moderate after recalibration of intercepts and slopes. The decision curve showed a positive net benefit in the 0-60% threshold probability range for APACHE IV and SAPS-R. CONCLUSIONS: In only 11 out of 43 available mortality prediction models, the performance could be studied usin

Background Recognising patients who need immediate hospital treatment for sepsis while simultaneously limiting unnecessary referrals is challenging for GPs.Aim To develop and validate a sepsis prediction model for adult patients in primary care.Design and setting This was a prospective cohort study in four out-of-hours primary care services in the Netherlands, conducted between June 2018 and March 2020.Method Adult patients who were acutely ill and received home visits were included. A total of nine clinical variables were selected as candidate predictors, next to the biomarkers C-reactive protein, procalcitonin, and lactate. The primary endpoint was sepsis within 72 hours of inclusion, as established by an expert panel. Multivariable logistic regression with backwards selection was used to design an optimal model with continuous clinical variables. The added value of the biomarkers was evaluated. Subsequently, a simple model using single cut-off points of continuous variables was developed and externally validated in two emergency department populations.Results A total of 357 patients were included with a median age of 80 years (interquartile range 71–86), of which 151 (42%) were diagnosed with sepsis. A model based on a simple count of one point for each of six variables (aged >65 years; temperature >38°C; systolic blood pressure ≤110 mmHg; heart rate >110/min; saturation ≤95%; and altered mental status) had good discrimination and calibration (C-statistic of 0.80 [95% confidence interval = 0.75 to 0.84]; Brier score 0.175). Biomarkers did not improve the performance of the model and were therefore not included. The model was robust during external validation.Conclusion Based on this study’s GP out-of-hours population, a simple model can accurately predict sepsis in acutely ill adult patients using readily available clinical parameters.

INTRODUCTION: The variety, time patterns and long-term prognosis of persistent COVID-19 symptoms (long COVID-19) in patients who suffered from mild to severe acute COVID-19 are incompletely understood. Cohort studies will be combined to describe the prevalence of long COVID-19 symptoms, and to explore the pathophysiological mechanisms and impact on health-related quality of life. A prediction model for long COVID-19 will be developed and internally validated to guide care in future patients. METHODS AND ANALYSIS: Data from seven COVID-19 cohorts will be aggregated in the longitudinal multiple cohort CORona Follow Up (CORFU) study. CORFU includes Dutch patients who suffered from COVID-19 at home, were hospitalised without or with intensive care unit treatment, needed inpatient or outpatient rehabilitation and controls who did not suffer from COVID-19. Individual cohort study designs were aligned and follow-up has been synchronised. Cohort participants will be followed up for a maximum of 24 months after acute infection. Next to the clinical characteristics measured in individual cohorts, the CORFU questionnaire on long COVID-19 outcomes and determinants will be administered digitally at 3, 6, 12, 18 and 24 months after the infection. The primary outcome is the prevalence of long COVID-19 symptoms up to 2 years after acute infection. Secondary outcomes are health-related quality of life (eg, EQ-5D), physical functioning, and the prevalence of thromboembolic complications, respiratory complications, cardiovascular diseases and endothelial dysfunction. A prediction model and a patient platform prototype will be developed. ETHICS AND DISSEMINATION: Approval was obtained from the medical research ethics committee of Maastricht University Medical Center+ and Maastricht University (METC 2021-2990) and local committees of the participating cohorts. The project is supported by ZonMW and EuroQol Research Foundation. Results will be published in open access peer-reviewed sci