Tissue Doppler in critical illness: a retrospective cohort study

Background There is a paucity of published data on tissue Doppler imaging (TDI) in the critically ill. In a critically ill cohort, we studied the distribution of TDI and its correlation with other echocardiographic indices of preload. To aid hypothesis generation and sample size calculation, associations between echocardiographic variables, including the ratio of peak early diastolic transmitral velocity (E) to peak early diastolic mitral annular velocity (E'), and mortality were also explored

Prediction of hospital outcome in septic shock: a prospective comparison of tissue Doppler and cardiac biomarkers

Introduction: Diastolic dysfunction as demonstrated by tissue Doppler imaging (TDI), particularly E/e' (peak early diastolic transmitral/peak early diastolic mitral annular velocity) is common in critical illness. In septic shock, the prognostic value of TDI is undefined. This study sought to evaluate and compare the prognostic significance of TDI and cardiac biomarkers (B-type natriuretic peptide (BNP); N-terminal proBNP (NTproBNP); troponin T (TnT)) in septic shock. The contribution of fluid management and diastolic dysfunction to elevation of BNP was also evaluated

Cost-minimisation analysis alongside a pilot study of early Tissue Doppler Evaluation of Diastolic Dysfunction in Emergency Department Non-ST Elevation Acute Coronary Syndromes (TEDDy-NSTEACS)

Objective To estimate the cost implications of early angiography for patients with suspected non-ST elevation acute coronary syndrome (NSTEACS) using tissue Doppler imaging (TDI). Design A decision tree model was used to synthesise data from the pilot study and literature sources. Sensitivity analyses tested the impact of assumptions incorporated into the analysis. Setting Emergency department (ED), Brisbane, Australia. Participants Patients with suspected NSTEACS. Interventions TDI as a diagnostic tool for triaging patients within 4 hours of presentation in addition to conventional risk stratification, compared with conventional risk stratification alone. Data sources Resource used for diagnosis and management were recorded prospectively and costed for 51 adults who had echocardiography within 24 hours of admission. Costs for conventional care were based on observed data. Cost estimates for the TDI intervention assumed patients classified as high risk at TDI (E/e’>14) progressed early to angiography with an associated 1-day reduction in length of stay. Primary outcome measures Costs until discharge from the Australian healthcare perspective in 2016–2017 prices. Results Findings suggest that using TDI as a diagnostic tool for triaging patients with suspected NSTEACS is likely to be cost saving by $A1090 (95$A573 to $A1703) per patient compared with conventional care. The results are mainly driven by the assumed reduction in length of stay due to the inclusion of early TDI in clinical decision-making. Conclusions This pilot study indicates that compared with conventional risk stratification, triaging patients presenting with suspected NSTEACS with TDI within 4 hours of ED presentation has potential cost savings. Findings assume a reduction in hospital stay is achieved for patients considered to be high risk at TDI. Larger, comparative studies with longer follow-up are needed to confirm the clinical effectiveness of TDI as a diagnostic strategy for NSTEACS, the assumed reduction in hospital stay and any cost saving

Pre-operative immune cell numbers and ratios are associated with peri-operative adverse outcomes in transfused patients

Background and objectivesTransfusion-related immune modulation (TRIM) and associated adverse outcomes during major surgery are increasingly important to patients and health services internationally. A panel of pre-operative blood tests is an essential part of the pre-operative anaesthetic assessment. This panel of blood tests commonly considers numbers of immune cells (i.e., lymphocytes, monocytes, and neutrophils and cell ratios) that may be used as biomarkers to evaluate and potentially predict post-operative adverse outcomes.DesignThis retrospective data collection from eight hospital databases, within the Royal Brisbane and Women's Hospital, considered only patients who received blood transfusion during surgery (2016–2018) (n = 2,121). The association between pre-operative immune cell numbers and ratios and adverse outcomes were assessed. Adverse outcomes were coded using the International Classification of Diseases-10 (ICD-10) coding which specifically considered transfusion-related immune modulation. Results were adjusted for confounding factors.ResultsAfter adjustment, decreased pre-operative lymphocyte numbers and increased neutrophil/lymphocyte ratio (NLR) were associated with increased odds of developing infection; decreased NLR with decreased odds of developing adverse renal outcomes; and decreased lymphocyte numbers with decreased odds of developing adverse cardiovascular outcomes. Monocyte numbers, neutrophil numbers, and the lymphocyte/monocyte ratio (LMR) were not associated with increased adverse outcomes after adjustment.ConclusionPre-operative lymphocyte numbers and NLR are associated with adverse outcomes during peri-operative transfusion. Future assessment of peri-operative immune modulation should include the assessment of immune cell function and numbers

Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes

Acute myeloid leukemia (AML) and myeloid neoplasms develop through acquisition of somatic mutations that confer mutation-specific fitness advantages to hematopoietic stem and progenitor cells. However, our understanding of mutational effects remains limited to the resolution attainable within immunophenotypically and clinically accessible bulk cell populations. To decipher heterogeneous cellular fitness to preleukemic mutational perturbations, we performed single-cell RNA sequencing of eight different mouse models with driver mutations of myeloid malignancies, generating 269,048 single-cell profiles. Our analysis infers mutation-driven perturbations in cell abundance, cellular lineage fate, cellular metabolism, and gene expression at the continuous resolution, pinpointing cell populations with transcriptional alterations associated with differentiation bias. We further develop an 11-gene scoring system (Stem11) on the basis of preleukemic transcriptional signatures that predicts AML patient outcomes. Our results demonstrate that a single-cell-resolution deep characterization of preleukemic biology has the potential to enhance our understanding of AML heterogeneity and inform more effective risk stratification strategies