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Intell Based Med ; 6: 100071, 2022.
Article in English | MEDLINE | ID: covidwho-1977322


Background: The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among COVID-19 patients could assist decision making in the ICU setting. In this work, we report on the development and validation of a dynamic mortality model specifically for critically ill COVID-19 patients and discuss its potential utility in the ICU. Methods: We collected electronic medical record (EMR) data from 3222 ICU admissions with a COVID-19 infection from 25 different ICUs in the Netherlands. We extracted daily observations of each patient and fitted both a linear (logistic regression) and non-linear (random forest) model to predict mortality within 24 h from the moment of prediction. Isotonic regression was used to re-calibrate the predictions of the fitted models. We evaluated the models in a leave-one-ICU-out (LOIO) cross-validation procedure. Results: The logistic regression and random forest model yielded an area under the receiver operating characteristic curve of 0.87 [0.85; 0.88] and 0.86 [0.84; 0.88], respectively. The recalibrated model predictions showed a calibration intercept of -0.04 [-0.12; 0.04] and slope of 0.90 [0.85; 0.95] for logistic regression model and a calibration intercept of -0.19 [-0.27; -0.10] and slope of 0.89 [0.84; 0.94] for the random forest model. Discussion: We presented a model for dynamic mortality prediction, specifically for critically ill COVID-19 patients, which predicts near-term mortality rather than in-ICU mortality. The potential clinical utility of dynamic mortality models such as benchmarking, improving resource allocation and informing family members, as well as the development of models with more causal structure, should be topics for future research.

Annals of the Rheumatic Diseases ; 80(SUPPL 1):992, 2021.
Article in English | EMBASE | ID: covidwho-1358646


Background: Early diagnosis and management of patients with inflammatory arthritis(IA) are critical to improve long-term patient-outcomes. Assessment of joint swelling at joint examination is the reference of IA-identification;early access clinics are constructed to promote this early recognition of IA. However, due to the COVID-19 pandemic the face-to-face capacity of such services is severely reduced. The accuracy of patient-reported swelling in comparison to joint examination has been extensively evaluated in established RA (ρ 0.31-0.67), but not in patients suspected for IA.[1] Objectives: To promote evidence based care in the era of telemedicine, we determined the accuracy of patient-reported joint swelling for actual presence of IA in persons suspected of IA by general practitioners(GP). Methods: Data from two Dutch Early Arthritis Recognition Clinics were studied. These are screening clinics (1.5-lines-setting) where GPs send patients in case of doubt on IA. At this clinic patients were asked to mark the presence of swollen joints on a mannequin with 52 joints. For this study the DIP joints and the metatarsal joints were excluded and, therefore, a total of 42 joints were assessed for self-reported joint swelling. Clinically apparent IA of ≥1 joint determined by the physician was the reference to calculate sensitivity, specificity, positive and negative likelihood ratios (LR+,LR-), and positive and negative predictive values (PPV, NPV) on patient-level. Pearson correlation coefficients(ρ) were determined. Predictive values depend on the prevalence of a disease in a population. Because the prevalence of IA in a 1.5-lines-setting will differ from a primary care setting, post-test probabilities of IA were estimated for two lower prior-test probabilities as example, namely 20% (estimated probability in patients GPs belief IA is likely) and 2% (prior-test probability with less preselection by GPs), using likelihood ratios and nomograms. Results: A total of 1637 consecutive patients were studied. Median symptom duration was 13 weeks. 76% of patients marked ≥1swollen joint at the mannequin. 41% of patients had ≥1swollen joint at examination by rheumatologists. ρ was 0.20(patient-level)-0.26(joint-level). The sensitivity of patients-reported joint swelling was high, 87%, indicating that the majority of patients with IA had marked swelling on the mannequin. However the specificity was 31%, indicating that 69% of persons without IA had also done so. The LR+ was 1.25;the LR-0.43. The PPV was 46%, the NPV 77%. Thus the PPV increased hardly (from 41% to 46%) and the NPV somewhat (from 59% to 77%). Also in settings with prior-test probabilities of 20% and 2%, estimated PPVs (from respectively 20% and 2% to 24% and 2%) and NPVs (from respectively 80% and 98% to 90% and 99%) hardly increased. Conclusion: Patient-reported joint swelling had little value in distinguishing patients with/without IA for different prior-test probabilities, and is less valuable in comparison to self-reported flare detection in established RA.

South African Medical Journal ; 111(6):535-537, 2021.
Article in English | EMBASE | ID: covidwho-1264653


There have recently been safety concerns regarding an increased risk of vaccine-induced immune thrombotic thrombocytopenia (VITT) following administration of SARS-CoV-2 adenoviral vector vaccines. The Southern African Society of Thrombosis and Haemostasis reviewed the emerging literature on this idiosyncratic complication. A draft document was produced and revised by consensus agreement by a panel of professionals from various specialties. The recommendations were adjudicated by independent international experts to avoid local bias. We present concise, practical guidelines for the clinical management of VITT.