Predicting Outcomes in Emergency Medical Admissions Using a Laboratory Only Nomogram

Background. We describe a nomogram to explain an Acute Illness Severity model, derived from emergency room triage and admission laboratory data, to predict 30-day in-hospital survival following an emergency medical admission. Methods. For emergency medical admissions (96,305 episodes in 50,612 patients) between 2002 and 2016, the relationship between 30-day in-hospital mortality and admission laboratory data was determined using logistic regression. The previously validated Acute Illness Severity model was then transposed to a Kattan-style nomogram with a Stata user-written program. Results. The Acute Illness Severity was based on the admission Manchester triage category and biochemical laboratory score; these latter were based on the serum albumin, sodium, potassium, urea, red cell distribution width, and troponin status. The laboratory admission data was predictive with an AUROC of 0.85 (95% CI: 0.85, 0.86). The sensitivity was 94.4%, with a specificity of 62.7%. The positive predictive value was 21.2%, with a negative predictive value of 99.1%. For the Kattan-style nomogram, the regression coefficients are converted to a 100-point scale with the predictor parameters mapped to a probability axis. The nomogram would be an easy-to-use tool at the bedside and for educational purposes, illustrating the relative importance of the contribution of each predictor to the overall score. Conclusion. A nomogram to illustrate and explain the prognostic factors underlying an Acute Illness Severity Score system is described

The development and validation of the Virtual Tissue Matrix, a software application that facilitates the review of tissue microarrays on line

BACKGROUND: The Tissue Microarray (TMA) facilitates high-throughput analysis of hundreds of tissue specimens simultaneously. However, bottlenecks in the storage and manipulation of the data generated from TMA reviews have become apparent. A number of software applications have been developed to assist in image and data management; however no solution currently facilitates the easy online review, scoring and subsequent storage of images and data associated with TMA experimentation. RESULTS: This paper describes the design, development and validation of the Virtual Tissue Matrix (VTM). Through an intuitive HTML driven user interface, the VTM provides digital/virtual slide based images of each TMA core and a means to record observations on each TMA spot. Data generated from a TMA review is stored in an associated relational database, which facilitates the use of flexible scoring forms. The system allows multiple users to record their interpretation of each TMA spot for any parameters assessed. Images generated for the VTM were captured using a standard background lighting intensity and corrective algorithms were applied to each image to eliminate any background lighting hue inconsistencies or vignetting. Validation of the VTM involved examination of inter-and intra-observer variability between microscope and digital TMA reviews. Six bladder TMAs were immunohistochemically stained for E-Cadherin, β-Catenin and PhosphoMet and were assessed by two reviewers for the amount of core and tumour present, the amount and intensity of membrane, cytoplasmic and nuclear staining. CONCLUSION: Results show that digital VTM images are representative of the original tissue viewed with a microscope. There were equivalent levels of inter-and intra-observer agreement for five out of the eight parameters assessed. Results also suggest that digital reviews may correct potential problems experienced when reviewing TMAs using a microscope, for example, removal of background lighting variance and tint, and potential disorientation of the reviewer, which may have resulted in the discrepancies evident in the remaining three parameters

Baseline study of Essential Ocean Variable monitoring in Irish waters; current measurement programmes & data quality

This report provides an initial assessment of Ireland’s current measurement programmes and capacity for Essential Ocean Variables (EOV) data collection. These are typically programmes that involve physical sampling of the marine environment, using a combination of ship-based measurements, fixed platforms e.g. tide and wave gauges, offshore buoys, autonomous platforms e.g. underwater gliders, and conventional collection of physical samples that are analysed on board ships or in shore-based laboratories. Systematic measurement of essential ocean variables underpins the delivery of services to government and the public in terms of real-time decision support, assessments of ocean health e.g. Marine Strategy Framework Directive (MSFD), Oslo & Paris Conventions (OSPAR), International Council on the Exploration of the Sea (ICES) and long-term observations to inform policy on marine climate change and provide climate information to guide related adaptation measures required under climate change sectoral adaptation plans e.g. seafood sector, transport, biodiversity, and built heritage

Centromere protein A dynamics in human pluripotent stem cell self-renewal, differentiation and DNA damage

Human pluripotent stem cells (hPSCs) hold significant promise for use in regenerative medicine, or as a model to understand human embryo development. However, the basic mechanisms required for proliferation and self-renewal of hPSCs have not been fully uncovered. Proliferation in all eukaryotes is dependent upon highly regulated expression of the histone H3 variant Centromere protein A (CENP-A). In the current study, we demonstrate that hPSCs have a unique messenger ribonucleic acid (mRNA) reserve of CENP-A not found in somatic fibroblasts. Using short hairpin RNA technology to reduce but not ablate CENP-A, we show that CENP-A-depleted hPSCs are still capable of maintaining a functional centromeric mark, whereas fibroblasts are not. However, upon induction of differentiation or DNA damage, hPSCs with depleted CENP-A arrest in G2/M and undergo apoptosis. Analysis of CENP-A dynamics following DNA damage in hPSCs reveals that 60 min after irradiation, CENP-A is found in multiple small nuclear foci that are mutually exclusive to γH2AX as well as CENP-C. Furthermore, following irradiation, hPSCs with depleted CENP-A mount a normal apoptotic response at 6 h; however at 24 h, apoptosis is significantly increased in CENP-A-depleted hPSCs relative to control. Taken together, our results indicate that hPSCs exhibit a unique mechanism for maintaining genomic integrity by possessing the flexibility to reduce the amount of CENP-A required to maintain a functional centromere under self-renewing conditions, and maintaining a reserve of CENP-A mRNA to rebuild the centromere following differentiation or DNA damage

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Hyponatraemia in Emergency Medical Admissions—Outcomes and Costs

Healthcare systems in the developed world are struggling with the demand of emergency room presentations; the study of the factors driving such demand is of fundamental importance. From a database of all emergency medical admissions (66,933 episodes in 36,271 patients) to St James’ Hospital, Dublin, Ireland, over 12 years (2002 to 2013) we have explored the impact of hyponatraemia on outcomes (30 days in-hospital mortality, length of stay (LOS) and costs). Identified variables, including Acute Illness Severity, Charlson Co-Morbidity and Chronic Disabling Disease that proved predictive univariately were entered into a multivariable logistic regression model to predict the bivariate of 30 days in-hospital survival. A zero truncated Poisson regression model assessed LOS and episode costs and the incidence rate ratios were calculated. Hyponatraemia was present in 22.7% of episodes and 20.3% of patients. The 30 days in-hospital mortality rate for hyponatraemic patients was higher (15.9% vs. 6.9% p < 0.001) and the LOS longer (6.3 (95% CI 2.9, 12.2) vs. 4.0 (95% CI 1.5, 8.2) p < 0.001). Both parameters worsened with the severity of the initial sodium level. Hospital costs increased non-linearly with the severity of initial hyponatraemia. Hyponatraemia remained an independent predictor of 30 days in-hospital mortality, length of stay and costs in the multi-variable model

Air Quality and Hospital Outcomes in Emergency Medical Admissions with Respiratory Disease

Background: The impact of very low levels of air pollutants, particulate matter (PM10) and sulfur dioxide (SO2) concentrations, on human health is not well characterized. We examined the outcomes (30-day in-hospital mortality) of emergency hospitalizations of respiratory patients and the level of local pollutants on the day of admission. Methods: All emergency admissions (82,421 episodes in 44,660 patients) were recorded over 13 years (2002–2014) and mortality assessed. The median interquartile ranges (IQR) age was 64.5 (43.9, 78.5) years with the proportion of males at 48.5%. Univariate and multivariate logistic regression was used to examine relationships between pollutant concentration (PM10 and SO2) and odds ratio (OR) for 30-day in hospital death, after adjustment for acuity. Results: Mortality related to each pollutant variable assessed (as quintiles of increasing atmospheric concentration). For PM10 mortality, the highest two quintiles concentrations were significantly increased (p < 0.001) with univariate ORs of 1.30. For SO2, the ORs were 1.32, 1.39, and 1.46, for the top three quintiles. There was also a strong relationship between the underlying respiratory function; with forced expiratory volume (FEV1) in 1 second (FEV1) ≥ 2.0L at the lowest PM10 quintile, mortality was 6.5% (95% CI: 6.1, 6.9) increasing to 9.5% (95% CI: 9.0, 10.0) at the highest PM10 quintile. For patients with FEV1 < 2.0L, the mortality at the lowest PM10 quintile was 9.9% (95% CI: 8.8, 10.9) increasing to 14.2% (95% CI: 12.8, 15.6) at the highest quintile. Conclusion: Despite air quality improvement, there was a clear relationship between pollutant concentration and outcomes for respiratory emergency admissions; additionally, the underlying level of pulmonary function was predictive of in-hospital mortality