Predictors Of Blood Transfusion Research Articles

Development and validation of a Bayesian belief network predicting the probability of blood transfusion after pediatric injury.

Early recognition and intervention of hemorrhage are associated with decreased morbidity in children. Triage models have been developed to aid in the recognition of hemorrhagic shock after injury but require complete data and have limited accuracy. To address these limitations, we developed a Bayesian belief network, a machine learning model that represents the joint probability distribution for a set of observed or unobserved independent variables, to predict blood transfusion after injury in children and adolescents. We abstracted patient, injury, and resuscitation characteristics of injured children and adolescents (age 1 to 18 years) from the 2017 to 2019 Trauma Quality Improvement Project database. We trained a Bayesian belief network to predict blood transfusion within 4 hours after arrival to the hospital following injury using data from 2017 and recalibrated the model using data from 2018. We validated our model on a subset of patients from the 2019 Trauma Quality Improvement Project. We evaluated model performance using the area under the receiver operating characteristic curve and calibration curves and compared performance with pediatric age-adjusted shock index (SIPA) and reverse shock index with Glasgow Coma Scale (rSIG) using sensitivity, specificity, accuracy, and Matthew's correlation coefficient (MCC). The final model included 14 predictor variables and had excellent discrimination and calibration. The model achieved an area under the receiver operating characteristic curve of 0.92 using emergency department data. When used as a binary predictor at an optimal threshold probability, the model had similar sensitivity, specificity, accuracy, and MCC compared with SIPA when only age, systolic blood pressure, and heart rate were observed. With the addition of the Glasgow Coma Scale score, the model has a higher accuracy and MCC than SIPA and rSIG. A Bayesian belief network predicted blood transfusion after injury in children and adolescents better than SIPA and rSIG. This probabilistic model may allow clinicians to stratify hemorrhagic control interventions based upon risk. Prognostic and Epidemiologic; Level III.

Selective type & screen for elective colectomy based on a transfusion risk score may generate substantial cost savings.

Preoperative type and screen are currently recommended for all patients undergoing colectomy. We aimed to identify risk factors for transfusion and define a low-risk cohort of patients undergoing colectomy in whom type and screen may be safely avoided. We identified all patients undergoing elective colectomy in the National Surgical Quality Improvement Project-Targeted Colectomy files from 2012 to 2016. Patients transfused preoperatively and those undergoing other concurrent major abdominal procedures were excluded. We compared patients who received blood transfusion on the day of surgery to those who did not. Half of the cohort was randomly selected for development of a points-based model predicting blood transfusion on the day of surgery. This model was then validated using the remaining patients. Of 61,964 patients undergoing colectomy, 3128 (5%) patients were transfused with 1290 (2.1%) occurring on the day of surgery. Preoperative anemia was the strongest predictor of blood transfusion on the day of surgery. Among patients with hematocrit > 35%, day of surgery transfusion risk was 0.8%; 99% of patients with hematocrit > 35% had a score 20 or less. Selective type and screen for patients with score ≤ 20 or hematocrit > 35% would avoid type and screen in 91% and 81% of patients, respectively. Transfusion following elective colectomy is rare and can be accurately predicted by preoperative patient characteristics. Selective type and screen based on these parameters have the potential to prevent operative delays and lower cost.

Blood transfusion risk prediction in spinal tuberculosis surgery: development and assessment of a novel predictive nomogram

ObjectiveThe present study attempted to predict blood transfusion risk in spinal tuberculosis surgery by using a novel predictive nomogram.MethodsThe study was conducted on the clinical data of 495 patients (167 patients in the transfusion group and 328 patients in the non-transfusion group) who underwent spinal tuberculosis surgery in our hospital from June 2012 to June 2021. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analyses were used to screen out statistically significant parameters, which were included to establish a novel predictive nomogram model. The receiver operating characteristic (ROC) curve, calibration curves, C-index, and decision curve analysis (DCA) were used to evaluate the model. Finally, the nomogram was further assessed through internal validation.ResultsThe C-index of the nomogram was 0.787 (95% confidence interval: 74.6%–.82.8%). The C-value calculated by internal validation was 0.763. The area under the curve (AUC) of the predictive nomogram was 0.785, and the DCA was 0.01–0.79.ConclusionA nomogram with high accuracy, clinical validity, and reliability was established to predict blood transfusion risk in spinal tuberculosis surgery. Surgeons must prepare preoperative surgical strategies and ensure adequate availability of blood before surgery.

A predictive model for blood transfusion during liver resection

BackgroundA predictive model that can identify patients who are at increased risk of intraoperative blood transfusion could guide preoperative transfusion risk counseling, optimize health care resources, and reduce medical costs. Although previous studies have identified some predictors for particular populations, there is currently no existing model that uses preoperative variables to accurately predict blood transfusion during surgery, which could help anesthesiologists optimize intraoperative anesthetic management. MethodsWe collected data from 582 patients who underwent elective liver resection at a university-affiliated tertiary hospital between January 1, 2018, and December 31, 2020. The data set was then randomly divided into a training set (n = 410) and a validation set (n = 172) at a 7:3 ratio. The least absolute shrinkage and selection operating regression model was used to select the optimal feature, and multivariate logistic regression analysis was applied to construct the transfusion risk model. The concordance index (C-index) and the area under the receiver operating characteristic (ROC) curve (AUC) were used to evaluate the discrimination ability, and the calibration ability was assessed with calibration curves. In addition, we used decision curve analysis (DCA) to estimate the clinical application value. For external validation, the test set data were employed. ResultsThe final model had 8 predictor variables for intraoperative blood transfusion, which included the following: preoperative hemoglobin level, preoperative prothrombin time >14 s, preoperative total bilirubin >21 μmol/L, respiratory diseases, cirrhosis, maximum lesion diameter >5 cm, macrovascular invasion, and previous abdominal surgery. The model showed a C-index of 0.834 (95% confidence interval, 0.789–0.879) for the training set and 0.831 (95% confidence interval, 0.766–0.896) for the validation set. The AUCs were 0.834 and 0.831 for the training and validation sets, respectively. The calibration curve showed that our model had good consistency between the predictions and observations. The DCA demonstrated that the transfusion nomogram was reliable for clinical applications when an intervention was decided at the possible threshold across 1%–99% for the training set. ConclusionWe developed a predictive model with excellent accuracy and discrimination ability that can help identify those patients at higher odds of intraoperative blood transfusion. This tool may help guide preoperative counseling regarding transfusion risk, optimize health care resources, reduce medical costs, and optimize anesthetic management during surgery.

Predictors of blood transfusion among patients admitted with early severe pre-eclampsia

Transfusion of packed red blood cells (pRBC) is an effective strategy for the management of severe anemia in pregnancy. Although rare, transfusion does incur risk and reactions can be severe. We sought to investigate rates of pRBC transfusion in patients with early (< 34 weeks), severe preeclampsia (sPREX) and to determine factors associated with transfusion in this population.

Perioperative Trajectory of Haemoglobin, Predictors of Blood Transfusion and Tailoring Targets for Patient Blood Management Interventions: A Single-centre, Retrospective Study of Non-emergent Cardiac Surgery Patients.

Anaemia and blood transfusion are two independent contributing factors to perioperative morbidity in cardiac surgery. While preoperative treatment of anaemia has been shown to improve outcomes, in real life, logistical difficulties remain substantial, even in high-income countries. The adequate trigger for transfusion in this population remains controversial, and there is a wide variability in transfusion rates among centres. To assess the impact of preoperative anaemia on perioperative transfusion in elective cardiac surgery,todescribe the perioperative trajectory of haemoglobin (Hb), to stratify outcomes based on preoperative presence of anaemia and to identify predictors of perioperative blood transfusion. and Methods: We included a retrospective cohort of consecutive patients who underwent cardiac surgery with cardiopulmonary bypass in a tertiary centre of cardiovascular surgery. Recorded outcomes included hospital and intensive care unit (ICU) length of stay (LOS), surgical re-exploration due to bleeding, packed red blood cell (PRBC) transfusion pre-, intra- and postoperatively. Other record perioperative variables were preoperative chronic kidney disease, duration of surgery, use of rotation thromboelastometry (ROTEM) and cell saver, and fresh frozen plasma (FFP) and platelet (PLT) transfusion. Hb values were recorded at four distinct time points: Hb1 - at hospital admission, Hb2 - last Hb recorded preoperatively, Hb3 - first Hb recorded postoperatively and Hb4 - at hospital discharge. We compared the outcomes between anaemic and non-anaemic patients. Transfusion was decided by the attending physician on a case-by-case basis. Results: Of the 856 patients operated during the selected period, 716 underwent non-emergent surgery and 710 were included in the analysis. Also, 40.5% (n = 288) of patients were anaemic preoperatively (Hb <13 g/dl); 369 patients (52%) were transfused PRBCs, with differences found between anaemic and non-anaemic patients regarding the percentage of transfused patients perioperatively (71.5% vs 38.6%, p < 0.001) and in the total median number of units transfused (2 [IQR 0-2] vs 0 [IQR 0-1], p <0.001). We built a multivariate model, and logistic regression analysis showed that preoperative Hb <13 g/dl (odds ratio [OR] 3.462 [95% CI 1.766-6.787]), female sex (OR 3.224 [95% CI 1.648-6.306]), age (1.024 per year [95% CI 1.0008-1.049]), hospital LOS (OR 1.093 per day of hospitalisation [95% CI 1.037-1.151]) and FFP transfusion (OR 5.110 [95% CI 1.997-13.071]) are associated with PRBC transfusion. Untreated preoperative anaemia leads to more transfusion in elective cardiac surgery patients, both as a ratio of transfused patients and as the number of units of PRBCs per patient, and this is associated with an increased use in FFP.

Incidence and predictors of blood transfusions in one-stage bilateral total hip arthroplasty: a single center prospective cohort study.

The safety of performing one-stage bilateral total hip arthroplasty (THA) remains controversial among the orthopedic community. The aim of the present study was to determine the incidence and predictors of blood transfusions in one-stage bilateral THA performed in a high-volume single center. Patients undergoing one-stage bilateral THA between 2015 and 2017 were included. The following data were collected from the hospital medical records: age, body mass index (BMI), American Society of Anaesthesiologists (ASA) score, smoking habit, comorbidities, preoperative serum creatinine, serum iron, ferritin, C-reactive protein (CRP), and hemoglobin (Hb). The Hb levels at postoperative day 1 and 3 were also collected. A total of 367 patients with a mean age of 56.1years (range, 32-79) were included. Forty-eight (13%) patients were transfused with a mean number of 1.6 blood units per patient. In non-transfused patients, the average Hb drop was 3.6 (SD ± 1) g/dL and 4.9g/dL (SD ± 1.3) at postoperative day 1 and day 3, respectively. The average preoperative Hb level was 14.64 (SD ± 1.21) g/dL. In the univariate logistic regression, the following variables were predictive factors for transfusions: male gender (OR 0.447; P = 0.01), preoperative hemoglobin level (OR 0.622; P = 0.001), preoperative ferritin level (OR 0.995; P = 0.016), BMI (OR 0.837; P = 0.001), cardiopathy (OR 3.534; P = 0.046), preoperative anaemia (OR 10.54; P = 0.011). In the multivariate logistic regression only preoperative hemoglobin level (OR 0.666; P = 0.01), and BMI (OR 0.868; P = 0.007) were statistically significant. The incidence of blood transfusions after one-stage bilateral THA is low in non-anemic patients operated on at a high-volume arthroplasty center. The main predictors of blood transfusions are preoperative Hb level and BMI.

Serum Lactate Level as a Predictor for Blood Transfusion in Postpartum Hemorrhage.

Postpartum hemorrhage (PPH) is the leading cause of maternal morbidity and mortality. At present, there are no reliable clinical or laboratory indicators to identify which patients might require blood transfusions during a PPH. Serum lactate has long been used as an early biomarker of tissue hypoperfusion in trauma settings. The aim of this study is to understand serum lactate's role in the management of obstetric hemorrhage. A retrospective chart review was performed of women who delivered between 2016 and 2019 at our institution and experienced a PPH. The patients were divided into two groups: those with a normal serum lactate level, defined as ≤2 mmol/L, and those with an abnormal serum lactate level, defined as >2 mmol/L. Need for packed red blood cell transfusion, as part of the resuscitation, was assessed for both groups. During the study period, 938 women experienced PPH. Of these, 108 (11.5%) had a normal serum lactate, ≤2 mmol/L, and 830 (88.5%) had an abnormal lactate, >2 mmol/L. Women with elevated lactate levels were more likely to receive a blood transfusion versus those with a normal lactate level (57.0 vs. 46.3%, p = 0.035, respectively). Additionally, the average number of blood transfusions administered was significantly higher in the abnormal lactate group versus in the normal lactate group (1.34 vs. 0.97, respectively, p = 0.004). In a multivariable linear regression model, increasing serum lactate levels were found to be predictive of requiring more than 1 unit of blood (p < 0.001). Women with elevated serum lactate levels were more likely to require blood transfusions during a PPH versus those with a normal serum lactate level. Thus, serum lactate levels are useful as an early indicator of requirement for blood transfusion in the management of obstetric hemorrhage. · Lactate is a biomarker for blood transfusion in trauma.. · Lactate's role in PPH is unknown.. · Elevated lactate predicts receiving more blood transfusions..

Epidemiology and Predictors of Blood Transfusion in Hospitalizations for Sickle Cell Disease

Background: Transfusional iron overload contributes to considerable morbidity and mortality in patients with sickle cell disease. Despite FDA (Food and Drug Administration) approval of voxelotor in 2019, it remains underutilized, and RBC (red blood cell) transfusions play a prominent role in managing these patients. Contemporary large-scale epidemiologic data on blood transfusions in sickle cell disease are lacking. This study reports demographics, readmission rate, and factors associated with blood transfusion in hospitalizations for sickle cell disease.Methods: We performed a retrospective cohort study using the Nationwide Readmissions Database (NRD) for 2017 & 2018 to identify hospitalizations with the primary diagnosis of sickle disease using appropriate ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) codes. These admissions were categorized into those who received blood transfusions and those without blood transfusions. We performed descriptive analysis to compare demographics, hospital characteristics, various comorbid conditions, and complications between the two groups. All-cause 30-day readmission rate was calculated after excluding index admissions from December, deaths during index admissions, and elective readmissions. Multivariable logistic regression was used to adjust for confounders and determine factors associated with RBC transfusion. The analysis was carried out to produce national estimates after applying weights, and the methodology provided by the HCUP (Healthcare Cost and Utilization Project) was utilized.Results: Out of 109,783 weighted index hospitalizations, 28,300 were transfused, and 81,483 were not transfused. The proportion of females and 40 years & older was higher in the transfused category than not transfused (59.49% vs. 53.52% and 28.86% vs. 21.27% respectively; p<0.001 for both). The wealthiest population was more likely to be in the transfused category than the non-transfused (11.27% vs. 8.34%; p<0.001). The proportion of admissions to teaching hospitals, large metropolitan hospitals, and highest volume hospitals was higher in the non-transfused category compared to the transfused (79.89% vs. 72.17%; p<0.001, 69.26% vs. 65.35%; p 0.003 and 74.71% vs. 63.51%; p<0.001 respectively). The comorbidity burden, mean length of stay, total hospital charges, and inpatient mortality were higher in the transfused category than those without transfusion (table 1). Most admissions were transfused once, with multiple transfusions (3 or more) being given more in the non-teaching hospitals than teaching (1.27% vs. 0.41%; p 0.01). Furthermore, more than half of all transfusions happened within the first two days of admission, with a higher proportion of early transfusions in the non-teaching hospitals compared to teaching hospitals (65.6% vs. 57.82% for admission days 1 and 2; p<0.001) (table 2). Age group ≥40 years and 25-39 years were more likely to receive transfusion in the first two days of admission than the 18-24-year-olds (69.01% vs. 59.14% vs. 49.2%; p<0.001 respectively). After adjusting for confounders, older age groups (age ≥40 years and 25-39 years) compared to 18-24-year-olds (aOR {adjusted odds ratio} 1.48; 95% CI {confidence interval} 1.36-1.62 and aOR 1.21; 95% CI 1.12-1.31 respectively), female sex (aOR 1.23; 95% CI 1.17-1.31), highest community-level income (aOR 1.52; 95% CI 1.31-1.75), admission to rural hospital (aOR 1.82; 95% CI 1.26-2.6), length of stay 4-7 vs. ≤3 days (aOR 1.56; 95% CI 1.46-1.66) and length of stay ≥8 vs. ≤3 days (aOR 2.28; 95% CI 2.05-2.53) were found to be associated with higher odds of blood transfusion. Admission to a teaching hospital was associated with lower blood transfusion odds than a non-teaching hospital (aOR 0.70; 95% CI 0.56-0.87) (table 3).Conclusion: A quarter of admissions for sickle cell disease receive a blood transfusion. In addition to performing more frequent and early transfusions, the odds of being transfused are higher in a non-teaching hospital. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Improved identification of severely injured pediatric trauma patients using reverse shock index multiplied by Glasgow Coma Scale.

The shock index pediatric age-adjusted (SIPA) predicts the need for increased resources and mortality among pediatric trauma patients without incorporating neurological status. A new scoring tool, rSIG, which is the reverse shock index (rSI) multiplied by the Glasgow Coma Scale (GCS), has been proven superior at predicting outcomes in adult trauma patients and mortality in pediatric patients compared with traditional scoring systems. We sought to compare the accuracy of rSIG to Shock Index (SI) and SIPA in predicting the need for early interventions in civilian pediatric trauma patients. Patients (aged 1-18 years) in the 2014 to 2018 Pediatric Trauma Quality Improvement Program database with complete heart rate, systolic blood pressure, and total GCS were included. Optimal cut points of rSIG were calculated for predicting blood transfusion within 4 hours, intubation, intracranial pressure monitoring, and intensive care unit admission. From the optimal thresholds, sensitivity, specificity, and area under the curve were calculated from receiver operating characteristics analyses to predict each outcome and compared with SI and SIPA. A total of 604,931 patients with a mean age of 11.1 years old were included. A minority of patients had a penetrating injury mechanism (5.6%) and the mean Injury Severity Score was 7.6. The mean SI and rSIG scores were 0.85 and 18.6, respectively. Reverse shock index multiplied by Glasgow Coma Scale performed better than SI and SIPA at predicting early trauma outcomes for the overall population, regardless of age. Reverse shock index multiplied by Glasgow Coma Scale outperformed SI and SIPA in the early identification of traumatically injured children at risk for early interventions, such as blood transfusion within 4 hours, intubation, intracranial pressure monitoring, and intensive care unit admission. Reverse shock index multiplied by Glasgow Coma Scale adds neurological status in initial patient assessment and may be used as a bedside triage tool to rapidly identify pediatric patients who will likely require early intervention and higher levels of care. Prognostic, level III.

O40 Predictive models of individual risk of elective caesarean section complications: a systematic review

Abstract Introduction With increasing caesarean section (c-section) rates, personalised communication of risk has become paramount. A reliable tool to predict complications would support evidence-based discussion around planned mode of birth. Method MEDLINE, Embase, Web of Science, CINAHL, and the Cochrane Library were searched on 27th January with the terms relating to c-section, prognostic models, and complications such as infection. Any study developing and/or validating a prognostic model for maternal complications of c-section in the English language after January 1995 was included. Data extracted encompassed: source of data, participant criteria, outcome to be predicted, candidate predictors, actual predictors, sample size, model development, and model performance. PROBAST (Prediction model Risk Of Bias Assessment Tool) was utilised for risk of bias analysis and applicability concern in the prognostic model studies. Result 7,752 studies were identified, of which 16 were reviewed producing 3 studies where 3 prognostic models were identified which predicted risk of: blood transfusion, spinal hypotension, and postpartum haemorrhage. From the 3 studies, a total of 29 unique candidate predictors were identified and 15 predictors in the final model. Study authors deemed their studies to be exploratory, exploratory, and confirmatory respectively. None were externally validated and all had a high risk of bias due to analysis technique. Conclusion Few models have been developed to predict complications of elective c-section. Existing models predicting blood transfusion, spinal hypotension, and postpartum haemorrhage cannot be recommended for clinical practice. Future research should focus on identifying predictors known before surgery and validating resulting models. Take-home Message Systematic review of prediction models for planned C-section complications found none suitable for practice.

Development and validation of a nomogram to predict intraoperative blood transfusion for gastric cancer surgery

To construct and validate a nomogram composed of preoperative variables to predict intraoperative blood transfusion for gastric cancer surgery. Intraoperative transfusion for gastric cancer surgery is a common medical procedure that is associated with increased postoperative complications. A total of 999 patients who underwent gastrectomy between January 2010 and June 2019 were randomly allocated into the primary and validation cohorts in a 2:1 ratio. In the primary cohort, logistic analyses were performed to identify independent predictors for transfusion. Using the Akaike information criterion, selected variables were incorporated to construct a nomogram. Validations of the nomogram were performed in the primary and validation cohorts. The discrimination ability of the nomogram was assessed by the concordance index (C-index), and calibration was assessed by calibration curves and the Hosmer-Lemeshow goodness-of-fit test. The following risk factors for transfusion were identified and used to construct the nomogram: ASA status (III-IV vs I-II: odds ratio [OR] 1.74), comorbidities (yes vs no: OR 1.57), tumour location (diffuse vs lower: OR 4.05), cTNM stage (III vs I: OR 1.95), and a preoperative haemoglobin level less than 80 g/L (vs over 120 g/L: OR 35.30). The C-index was 0.859 and 0.850 in the primary and validation cohorts, respectively, which both indicated good discrimination of the nomogram. Additionally, both calibration curves and Hosmer-Lemeshow tests (p-value 0.184 and 0.887, respectively) demonstrated high agreement between the predictions and actual outcomes. A nomogram composed of preoperative variables to predict blood transfusion for gastric cancer surgery was effectively developed and validated. This nomogram could be used to improve the utilisation of red blood cells for gastrectomy.

Quantification of Blood Loss Improves Detection of Postpartum Hemorrhage and Accuracy of Postpartum Hemorrhage Rates: A Retrospective Cohort Study.

ObjectiveTo evaluate the ability of estimated blood loss (EBL) and quantitative blood loss (QBL) to predict the need for blood transfusion in postpartum patients.MethodsThis is a retrospective observational study involving all deliveries one year before and after the change from EBL to QBL assessment in June 2017. Blood loss, need for blood transfusion, admission hematocrit, and postpartum nadir hematocrit were collected. Descriptive and bivariable analyses were performed. Receiver operator curves were compared.ResultsOverall, the baseline characteristics between the EBL (n=2743) and QBL (n=2,712) groups were similar. Although there was a higher rate of blood loss ≥ 1,000 mL in QBL vs EBL (6.5% vs 2.1%, P<0.001), there was no difference in the rate of blood transfusions (2.0% vs 2.0%, P=1). Among cesarean deliveries, QBL outperformed EBL for predicting blood transfusion and/or ≥10 point drop in hematocrit (AUC 0.75 vs 0.66, P=0.02). QBL also outperformed EBL for predicting transfusion after vaginal delivery (AUC 0.93 vs 0.81, P=0.03). ConclusionQBL is a more sensitive test for detecting clinically significant blood loss, which could lead to earlier recognition of hemorrhage and interventions.

Predictors of blood transfusion in patients undergoing total shoulder arthroplasty

BackgroundAnatomic total shoulder arthroplasty (TSA) and reverse total shoulder arthroplasty are major surgeries that may result in significant blood loss and the need for transfusion. The purpose of this study was to identify predictors for blood transfusion in patients undergoing TSA. MethodsThe American College of Surgeons National Surgical Quality Improvement Program was used to identify 12,982 patients who underwent TSA (anatomic or reverse) from January 1, 2011 to December 31, 2016. We compared patients who underwent intraoperative or postoperative blood transfusion with those who did not receive a blood transfusion. Multivariable logistic regression was used to determine independent factors associated with blood transfusion. ResultsThe rate of intraoperative and postoperative blood transfusion was 3.5% during the study period. Compared with patients who did not receive a blood transfusion, those who did were older (73.4 vs. 68.9 years, P < .001), had longer operative times (137.8 vs. 110.7 minutes, P < .001), had longer hospital stays (3.9 vs. 1.9 days, P < .001), and were more likely to be female (74% vs. 55%, P < .001). Patients who received a blood transfusion had higher mean American Society of Anesthesiologists (ASA) classification score (2.8 vs. 2.5, P < .001). The following factors were independently associated with greater odds of blood transfusion: ASA class 4 (odds ratio [OR] 8.4, 95% confidence interval [CI] 2.0-36), dialysis (OR 2.5, 95% CI 1.0-5.9), bleeding disorders (OR 2.4, 95% CI 1.6-3.5), female sex (OR 1.8, 95% CI 1.4-2.3), and smoking (OR 1.4, 95% CI 1.0-2.0). Patients with independent functional status before surgery were least likely to require blood transfusion (OR 0.5, P < .001). ConclusionIn patients undergoing shoulder arthroplasty, preoperative factors such as ASA classification, smoking, and functional status can be used to identify patients at increased risk for requiring blood transfusion. Level of evidenceLevel III.

Establishment and assessment of a nomogram for predicting blood transfusion risk in posterior lumbar spinal fusion

BackgroundThe aim of this study was to determine the risk factors and develop a nomogram for blood transfusions after posterior lumbar spinal fusion (PSL).MethodsWe conducted a retrospective, single-center study based on 885 patients receiving PSL, and data was obtained from May 2015 to September 2019. Univariable and multivariable logistics regression analysis were conducted to identify risk factors for blood transfusion, and a nomogram was constructed to individually evaluate the risk of blood transfusion. Discrimination, calibration, and clinical usefulness were validated by the receiver operating characteristics (ROC), C-index, calibration plot, and decision curve analysis, respectively. Bootstrapping validation was performed to assess the performance of the model.ResultsOf 885 patients, 885 were enrolled in the final study population, and 289 received blood transfusion. Statistical analyses showed that low preoperative hemoglobin (Hb), longer time to surgery, operative time, levels of fusion > 1, longer surgery duration, and higher total intraoperative blood loss (IBL) were the risk factors for transfusion. The C-index was 0.898 (95% CI 0.847–0.949) in this dataset and 0.895 in bootstrapping validation, respectively. Calibration curve showed satisfied discrimination and calibration of the nomogram. Decision curve analysis (DCA) shown that the nomogram was clinical utility.ConclusionsIn summary, we investigated the relationship between the blood transfusion requirement and predictors: levels of fusion, operative time, time to surgery, total intraoperative EBL, and preoperative Hb level. Our nomogram with a robust performance in the assessment of risk of transfusion can contribute to clinicians in making clinical decision. However, external validation is still needed in the further.

Lactate and base deficit combination score for predicting blood transfusion need in blunt multi-trauma patients.

Lactate and base deficit (BD) values are parameters evaluated as indicators of tissue perfusion and have been used as markers of severity of injury and mortality. The aim of the study was to determine the relationship between combined score (CS) and blood transfusion need within 24 h and comparison of the variables between transfusion and non-transfusion group, correlation lactate with BD and with physiological, laboratory parameters, and determining the major risk factors of patients for the need for blood transfusion. The study included a total of 359 patients (245 males, median age: 40, min-max: 18-95) with blunt multi-trauma. De-mographics data, laboratory parameters (hemoglobin [Hb], hematocrit [Htc], lactate, BD, pH), physiologic parameters (systolic blood pressure [SBP], diastolic blood pressure [DBP], heart rate [HR], respiratory rate [RR]), shock index (SI), and revised trauma score (RTS) were recorded. Logistic regression method was used to create the CS formula using lactate and BD values. According to this formula, the probability value of 0.092447509 was calculated for the need for blood transfusion within 24 h. If CS was higher than the probability value, the need for blood transfusion within 24 h was considered. Furthermore, univariate analysis was used to determine major risk for blood transfusion need in 24 h, and the receiver operating characteristic curves were performed to compare CS, lactate, BD, SI and RTS. The comparison between transfusion and non-transfusion group there was significance between SBP, DBP, HR, RR, SpO2, Glasgow coma scale, Hb, Htc, lactate, BD, pH, SI and RTS (for each p<0.05). Lactate value has a positive correlation with SI, HR and has a negative correlation with BD, RTS, SBP, and DBP. BD values has a positive correlation with RTS, SBP, DBP, Hb, and Htc and has a negative correlation with SI, HR, and RR. The main risks for blood transfusion need were SI, lactate, BD, SBP, and SpO2%. CS was 0.09 in 100 (27.85%) patients and 41 with high CS had blood transfusion within 24 h (p<0.001; OR21.803, sensitivity 83.7%, specificity 81%,positive predictive value 41%, and negative predictive value 96.9%). A ROC curve showed that CS (AUC: 86.) was more significant than SI and RTS for the need for blood transfusion. CS is effective for predicting blood necessity in 24 h for blunt multi-trauma patients.

Blood product transfusion in liver transplantation in First Clinical Hospital of Mongolia

Background: Liver transplantation is a well-accepted treatment of end-stage liver diseases. Seven-eight liver transplants have been performed from 2011 to June of 2019 in First Clinical Hospital of Mongolia. Numerous advances in perioperative manage ment, like expertise in surgical techniques, better preoperative optimization, intraoperative monitoring and management, chang es in immunosuppression regime and advances in postoperative management, not only increased the number of this procedure but also the outcome. The role of the anesthesiologist is to provide safe anesthesia and maintain an acceptable hemodynamic performance, ensuring sufficient perfusion to the vital organs. Estimation of the amount of blood products required during liver transplantation can help provision of adequate blood supply, minimize transfusion associated complications and plan for preven tive measures in high risk patients. Methods: Our objective is to investigate some factors impact to perioperative blood product transfusion. We used data of pa tients who underwent liver transplantation between October 2011 and June 2019 at First Clinical Hospital of Mongolia, were reviewed. The all amount of blood product utilized during surgery and some factors, including pretransplant laboratory data, pre transplant clinical data were recorded. Results: We studied 77 patients who underwent liver transplantation. The mean±standard deviation amounts of red blood cells and fresh frozen plasma transfusion during surgery were 1.64±2.36 and 2.22±2.7 liters, respectively. The mean amount of red blood cells and albumin was significantly (P<0.003 and P<0.005) correlated with model for end-stage liver disease (MELD) score of patients. The mean amount of blood products utilized during operation was decreased from 2015 to 2019 except two retrans plantation patients. Conclusions: Some preoperative factors may predict blood transfusion requirements in patients undergoing liver transplanta tion. Therefore, evaluation of patients before operation should be considered to provide adequate blood supply. Understanding preoperative factors associated with rate of transfusion may help us to best utilize the limited available blood resources.

Adjusted preoperative variables to predict perioperative red blood cell transfusion in coronary artery bypass grafting.

The variables for predicting blood transfusion perioperatively are not completely clear in coronary artery bypass grafting (CABG) patients. To construct a comprehensive model to predict perioperative RBC transfusion in patients undergoing isolated CABG using adjusted preoperative variables. Perioperative data of 1253 patients who underwent isolated CABG by the same surgical team were collected from April 2018 to March 2019. Logistic regression analyses were used to establish equations to construct two models for predicting intraoperative and postoperative RBC transfusions, respectively. All significant variables included in the two models were combined to form a comprehensive model to predict perioperative RBC transfusion. Area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the discriminatory power of the models. The total RBC transfusion rate for CABG patients during hospitalization was 29.05%. The rate of intraoperative and postoperative RBC transfusions was 6.9% and 26.7%, respectively. Eight variables in a total of 30 risk factors constituted the intraoperative prediction model, 12 variables constituted the postoperative prediction model, and 13 variables for the combined model. The AUC of the three models were 0.87, 0.82, and 0.83, respectively, demonstrating moderate discriminatory power for RBC transfusion during the intraoperative, postoperative, and perioperative periods. The comprehensive model combined with all variables of predicting intraoperative and postoperative RBC transfusion is feasible for predicting perioperative RBC transfusion.

Risk assessment of cirrhosis patients with esophageal and gastric variceal bleeding by three scoring systems

Objective To compare the risk assessment capability of model for end-stage liver disease (MELD), glasgow-blatchford score (GBS), and the AIMS65 scoring system for liver cirrhosis patients with esophageal and gastric variceal bleeding (EGVB). Methods A retrospective analysis was made on data of 182 cirrhosis patients with EGVB admitted to the Department of Gastroenterology, General Hospital of Tianjin Medical University from January 1, 2015 to March 1, 2018. According to the MELD, GBS and AIMS65 scoring system, the corresponding scores of each were calculated to evaluate the ability of the three scoring systems to correctly classify EGVB as a high-risk patient . The receiver operating characteristic curve was drawn to compare the predictive value of three scoring systems for different clinical outcomes (blood transfusion, rebleeding, and death). The area under curve (AUC)>0.7 was believed to have higher accuracy. Results The clinical outcomes of 182 patients included blood transfusion in 113 (62.1%) cases, rebleeding in 31 (17.0%) cases, and death of 11 (6.0%) cases. The MELD score was 7-25, GBS was 3-16, and AIMS65 score was 0-3. There were 4 (2.2%) patients with MELD score < 9, 139 (76.4%) patients with AIMS65 score 0-1, including 68 patients with AIMS65 score of 0 and 71 patients with AIMS65 score of 1. The AUC of MELD, GBS and AIMS65 for predicting blood transfusion was 0.514 (95%CI: 0.439-0.589), 0.681 (95%CI: 0.608-0.748), and 0.669 (95%CI: 0.596-0.737), respectively. When predicting rebleeding, the AUC of MELD, GBS and AIMS65 was 0.525 (95%CI: 0.449-0.599), 0.528 (95%CI: 0.453-0.602) and 0.580 (95%CI: 0.505-0.652), respectively. When predicting in-hospital mortality, the AUC of MELD, GBS and AIMS65 was 0.642 (95%CI: 0.567-0.711), 0.581 (95%CI: 0.505-0.653) and 0.786 (95%CI: 0.719-0.843), respectively. AIMS65 was superior to MELD (P=0.083 6) and GBS (P=0.047 0). Conclusion GBS can correctly classify cirrhosis patients with EGVB as high-risk group , and is better than AIMS65 and MELD scoring system. MELD, GBS and AIMS65 all have poor accuracy in predicting blood transfusion and rebleeding, AIMS65 has a higher predictive value for death. Key words: Prognosis; Liver cirrhosis; Esophageal and gastric variceal bleeding; Scoring system

A vértranszfúzió gyakorisága primer csípőprotézis-beültetés után

Introduction: Total hip arthroplasty is one of the most common surgical procedures that requires blood transfusion, with the possible risk of significant complications. Aim: A retrospective study was performed to analyze the predictors of blood transfusion after primary total hip arthroplasty. Method: We collected the data of 210 consecutive patients undergoing total hip arthroplasty. Patient's data, preoperative hemoglobin and hematocrit level, the type of the prosthesis, the use of a suction drain, tranexamic acid or anticoagulants and the type and amount of blood transfusion were recorded. Results: A total of 41% of our patients required transfusion, 8.6% receiving allogenic blood. Significant predictors of allogenic blood transfusion were preoperative hemoglobin and hematocrit levels, the type of prosthesis, the use of suction drainage and the use of tranexamic acid. Patients with pre-donated autologous blood did not require allogenic blood transfusion. Conclusion: Based on our study, total hip arthroplasty necessitates allogenic blood transfusion in 8.6%. Major predictors associated with the need for transfusion are preoperative hemoglobin and hematocrit levels, the type of prosthesis, the use of suction drainage and the use of tranexamic acid. Pre-donated autologous blood helps to reduce allogenic transfusion rate. Orv Hetil. 2020; 161(8): 290-294.