PubMed Health⌕ Search

PubMed · 9456106

Comprehensive multimodality blood conservation: 100 consecutive CABG operations without transfusion.

Abstract

BACKGROUND: Despite the recent introduction of a number of technical and pharmacologic blood conservation measures, bleeding and allogeneic transfusion remain persistent problems in open heart surgical procedures. We hypothesized that a comprehensive multimodality blood conservation program applied algorithmically on the basis of bleeding and transfusion risk would provide a maximum, cost-effective, and safe reduction in postoperative bleeding and allogeneic blood transfusion. METHODS: One hundred consecutive patients undergoing coronary artery bypass grafting were prospectively enrolled in a risk factor-based multimodality blood conservation program (MMD group). To evaluate the relative efficacy and safety of this comprehensive approach, comparison was made with a similar group of 90 patients undergoing coronary artery bypass grafting to whom the multimodality blood conservation program was not applied but in whom an identical set of transfusion guidelines was enforced (control group). To evaluate the cost effectiveness of the multimodality program, comparison was also made between patients in the MMD group and a consecutive series of contemporaneous, diagnostic-related group-matched patients. RESULTS: One hundred consecutive patients in the MMD group underwent coronary artery bypass grafting without allogeneic transfusion. This compared favorably with the control population in whom a mean of 2.2 +/- 6.7 units of allogeneic blood was transfused per patient (34 patients [38%] received transfusion). In addition, the volume of postoperative blood loss at 12 hours in the control group was almost double that of the MMD group (660 +/- 270 mL versus 370 +/- 180 mL [p < 0.001]). Total costs for the MMD group in each of the three major diagnostic-related groups were equivalent to or significantly less than those in the consecutive series of diagnostic-related group-matched patients. CONCLUSIONS: Comprehensive risk factor-based application of multiple blood conservation measures in an optimized, integrated, and algorithmic manner can significantly decrease bleeding and need of allogeneic transfusion in coronary artery bypass grafting in a safe and cost-effective manner.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

R E Helm, T K Rosengart, M Gomez, J D Klemperer, W J DeBois, F Velasco, J P Gold, N K Altorki, S Lang, S Thomas, O W Isom, K H Krieger. 1998. Comprehensive multimodality blood conservation: 100 consecutive CABG operations without transfusion.. https://doi.org/10.1016/s0003-4975(97)01004-7

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

A note on a generalized single step theory for any number of hierarchical genomic matrices.

BACKGROUND: The Single Step algorithm allows combining information from genotyped and un-genotyped individuals, provided they are connected by a pedigree. However, current single step theory is limited to a single list of markers. RESULTS: We present a generalized single step (GSS) method that can accommodate any number of hierarchical molecular datasets (e.g. sequence, high and low density arrays) and pedigree, avoiding imputation. We prove that a similar efficient inversion algorithm exists. The method is recursive, starting with the highest marker density scenario. We illustrate the method with simulation and show that GSS can increase predictive accuracy compared to standard single step. R code is provided so that custom scenarios can be easily compared, either with simulated or real data. CONCLUSION: The method developed generalizes extant single step theory to any number of hierarchical molecular relationship matrices, broadening the scenarios where single step can be applied. A topic of particular interest can be ecology field data or human populations where pedigree is not available, but where samples sequenced and genotyped at different densities can exist. GSS can also be a useful tool to optimize allocation of genotyping and / or sequencing resources.

Algorithms↗

cgDist: Nucleotide-level distance calculation from cgMLST allelic profiles.

Bacterial genomic surveillance requires balancing computational efficiency with genetic resolution for effective cluster investigation. cgMLST distance calculations treat all allelic differences as equivalent units, obscuring nucleotide-level variation. Furthermore, single nucleotide polymorphism-based pipelines provide finer resolution at substantially higher computational cost, which limits their routine deployment in surveillance laboratories. We present cgDist, an algorithm that calculates nucleotide-level distances directly from cgMLST allelic profiles, providing finer resolution than allele-count distances by leveraging within-allele nucleotide variation. The cache architecture stores alignment statistics, enabling distance calculation modes without computation and supporting both dataset-specific and schema-complete cache generation. This design enables incremental surveillance analysis, with performance benefits as laboratories accumulate alignment data. cgDist functions as a precision 'zoom lens' for the investigation of clusters identified through initial cgMLST screening. Rather than restructuring population relationships, this targeted approach concentrates enhanced resolution where it is most informative. The algorithm ensures that cgDist distances are greater than or equal to corresponding cgMLST distances, preserving epidemiological interpretability while adding genetic discrimination. By increasing resolution within identified clusters, cgDist may also support outbreak investigation, a potential application that remains to be evaluated on outbreak-derived data.

Algorithms↗

Theseus: fast and optimal affine-gap sequence-to-graph alignment.

MOTIVATION: Sequence-to-graph alignment is a central problem in bioinformatics, with applications in multiple sequence alignment (MSA) and pangenome analysis, among others. However, current algorithms for optimal affine-gap alignment impose high memory and computational requirements, limiting their scalability to aligning long sequences to complex graphs. Practical solutions partially address this problem using heuristic strategies that ultimately trade off optimality for speed. RESULTS: This work presents Theseus, a novel, fast, and optimal affine-gap sequence-to-graph alignment algorithm. Theseus leverages similarities between genomic sequences to accelerate the alignment computation and reduces the overall memory requirements without compromising optimality. To that end, Theseus processes only a subset of the dynamic programming cells, using a sparse-data strategy that enables efficient sequence-to-graph alignment. Moreover, our algorithm supports optimal affine-gap alignment on arbitrary directed graphs, including those with cycles. We evaluate Theseus on two key problems: MSA and pangenome read mapping. For MSA, we compare it against SPOA, abPOA, and POASTA. Theseus is 1.6&#xd7; to 17.6&#xd7; faster than POASTA, and 7.3&#xd7; faster, on average, than SPOA, both optimal aligners. Compared with abPOA, Theseus ensures optimality and scales to the largest problems. For pangenome read mapping, we benchmark Theseus against the alignment stage of the mapping tool vg map, along with the alignment kernels of SPOA, abPOA, and POASTA. Theseus outperforms the other methods, showing a 1.9&#xd7; to 16.9&#xd7; speedup on short reads. Moreover, Theseus is 1.5&#xd7; to 36.3&#xd7; faster than vg when aligning against synthetic cyclic graphs. AVAILABILITY AND IMPLEMENTATION: Theseus code and documentation are publicly available at https://github.com/albertjimenezbl/theseus-lib.

Algorithms↗