Craniocerebral gunshot injuries in South Africa – a suggested management strategy

Objective. To determine the outcome of craniocerebral gunshot injuries, analyse factors that affect prognosis and suggest a management protocol.Design. A retrospective analysis of civilian craniocerebral gunshot injuries treated over a 7-year period.Setting. Groote Schuur Hospital's neurosurgery and trauma unit service.Patients. One hundred and eighty-one patients with craniocerebral gunshot injuries were admitted to the Department of Neurosurgery, Groote Schuur Hospital, University of Cape Town, over a 7-year period and a retrospective analysis of these patient records with regard to outcome and prognostic factors was carried out.Results. Seventy-six patients sustained non-penetrating injuries, 8 (11 %) of whom had underlying cerebral injury on computed tomography (CT) scan. The prognosis was good in the case of non-penetrating injuries. One hundred and five patients sustained penetrating injuries and 57% (62) had a poor outcome. A Glasgow Coma Score (GCS) of 5 or less following resuscitation was associated with a 98% mortality rate. CT scan evidence of transventricular injury was associated with 100% mortality, bihernispheric injury with 90% mortality, and diffuse cerebral swelling with 81% mortality.Conclusion. Patients with non-penetrating craniocerebral gunshot injuries should all undergo a CT scan as 10% will have cerebral injury. The prognosis is normally good. In penetrating craniocerebral gunshot injuries a GCS of 5 or less, or a GCS of 8 or less with CT scan findings of transventricular or bihernispheric injury have such a poor outcome that conservative treatment is indicated

Circular Networks from Distorted Metrics

Trees have long been used as a graphical representation of species relationships. However complex evolutionary events, such as genetic reassortments or hybrid speciations which occur commonly in viruses, bacteria and plants, do not fit into this elementary framework. Alternatively, various network representations have been developed. Circular networks are a natural generalization of leaf-labeled trees interpreted as split systems, that is, collections of bipartitions over leaf labels corresponding to current species. Although such networks do not explicitly model specific evolutionary events of interest, their straightforward visualization and fast reconstruction have made them a popular exploratory tool to detect network-like evolution in genetic datasets. Standard reconstruction methods for circular networks, such as Neighbor-Net, rely on an associated metric on the species set. Such a metric is first estimated from DNA sequences, which leads to a key difficulty: distantly related sequences produce statistically unreliable estimates. This is problematic for Neighbor-Net as it is based on the popular tree reconstruction method Neighbor-Joining, whose sensitivity to distance estimation errors is well established theoretically. In the tree case, more robust reconstruction methods have been developed using the notion of a distorted metric, which captures the dependence of the error in the distance through a radius of accuracy. Here we design the first circular network reconstruction method based on distorted metrics. Our method is computationally efficient. Moreover, the analysis of its radius of accuracy highlights the important role played by the maximum incompatibility, a measure of the extent to which the network differs from a tree.Comment: Submitte

Comparison of Quantitative Techniques including Xpert MTB/RIF to Evaluate Mycobacterial Burden

Introduction: Accurate quantification of mycobacterial load is important for the evaluation of patient infectiousness, disease severity and monitoring treatment response in human and in-vitro laboratory models of disease. We hypothesized that newer techniques would perform as well as solid media culture to quantify mycobacterial burden in laboratory specimens. Methods: We compared the turn-around-time, detection-threshold, dynamic range, reproducibility, relative discriminative ability, of 4 mycobacterial load determination techniques: automated liquid culture (BACTEC-MGIT-960), [3H]-uracil incorporation assays, luciferase-reporter construct bioluminescence, and quantitative PCR(Xpert -MTB/RIF) using serial dilutions of Mycobacterium bovis and Mycobacterium tuberculosis H37RV. Mycobacterial colony-forming-units(CFU) using 7H10-Middlebrook solid media served as the reference standard. Results: All 4 assays correlated well with the reference standard, however, bioluminescence and uracil assays had a detection threshold ≥1×103 organisms. By contrast, BACTEC-MGIT-960 liquid culture, although only providing results in days, was user-friendly, had the lowest detection threshold (<10 organisms), the greatest discriminative ability (1 vs. 10 organisms; p = 0.02), and the best reproducibility (coefficient of variance of 2% vs. 38% compared to uracil incorporation; p = 0.02). Xpert-MTB/RIF correlated well with mycobacterial load, had a rapid turn-around-time (<2 hours), was user friendly, but had a detection limit of ~100 organisms. Conclusions: Choosing a technique to quantify mycobacterial burden for laboratory or clinical research depends on availability of resources and the question being addressed. Automated liquid culture has good discriminative ability and low detection threshold but results are only obtained in days. Xpert MTB/RIF provides rapid quantification of mycobacterial burden, but has a poorer discrimination and detection threshold

The organisational response of a hospital critical care service to the COVID-19 pandemic: The Groote Schuur Hospital experience.

Background: There are limited data about the coronavirus disease-19 (COVID-19)-related organisational responses and the challenges of expanding a critical care service in a resource-limited setting. Objectives: To describe the ICU organisational response to the pandemic and the main outcomes of the intensive care service of a large state teaching hospital in South Africa. Methods: Data were extracted from administrative records and a prospective patient database with ethical approval. An ICU expansion plan was developed, and resource constraints identified. A triage tool was distributed to referring wards and hospitals. Intensive care was reserved for patients who required invasive mechanical ventilation (IMV). The total number of ICU beds was increased from 25 to 54 at peak periods, with additional non-COVID ICU capacity required during the second wave. The availability of nursing staff was the main factor limiting expansion. A ward-based high flow nasal oxygen (HFNO) service reduced the need for ICU admission of patients who failed conventional oxygen therapy. A team was established to intubate and transfer patients requiring ICU admission but was only available for the first wave. Results: We admitted 461 COVID-19 patients to the ICU over a 13-month period from 5 April 2020 to 5 May 2021 spanning two waves of admissions. The median age was 50 years and duration of ICU stay was 9 days. More than a third of the patients (35%; n=161) survived to hospital discharge. Conclusion: Pre-planning, leadership, teamwork, flexibility and good communication were essential elements for an effective response. A shortage of nurses was the main constraint on ICU expansion. HFNO may have reduced the requirement for ICU admission, but patients intubated after failing HFNO had a poor prognosis. Contributions of the study: We describe the organisational requirements to successfully expand critical care facilities and strategies to reduce the need for invasive mechanical ventilation in COVID-19 pneumonia. We also present the intensive care outcomes of these patients in a resource-constrained environment

Prospective validation of the 4C prognostic models for adults hospitalised with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol

Purpose: To prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19. // Methods: Prospective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups. // Results: 76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, –0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions. // Conclusion: Both 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London

Phosphodiesterase 5 inhibitor treatment and survival in interstitial lung disease pulmonary hypertension: A Bayesian retrospective observational cohort study

Background and Objective Pulmonary hypertension is a life-limiting complication of interstitial lung disease (ILD-PH). We investigated whether treatment with phosphodiesterase 5 inhibitors (PDE5i) in patients with ILD-PH was associated with improved survival. Methods Consecutive incident patients with ILD-PH and right heart catheterisation, echocardiography and spirometry data were followed from diagnosis to death, transplantation or censoring with all follow-up and survival data modelled by Bayesian methods. Results The diagnoses in 128 patients were idiopathic pulmonary fibrosis (n = 74, 58%), hypersensitivity pneumonitis (n = 17, 13%), non-specific interstitial pneumonia (n = 12, 9%), undifferentiated ILD (n = 8, 6%) and other lung diseases (n = 17, 13%). Final outcomes were death (n = 106, 83%), transplantation (n = 9, 7%) and censoring (n = 13, 10%). Patients treated with PDE5i (n = 50, 39%) had higher mean pulmonary artery pressure (median 38 mm Hg [interquartile range, IQR: 34, 43] vs. 35 mm Hg [IQR: 31, 38], p = 0.07) and percentage predicted forced vital capacity (FVC; median 57% [IQR: 51, 73] vs. 52% [IQR: 45, 66], p=0.08) though differences did not reach significance. Patients treated with PDE5i survived longer than untreated patients (median 2.18 years [95% CI: 1.43, 3.04] vs. 0.94 years [0.69, 1.51], p = 0.003) independent of all other prognostic markers by Bayesian joint-modelling (HR 0.39, 95% CI: 0.23, 0.59, p < 0.001) and propensity-matched analyses (HR 0.38, 95% CI: 0.22, 0.58, p < 0.001). Survival difference with treatment was significantly larger if right ventricular function was normal, rather than abnormal, at presentation (+2.55 years, 95% CI: −0.03, +3.97 vs. +0.98 years, 95% CI: +0.47, +2.00, p = 0.04). Conclusion PDE5i treatment in ILD-PH should be investigated by a prospective randomized trial

The synthetic bacterial lipopeptide Pam3CSK4 modulates respiratory syncytial virus infection independent of TLR activation

Respiratory syncytial virus (RSV) is an important cause of acute respiratory disease in infants, immunocompromised subjects and the elderly. However, it is unclear why most primary RSV infections are associated with relatively mild symptoms, whereas some result in severe lower respiratory tract infections and bronchiolitis. Since RSV hospitalization has been associated with respiratory bacterial co-infections, we have tested if bacterial Toll-like receptor (TLR) agonists influence RSVA2- GFP infection in human primary cells or cell lines. The synthetic bacterial lipopeptide Pam3-Cys-Ser-Lys4 (Pam3CSK4), the prototype ligand for the heterodimeric TLR1/TLR2 complex, enhanced RSV infection in primary epithelial, myeloid and lymphoid cells. Surprisingly, enhancement was optimal when lipopeptides and virus were added simultaneously, whereas addition of Pam3CSK4 immediately after infection had no effect. We have identified two structurally related lipopeptides without TLR-signaling capacity that also modulate RSV infection, whereas Pam3CSK4-reminiscent TLR1/2 agonists did not, and conclude that modulation of infection is independent of TLR activation. A similar TLR-independent enhancement of infection could also be demonstrated for wild-type RSV strains, and for HIV-1, measles virus and human metapneumovirus. We show that the effect of Pam3CSK4 is primarily mediated by enhanced binding of RSV to its target cells. The Npalmitoylated cystein

Understanding the burden of interstitial lung disease post-COVID-19: the UK Interstitial Lung Disease-Long COVID Study (UKILD-Long COVID)

Introduction The COVID-19 pandemic has led to over 100 million cases worldwide. The UK has had over 4 million cases, 400 000 hospital admissions and 100 000 deaths. Many patients with COVID-19 suffer long-term symptoms, predominantly breathlessness and fatigue whether hospitalised or not. Early data suggest potentially severe long-term consequence of COVID-19 is development of long COVID-19-related interstitial lung disease (LC-ILD). Methods and analysis The UK Interstitial Lung Disease Consortium (UKILD) will undertake longitudinal observational studies of patients with suspected ILD following COVID-19. The primary objective is to determine ILD prevalence at 12 months following infection and whether clinically severe infection correlates with severity of ILD. Secondary objectives will determine the clinical, genetic, epigenetic and biochemical factors that determine the trajectory of recovery or progression of ILD. Data will be obtained through linkage to the Post-Hospitalisation COVID platform study and community studies. Additional substudies will conduct deep phenotyping. The Xenon MRI investigation of Alveolar dysfunction Substudy will conduct longitudinal xenon alveolar gas transfer and proton perfusion MRI. The POST COVID-19 interstitial lung DiseasE substudy will conduct clinically indicated bronchoalveolar lavage with matched whole blood sampling. Assessments include exploratory single cell RNA and lung microbiomics analysis, gene expression and epigenetic assessment. Ethics and dissemination All contributing studies have been granted appropriate ethical approvals. Results from this study will be disseminated through peer-reviewed journals. Conclusion This study will ensure the extent and consequences of LC-ILD are established and enable strategies to mitigate progression of LC-ILD