Auditing plasma transfusion in intensive care: Use of decision time interval analysis.

OBJECTIVES: To present a new method for displaying blood utilization data based on analysis of decision time intervals (DTIs). METHODS: Retrospective study of patients treated in a medical intensive care unit (ICU), surgical ICU, or postcardiac surgery ICU at an academic hospital between January 2018 and June 2023. Each patient's episode of care was divided into a series of DTIs. Transfusions during each time interval were recorded. RESULTS: In total, 16,562 patients received 6980 units of plasma and 21,034 units of red blood cells during 111,557 time intervals of care. Patients had international normalized ratio (INR) values ranging from less than 1.0 to more than 4.0. Data on plasma transfusion at different INR values were displayed as the number of transfusion episodes, number of units given, or the proportion of DTIs with transfusion. Clinicians transfused plasma on 1.5% of occasions when the INR was 1.5 or less and on 2.2% of occasions when the INR was less than 2.0. Plasma was transfused without red blood cells in only 0.75% of DTIs. Transfusion practice was statistically different among the 3 ICUs. CONCLUSIONS: Compared with traditional methods of displaying the results of blood audits, DTI analysis displays information regarding the decision both to transfuse and to not transfuse. Utilization reviews that display data based on decision time analysis reveal clinical practice patterns very different from those suggested by traditional displays of plasma audit data.

Platelet transfusion in critical care: A new method to analyze transfusion practice based on decision time intervals.

BACKGROUND: While prior studies of platelet transfusion in critical care have focused on transfusions given, proper analysis of clinical transfusion practice also requires consideration of the decision not to transfuse. STUDY DESIGN AND METHODS: We introduce a new method to assess transfusion practice based on decision time intervals (DTIs). Each patient's intensive care (ICU) stay was segmented into a series of DTIs defined by a time interval following results of a complete blood count (CBC). We studied the presence of 17 clinical factors during each DTI whether transfusion was given or not. We used a generalized linear mixed model to assess the most influential clinical triggers for platelet transfusion. RESULTS: Among 6125 ICU patients treated between October 2016 and October 2021, we analyzed 39,745 DTIs among patients (n = 2921) who had at least one DTI with thrombocytopenia (≤150,000/µL). We found no association between platelet count and two markers of bleeding: drop in hemoglobin and chest tube drainage. We found that the majority of DTIs were associated with no platelet transfusion regardless of the platelet count; that no specific platelet value triggered transfusion; but rather that multiple clinical factors in conjunction with the platelet count influenced the decision to transfuse. DISCUSSION: DTI analysis represents a new method to assess transfusion practice that considers both transfusions given and not given, and that analyzes clinical circumstances present when decisions regarding transfusion are made. The method is easily adapted to blood components other than platelet transfusions and is easily extended to other ICU and other hospital settings.

Significant Operational Improvements with Implementation of Next Generation Laboratory Automation.

OBJECTIVES: To investigate the benefits and challenges of introducing next generation chemistry and coagulation automation. METHODS: We replaced the Roche modular preanalytic system attached to Roche Cobas 6000 analyzers with the Roche 8100 preanalytical line attached to the Roche Cobas 8000 and Stago STA R Max analyzers. The system included 2 add-on buffers (AOBs) for automated specimen archival and retrieval and primary-tube specimen processing. We measured turnaround time (TAT) from specimen receipt to result for chemistry and coagulation tests before, during, and after system implementation. TAT for add-on tests was also measured. RESULTS: We completed the system implementation during a 17-month period using existing laboratory space. The TAT for chemistry, coagulation, and add-on tests decreased significantly (P <.005, P <.001, and P <.005, respectively). We encountered several challenges, including barcode-label errors, mechanical problems, and workflow issues due to lack of bidirectional track for coagulation testing. CONCLUSIONS: Next generation laboratory automation yielded significantly shortened and less-variable TAT, particularly for add-on testing. Our approach could help other laboratories in the process of implementing and configuring automated systems.

Intersection of population variation and autoimmunity genetics in human T cell activation.

T lymphocyte activation by antigen conditions adaptive immune responses and immunopathologies, but we know little about its variation in humans and its genetic or environmental roots. We analyzed gene expression in CD4(+) T cells during unbiased activation or in T helper 17 (T(H)17) conditions from 348 healthy participants representing European, Asian, and African ancestries. We observed interindividual variability, most marked for cytokine transcripts, with clear biases on the basis of ancestry, and following patterns more complex than simple T(H)1/2/17 partitions. We identified 39 genetic loci specifically associated in cis with activated gene expression. We further fine-mapped and validated a single-base variant that modulates YY1 binding and the activity of an enhancer element controlling the autoimmune-associated IL2RA gene, affecting its activity in activated but not regulatory T cells. Thus, interindividual variability affects the fundamental immunologic process of T helper activation, with important connections to autoimmune disease.

Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes.

To extend our understanding of the genetic basis of human immune function and dysfunction, we performed an expression quantitative trait locus (eQTL) study of purified CD4(+) T cells and monocytes, representing adaptive and innate immunity, in a multi-ethnic cohort of 461 healthy individuals. Context-specific cis- and trans-eQTLs were identified, and cross-population mapping allowed, in some cases, putative functional assignment of candidate causal regulatory variants for disease-associated loci. We note an over-representation of T cell-specific eQTLs among susceptibility alleles for autoimmune diseases and of monocyte-specific eQTLs among Alzheimer's and Parkinson's disease variants. This polarization implicates specific immune cell types in these diseases and points to the need to identify the cell-autonomous effects of disease susceptibility variants.

Enriched transcription factor binding sites in hypermethylated gene promoters in drug resistant cancer cells.

MOTIVATION: In the human genome, 'CpG islands', CG-rich regions located in or near gene promoters, are normally unmethylated. However, in cancer cells, CpG islands frequently gain methylation, resulting in silencing of growth-limiting tumor suppressor genes. To our knowledge, the potential relationship between CpG island hypermethylation, transcription factor (TF) binding in local promoter regions and transcriptional control has not been previously explored in a genome-wide context. RESULTS: In this study, we utilized bioinformatics tools and TF binding site(TFBs) databases to globally analyze sequences methylated in a laboratory model for the development of drug-resistant cancer. Our results demonstrated that four TFBS were enriched in hypermethylated sequences. More interestingly, overrepresentation of these TFBS was observed in hyper-/hypo-methylated sequences where signi.cant changes in methylation levels were observed in drug-resistant cancer cells. In summary, we believe that these.ndings offer a means to further explore the relationship between DNA methylation and gene expression in drug resistance and tumorigenesis.

New anti-cancer strategies: epigenetic therapies and biomarkers.

Epigenetics is the study of chromatin modifications that affect gene expression without altering DNA nucleotide sequences. This review highlights a prominent role for epigenetic therapies, particularly those that reverse aberrant DNA methylation and histone acetylation, in the potential treatment of cancer. Administration of such therapies to reverse epigenetic "silencing" of tumor suppressors, including genes involved in chemotherapy responses, could prove useful in the management of cancer patients. In this review, we summarize recent advances in the use of methyltransferase and histone deacetylase inhibitors and possible synergistic combinations of these to achieve maximal tumor suppressor gene re-expression. Moreover, when used in combination with conventional chemotherapeutic agents, epigenetic-based therapies may provide a means to resensitize drug-resistant tumors to established treatments. As specific, aberrant epigenetic modifications are frequently associated with distinct cancer types, and likely occur early in tumorigenesis, these have potential utility as biomarkers. Finally, future directions are addressed, including alternative epigenetic targets, gene-specific modifications, and the use of bioinformatics.