Generating insights in uncharted territories:Real-time learning from data in critically ill patients-an implementer report

Introduction In the current situation, clinical patient data are often siloed in multiple hospital information systems. Especially in the intensive care unit (ICU), large volumes of clinical data are routinely collected through continuous patient monitoring. Although these data often contain useful information for clinical decision making, they are not frequently used to improve quality of care. During, but also after, pressing times, data-driven methods can be used to mine treatment patterns from clinical data to determine the best treatment options from a hospitals own clinical data. Methods In this implementer report, we describe how we implemented a data infrastructure that enabled us to learn in real time from consecutive COVID-19 ICU admissions. In addition, we explain our step-by-step multidisciplinary approach to establish such a data infrastructure. Conclusion By sharing our steps and approach, we aim to inspire others, in and outside ICU walls, to make more efficient use of data at hand, now and in the future

Zinc-Embedded Polyamide Fabrics Inactivate SARS-CoV-2 and Influenza A Virus.

Influenza A viruses (IAV) and SARS-CoV-2 can spread via liquid droplets and aerosols. Face masks and other personal protective equipment (PPE) can act as barriers that prevent the spread of these viruses. However, IAV and SARS-CoV-2 are stable for hours on various materials, which makes frequent and correct disposal of these PPE important. Metal ions embedded into PPE may inactivate respiratory viruses, but confounding factors such as adsorption of viruses make measuring and optimizing the inactivation characteristics difficult. Here, we used polyamide 6.6 (PA66) fibers containing embedded zinc ions and systematically investigated if these fibers can adsorb and inactivate SARS-CoV-2 and IAV H1N1 when woven into a fabric. We found that our PA66-based fabric decreased the IAV H1N1 and SARS-CoV-2 titer by approximately 100-fold. Moreover, we found that the zinc content and the virus inactivating property of the fabric remained stable over 50 standardized washes. Overall, these results provide insights into the development of reusable PPE that offer protection against RNA virus spread

From registration to publication: A study on Dutch academic randomized controlled trials

Introduction: Registration of clinical trials has been initiated in order to assess adherence of the reported results to the original trial protocol. This study aimed to investigate the publication rates, timely dissemination of results, and the prevalence of consistency in hypothesis, sample size, and primary endpoint of Dutch investigator-initiated randomized controlled clinical trials (RCTs). Methods: All Dutch investigator-initiated RCTs with a completion date between December 31, 2010, and January 1, 2012, and registered in the Trial Register of The Netherlands database were included. PubMed was searched for the publication of these RCT results until September 2016, and the time to the publication date was calculated. Consistency in hypothesis, sample size, and primary endpoint compared with the registry data were assessed. Results: The search resulted in a total of 168 Dutch investigator-initiated RCTs. In September 2016, the results of 129 (77%) trials had been published, of which 50 (39%) within 2 years after completion of accrual. Consistency in hypothesis with the original protocol was observed in 108 (84%) RCTs; in 71 trials (55%), the planned sample size was reached; and 103 trials (80%) presented the original primary endpoint. Consistency in all three parameters was observe

Short-Term Outcomes of Secondary Liver Surgery for Initially Unresectable Colorectal Liver Metastases following Modern Induction Systemic Therapy in the Dutch CAIRO5 Trial

Objective: To present short-term outcomes of liver surgery in patients with initially unresectable colorectal liver metastases (CRLM) downsized by chemotherapy plus targeted agents. Background: The increase of complex hepatic resections of CRLM, technical innovations pushing boundaries of respectability, and use of intensified induction systemic regimens warrant for safety data in a homogeneous multicenter prospective cohort. Methods: Patients with initially unresectable CRLM, who underwent complete resection after induction systemic regimens with doublet or triplet chemotherapy, both plus targeted therapy, were selected from the ongoing phase III CAIRO5 study (NCT02162563). Short-term outcomes and risk factors for severe postoperative morbidity (Clavien Dindo grade ≥ 3) were analyzed using logistic regression analysis. Results: A total of 173 patients underwent resection of CRLM after induction systemic therapy. The median number of metastases was 9 and 161 (93%) patients had bilobar disease. Thirty-six (20.8%) 2-stage resections and 88 (51%) major resections (>3 liver segments) were performed. Severe postoperative morbidity and 90-day mortality was 15.6% and 2.9%, respectively. After multivariable analysis, blood transfusion (odds ratio [OR] 2.9 [95% confidence interval (CI) 1.1-6.4], P = 0.03), major resection (OR 2.9 [95% CI 1.1-7.5], P = 0.03), and triplet chemotherapy (OR 2.6 [95% CI 1.1-7.5], P = 0.03) were independently correlated with severe postoperative complications. No association was found between number of cycles of systemic therapy and severe complications (r = -0.038, P = 0.31). Conclusion: In patients with initially unresectable CRLM undergoing modern induction systemic therapy and extensive liver surgery, severe postoperative morbidity and 90-day mortality were 15.6% and 2.7%, respectively. Triplet chemotherapy, blood transfusion, and major resections were associated with severe postoperative morbidity

Treatment strategies in colorectal cancer patients with initially unresectable liver-only metastases, a study protocol of the randomised phase 3 CAIRO5 study of the Dutch Colorectal Cancer Group (DCCG)

Background: Colorectal cancer patients with unresectable liver-only metastases may be cured after downsizing of metastases by neoadjuvant systemic therapy

Viable Tumor Tissue Adherent to Needle Applicators after Local Ablation: A Risk Factor for Local Tumor Progression

Background. Local tumor progression (LTP) is a serious complication after local ablation of malignant liver tumors, negatively influencing patient survival. LTP may be the result of incomplete ablation of the treated tumor. In this study, we determined whether viable tumor cells attached to the needle applicator after ablation was associated with LTP and disease-free survival. Methods. In this prospective study, tissue was collected of 96 consecutive patients who underwent local liver ablations for 130 liver malignancies. Cells and tissue attached to the needle applicators were analyzed for viability using glucose-6-phosphate-dehydrogenase staining and autofluorescence intensity levels of H&E stained sections. Patients were followed-up until disease progression. Results. Viable tumor cells were found on the needle applicators after local ablation in 26.7% of patients. The type of needle applicator used, an open approach, and the omission of track ablation were significantly correlated with viable tumor tissue adherent to the needle applicator. The presence of viable cells was an independent predictor of LTP. The attachment of viable cells to the needle applicators was associated with a shorter time to LTP. Conclusions. Viable tumor cells adherent to the needle applicators were found after ablation of 26.7% of patients. An independent risk factor for viable cells adherent to the needle applicators is the omission of track ablation. We recommend using only RFA devices that have track ablation functionality. Adherence of viable tumor cells to the needle applicator after local ablation was an independent risk factor for LT

Moving from bytes to bedside: a systematic review on the use of artificial intelligence in the intensive care unit

Purpose: Due to the increasing demand for intensive care unit (ICU) treatment, and to improve quality and efficiency of care, there is a need for adequate and efficient clinical decision-making. The advancement of artificial intelligence (AI) technologies has resulted in the development of prediction models, which might aid clinical decision-making. This systematic review seeks to give a contemporary overview of the current maturity of AI in the ICU, the research methods behind these studies, and the risk of bias in these studies. Methods: A systematic search was conducted in Embase, Medline, Web of Science Core Collection and Cochrane Central Register of Controlled Trials databases to identify eligible studies. Studies using AI to analyze ICU data were considered eligible. Specifically, the study design, study aim, dataset size, level of validation, level of readiness, and the outcomes of clinical trials were extracted. Risk of bias in individual studies was evaluated by the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Results: Out of 6455 studies identified through literature search, 494 were included. The most common study design was retrospective [476 studies (96.4% of all studies)] followed by prospective observational [8 (1.6%)] and clinical [10 (2%)] trials. 378 (80.9%) retrospective studies were classified as high risk of bias. No studies were identified that reported on the outcome evaluation of an AI model integrated in routine clinical practice. Conclusion: The vast majority of developed ICU-AI models remain within the testing and prototyping environment; only a handful were actually evaluated in clinical practice. A uniform and structured approach can support the development, safe delivery, and implementation of AI to determine clinical benefit in the ICU