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  • 1
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    Anti-C5a antibody IFX-1 (vilobelimab) treatment versus best supportive care for patients with severe COVID-19 (PANAMO): an exploratory, open-label, phase 2 randomised controlled trial
    Elsevier BV ; 2020
    In:  The Lancet Rheumatology Vol. 2, No. 12 ( 2020-12), p. e764-e773
    Details
    In: The Lancet Rheumatology, Elsevier BV, Vol. 2, No. 12 ( 2020-12), p. e764-e773
    Type of Medium: Online Resource
    ISSN: 2665-9913
    URL: Article
    DOI: 10.1016/S2665-9913(20)30341-6
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
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  • 2
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    Better COVID-19 Intensive Care Unit survival in females, independent of age, disease severity, comorbidities, and treatment
    Springer Science and Business Media LLC ; 2022
    In:  Scientific Reports Vol. 12, No. 1 ( 2022-01-14)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2022-01-14)
    Abstract: Although male Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) patients have higher Intensive Care Unit (ICU) admission rates and a worse disease course, a comprehensive analysis of female and male ICU survival and underlying factors such as comorbidities, risk factors, and/or anti-infection/inflammatory therapy administration is currently lacking. Therefore, we investigated the association between sex and ICU survival, adjusting for these and other variables. In this multicenter observational cohort study, all patients with SARS-CoV-2 pneumonia admitted to seven ICUs in one region across Belgium, The Netherlands, and Germany, and requiring vital organ support during the first pandemic wave were included. With a random intercept for a center, mixed-effects logistic regression was used to investigate the association between sex and ICU survival. Models were adjusted for age, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, comorbidities, and anti-infection/inflammatory therapy. Interaction terms were added to investigate effect modifications by sex with country and sex with obesity. A total of 551 patients (29% were females) were included. Mean age was 65.4 ± 11.2 years. Females were more often obese and smoked less frequently than males (p-value 0.001 and 0.042, respectively). APACHE II scores of females and males were comparable. Overall, ICU mortality was 12% lower in females than males (27% vs 39% respectively, p-value  〈  0.01) with an odds ratio (OR) of 0.62 (95%CI 0.39–0.96, p-value 0.032) after adjustment for age and APACHE II score, 0.63 (95%CI 0.40–0.99, p-value 0.044) after additional adjustment for comorbidities, and 0.63 (95%CI 0.39–0.99, p-value 0.047) after adjustment for anti-infection/inflammatory therapy. No effect modifications by sex with country and sex with obesity were found (p-values for interaction  〉  0.23 and 0.84, respectively). ICU survival in female SARS-CoV-2 patients was higher than in male patients, independent of age, disease severity, smoking, obesity, comorbidities, anti-infection/inflammatory therapy, and country. Sex-specific biological mechanisms may play a role, emphasizing the need to address diversity, such as more sex-specific prediction, prognostic, and therapeutic approach strategies.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-021-04531-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2615211-3
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  • 3
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    Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort (MaastrICCht)
    BMJ ; 2020
    In:  BMJ Open Vol. 10, No. 9 ( 2020-09), p. e040175-
    Details
    In: BMJ Open, BMJ, Vol. 10, No. 9 ( 2020-09), p. e040175-
    Abstract: The course of the disease in SARS-CoV-2 infection in mechanically ventilated patients is unknown. To unravel the clinical heterogeneity of the SARS-CoV-2 infection in these patients, we designed the prospective observational Maastricht Intensive Care COVID cohort (MaastrICCht). We incorporated serial measurements that harbour aetiological, diagnostic and predictive information. The study aims to investigate the heterogeneity of the natural course of critically ill patients with a SARS-CoV-2 infection. Methods and analysis Mechanically ventilated patients admitted to the intensive care with a SARS-CoV-2 infection will be included. We will collect clinical variables, vital parameters, laboratory variables, mechanical ventilator settings, chest electrical impedance tomography, ECGs, echocardiography as well as other imaging modalities to assess heterogeneity of the course of a SARS-CoV-2 infection in critically ill patients. The MaastrICCht is also designed to foster various other studies and registries and intends to create an open-source database for investigators. Therefore, a major part of the data collection is aligned with an existing national intensive care data registry and two international COVID-19 data collection initiatives. Additionally, we create a flexible design, so that additional measures can be added during the ongoing study based on new knowledge obtained from the rapidly growing body of evidence. The spread of the COVID-19 pandemic requires the swift implementation of observational research to unravel heterogeneity of the natural course of the disease of SARS-CoV-2 infection in mechanically ventilated patients. Our study design is expected to enhance aetiological, diagnostic and prognostic understanding of the disease. This paper describes the design of the MaastrICCht. Ethics and dissemination Ethical approval has been obtained from the medical ethics committee (Medisch Ethische Toetsingscommissie 2020-1565/3 00 523) of the Maastricht University Medical Centre+ (Maastricht UMC+), which will be performed based on the Declaration of Helsinki. During the pandemic, the board of directors of Maastricht UMC+ adopted a policy to inform patients and ask their consent to use the collected data and to store serum samples for COVID-19 research purposes. All study documentation will be stored securely for fifteen years after recruitment of the last patient. The results will be published in peer-reviewed academic journals, with a preference for open access journals, while particularly considering deposition of the manuscripts on a preprint server early. Trial registration number The Netherlands Trial Register (NL8613).
    Type of Medium: Online Resource
    ISSN: 2044-6055 , 2044-6055
    URL: Article
    DOI: 10.1136/bmjopen-2020-040175
    Language: English
    Publisher: BMJ
    Publication Date: 2020
    detail.hit.zdb_id: 2599832-8
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  • 4
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    Pulmonary pathophysiology development of COVID-19 assessed by serial Electrical Impedance Tomography in the MaastrICCht cohort
    Springer Science and Business Media LLC ; 2022
    In:  Scientific Reports Vol. 12, No. 1 ( 2022-08-25)
    Details
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2022-08-25)
    Abstract: Patients with SARS-CoV-2 infection present with different lung compliance and progression of disease differs. Measures of lung mechanics in SARS-CoV-2 patients may unravel different pathophysiologic mechanisms during mechanical ventilation. The objective of this prospective observational study is to describe whether Electrical Impedance Tomography (EIT) guided positive end-expiratory pressure (PEEP) levels unravel changes in EIT-derived parameters over time and whether the changes differ between survivors and non-survivors. Serial EIT-measurements of alveolar overdistension, collapse, and compliance change in ventilated SARS-CoV-2 patients were analysed. In 80 out of 94 patients, we took 283 EIT measurements (93 from day 1–3 after intubation, 66 from day 4–6, and 124 from day 7 and beyond). Fifty-one patients (64%) survived the ICU. At admission mean PaO 2 /FiO 2 -ratio was 184.3 (SD 61.4) vs. 151.3 (SD 54.4) mmHg, ( p  = 0.017) and PEEP was 11.8 (SD 2.8) cmH 2 O vs. 11.3 (SD 3.4) cmH 2 O, ( p  = 0.475), for ICU survivors and non-survivors. At day 1–3, compliance was ~ 55 mL/cmH 2 O vs. ~ 45 mL/cmH 2 O in survivors vs. non-survivors. The intersection of overdistension and collapse curves appeared similar at a PEEP of ~ 12–13 cmH 2 O. At day 4–6 compliance changed to ~ 50 mL/cmH 2 O vs. ~ 38 mL/cmH 2 O. At day 7 and beyond, compliance was ~ 38 mL/cmH 2 O with the intersection at a PEEP of ~ 9 cmH 2 O vs. ~ 25 mL/cmH 2 O with overdistension intersecting at collapse curves at a PEEP of ~ 7 cmH 2 O. Surviving SARS-CoV-2 patients show more favourable EIT-derived parameters and a higher compliance compared to non-survivors over time. This knowledge is valuable for discovering the different groups.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    URL: Article
    DOI: 10.1038/s41598-022-18843-z
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2615211-3
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  • 5
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    Trends in Early and Late Mortality in Patients With Severe Acute Pancreatitis Admitted to ICUs: A Nationwide Cohort Study
    Ovid Technologies (Wolters Kluwer Health) ; 2022
    In:  Critical Care Medicine Vol. 50, No. 10 ( 2022-10), p. 1513-1521
    Details
    In: Critical Care Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 50, No. 10 ( 2022-10), p. 1513-1521
    Abstract: To investigate national mortality trends over a 12-year period for patients with severe acute pancreatitis (SAP) admitted to Dutch ICUs. Additionally, an assessment of outcome in SAP was undertaken to differentiate between early ( 〈 14 d of ICU admission) and late ( 〉 14 d of ICU admission) mortality. DESIGN: Data from the Dutch National Intensive Care Evaluation and health insurance companies’ databases were extracted. Outcomes included 14-day, ICU, hospital, and 1-year mortality. Mortality before and after 2010 was compared using mixed logistic regression and mixed Cox proportional-hazards models. Sensitivity analyses, excluding early mortality, were performed to assess trends in late mortality. SETTING: Not applicable. PATIENTS: Consecutive adult patients with SAP admitted to all 81 Dutch ICUs between 2007 and 2018. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: Among 4,160 patients treated in 81 ICUs, 14-day mortality was 17%, ICU mortality 17%, hospital mortality 23%, and 1-year mortality 33%. After 2010 in-hospital mortality adjusted for age, sex, modified Marshall, and Acute Physiology and Chronic Health Evaluation III scores were lower (odds ratio [OR], 0.76; 95% CI, 0.61–0.94) than before 2010. There was no change in ICU and 1-year mortality. Sensitivity analyses excluding patients with early mortality demonstrated a decreased ICU mortality (OR, 0.45; 95% CI, 0.32–0.64), decreased in-hospital (OR, 0.48; 95% CI, 0.36–0.63), and decreased 1-year mortality (hazard ratio, 0.81; 95% CI, 0.68–0.96) after 2010 compared with 2007–2010. CONCLUSIONS: Over the 12-year period examined, mortality in patients with SAP admitted to Dutch ICUs did not change, although after 2010 late mortality decreased. Novel therapies should focus on preventing early mortality in SAP.
    Type of Medium: Online Resource
    ISSN: 0090-3493
    URL: Article
    DOI: 10.1097/CCM.0000000000005629
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2022
    detail.hit.zdb_id: 2034247-0
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  • 6
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    Predicting mortality of individual patients with COVID-19: a multicentre Dutch cohort
    BMJ ; 2021
    In:  BMJ Open Vol. 11, No. 7 ( 2021-07), p. e047347-
    Details
    In: BMJ Open, BMJ, Vol. 11, No. 7 ( 2021-07), p. e047347-
    Abstract: Develop and validate models that predict mortality of patients diagnosed with COVID-19 admitted to the hospital. Design Retrospective cohort study. Setting A multicentre cohort across 10 Dutch hospitals including patients from 27 February to 8 June 2020. Participants SARS-CoV-2 positive patients (age ≥18) admitted to the hospital. Main outcome measures 21-day all-cause mortality evaluated by the area under the receiver operator curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The predictive value of age was explored by comparison with age-based rules used in practice and by excluding age from the analysis. Results 2273 patients were included, of whom 516 had died or discharged to palliative care within 21 days after admission. Five feature sets, including premorbid, clinical presentation and laboratory and radiology values, were derived from 80 features. Additionally, an Analysis of Variance (ANOVA)-based data-driven feature selection selected the 10 features with the highest F values: age, number of home medications, urea nitrogen, lactate dehydrogenase, albumin, oxygen saturation (%), oxygen saturation is measured on room air, oxygen saturation is measured on oxygen therapy, blood gas pH and history of chronic cardiac disease. A linear logistic regression and non-linear tree-based gradient boosting algorithm fitted the data with an AUC of 0.81 (95% CI 0.77 to 0.85) and 0.82 (0.79 to 0.85), respectively, using the 10 selected features. Both models outperformed age-based decision rules used in practice (AUC of 0.69, 0.65 to 0.74 for age 〉 70). Furthermore, performance remained stable when excluding age as predictor (AUC of 0.78, 0.75 to 0.81). Conclusion Both models showed good performance and had better test characteristics than age-based decision rules, using 10 admission features readily available in Dutch hospitals. The models hold promise to aid decision-making during a hospital bed shortage.
    Type of Medium: Online Resource
    ISSN: 2044-6055 , 2044-6055
    URL: Article
    DOI: 10.1136/bmjopen-2020-047347
    Language: English
    Publisher: BMJ
    Publication Date: 2021
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  • 7
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    Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
    BMJ ; 2020
    In:  BMJ
    Details
    In: BMJ, BMJ
    Abstract: To review and appraise the validity and usefulness of published and preprint reports of prediction models for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19 infection or being admitted to hospital or dying with the disease. Design Living systematic review and critical appraisal by the covid-PRECISE (Precise Risk Estimation to optimise covid-19 Care for Infected or Suspected patients in diverse sEttings) group. Data sources PubMed and Embase through Ovid, up to 17 February 2021, supplemented with arXiv, medRxiv, and bioRxiv up to 5 May 2020. Study selection Studies that developed or validated a multivariable covid-19 related prediction model. Data extraction At least two authors independently extracted data using the CHARMS (critical appraisal and data extraction for systematic reviews of prediction modelling studies) checklist; risk of bias was assessed using PROBAST (prediction model risk of bias assessment tool). Results 126 978 titles were screened, and 412 studies describing 731 new prediction models or validations were included. Of these 731, 125 were diagnostic models (including 75 based on medical imaging) and the remaining 606 were prognostic models for either identifying those at risk of covid-19 in the general population (13 models) or predicting diverse outcomes in those individuals with confirmed covid-19 (593 models). Owing to the widespread availability of diagnostic testing capacity after the summer of 2020, this living review has now focused on the prognostic models. Of these, 29 had low risk of bias, 32 had unclear risk of bias, and 545 had high risk of bias. The most common causes for high risk of bias were inadequate sample sizes (n=408, 67%) and inappropriate or incomplete evaluation of model performance (n=338, 56%). 381 models were newly developed, and 225 were external validations of existing models. The reported C indexes varied between 0.77 and 0.93 in development studies with low risk of bias, and between 0.56 and 0.78 in external validations with low risk of bias. The Qcovid models, the PRIEST score, Carr’s model, the ISARIC4C Deterioration model, and the Xie model showed adequate predictive performance in studies at low risk of bias. Details on all reviewed models are publicly available at https://www.covprecise.org/ . Conclusion Prediction models for covid-19 entered the academic literature to support medical decision making at unprecedented speed and in large numbers. Most published prediction model studies were poorly reported and at high risk of bias such that their reported predictive performances are probably optimistic. Models with low risk of bias should be validated before clinical implementation, preferably through collaborative efforts to also allow an investigation of the heterogeneity in their performance across various populations and settings. Methodological guidance, as provided in this paper, should be followed because unreliable predictions could cause more harm than benefit in guiding clinical decisions. Finally, prediction modellers should adhere to the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) reporting guideline. Systematic review registration Protocol https://osf.io/ehc47/ , registration https://osf.io/wy245 . Readers’ note This article is the final version of a living systematic review that has been updated over the past two years to reflect emerging evidence. This version is update 4 of the original article published on 7 April 2020 ( BMJ 2020;369:m1328). Previous updates can be found as data supplements ( https://www.bmj.com/content/369/bmj.m1328/related#datasupp ). When citing this paper please consider adding the update number and date of access for clarity.
    Type of Medium: Online Resource
    ISSN: 1756-1833
    URL: Article
    DOI: 10.1136/bmj.m1328
    Language: English
    Publisher: BMJ
    Publication Date: 2020
    detail.hit.zdb_id: 1479799-9
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  • 8
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    Functional Outcomes and Their Association With Physical Performance in Mechanically Ventilated Coronavirus Disease 2019 Survivors at 3 Months Following Hospital Discharge: A Cohort Study
    Ovid Technologies (Wolters Kluwer Health) ; 2021
    In:  Critical Care Medicine Vol. 49, No. 10 ( 2021-10), p. 1726-1738
    Details
    In: Critical Care Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 49, No. 10 ( 2021-10), p. 1726-1738
    Abstract: We performed a comprehensive health assessment in mechanically ventilated coronavirus disease 2019 survivors to assess the impact of respiratory and skeletal muscle injury sustained during ICU stay on physical performance at 3 months following hospital discharge. DESIGN: Preregistered prospective observational cohort study. SETTING: University hospital ICU. PATIENTS: All mechanically ventilated coronavirus disease 2019 patients admitted to our ICU during the first European pandemic wave. MEASUREMENTS AND MAIN RESULTS: At 3 months after hospital discharge, 46 survivors underwent a comprehensive physical assessment (6-min walking distance, Medical Research Council sum score and handgrip strength), a full pulmonary function test, and a chest CT scan which was used to analyze skeletal muscle architecture. In addition, patient-reported outcomes measures were collected. Physical performance assessed by 6-minute walking distance was below 80% of predicted in 48% of patients. Patients with impaired physical performance had more muscle weakness (Medical Research Council sum score 53 [51–56] vs 59 [56–60] ; p 〈 0.001), lower lung diffusing capacity (54% [44–66%] vs 68% of predicted [61–72% of predicted] ; p = 0.002), and higher intermuscular adipose tissue area ( p = 0.037). Reduced lung diffusing capacity and increased intermuscular adipose tissue were independently associated with physical performance. CONCLUSIONS: Physical disability is common at 3 months in severe coronavirus disease 2019 survivors. Lung diffusing capacity and intermuscular adipose tissue assessed on CT were independently associated with walking distance, suggesting a key role for pulmonary function and muscle quality in functional disability.
    Type of Medium: Online Resource
    ISSN: 0090-3493
    URL: Article
    DOI: 10.1097/CCM.0000000000005089
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
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  • 9
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    Prevalence, pathophysiology, prediction and health-related quality of life of long COVID: study protocol of the longitudinal multiple cohort CORona Follow Up (CORFU) study
    BMJ ; 2022
    In:  BMJ Open Vol. 12, No. 11 ( 2022-11), p. e065142-
    Details
    In: BMJ Open, BMJ, Vol. 12, No. 11 ( 2022-11), p. e065142-
    Abstract: 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 scientific journals and presented at (inter)national conferences. Trial registration number NCT05240742 .
    Type of Medium: Online Resource
    ISSN: 2044-6055 , 2044-6055
    URL: Article
    URL: Article
    DOI: 10.1136/bmjopen-2022-065142
    DOI: 10.1136/bmjopen-2022-065142.supp1
    Language: English
    Publisher: BMJ
    Publication Date: 2022
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  • 10
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    Postsurgical Thrombotic Microangiopathy and Deregulated Complement
    MDPI AG ; 2022
    In:  Journal of Clinical Medicine Vol. 11, No. 9 ( 2022-04-29), p. 2501-
    Details
    In: Journal of Clinical Medicine, MDPI AG, Vol. 11, No. 9 ( 2022-04-29), p. 2501-
    Abstract: Postsurgical thrombotic microangiopathy (TMA) is a complication associated with significant morbidity and mortality. Still, the pathophysiological underlying mechanism of postsurgical TMA, a diagnosis often overlooked in postoperative patients with acute kidney injury and thrombocytopenia, is largely unknown. Here, we report the case of a 56-year-old male that developed anuric acute kidney injury, Coombs-negative hemolysis, and thrombocytopenia after surgical aortic arch replacement. Massive ex vivo complement activation on the endothelium, a rare complement gene variant in C2, at-risk haplotype MCPggaac, and excellent response to therapeutic complement inhibition, points to the pivotal role of complement in the pathophysiology of disease. Moreover, the importance of a multidisciplinary team approach in (postsurgical) thrombocytopenia is emphasized.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    URL: Article
    DOI: 10.3390/jcm11092501
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662592-1
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