Development and validation of a nomogram to predict perioperative blood transfusion in patients undergoing total knee arthroplasty

Predictors of Blood Transfusion in Patients Undergoing Lumbar Spinal Fusion

OBJECTIVE

To determine risk factors for perioperative blood transfusion after lumbar fusion surgery.

METHODS

After institutional review board approval, a retrospective cohort study of adult patients who underwent lumbar fusion at a single, urban tertiary academic center was retrospectively retrieved. Our primary outcome, blood transfusion, was collected via chart query. A receiver operating characteristic curve was used to evaluate the regression model. A P-value < 0.05 was considered statistically significant.

RESULTS

Of the 3,842 patients, 282 (7.3%) required a blood transfusion. For patients undergoing posterolateral decompression and fusion, predictors of transfusion included age (P < 0.001) and more levels fused (P < 0.001). A higher preoperative hemoglobin level (P < 0.001) and revision surgery (P = 0.005) were protective of blood transfusion. For patients undergoing transforaminal lumbar interbody fusion, greater Elixhauser comorbidity index (P < 0.001), longer operative time (P = 0.040), and more levels fused (P = 0.030) were independent predictors of the need for blood transfusion. Patients with a higher body mass index (P = 0.012) and preoperative hemoglobin level (P < 0.001) had a reduced likelihood of receiving a transfusion. For circumferential fusion, greater age (P = 0.006) and longer operative times (P = 0.015) were independent predictors of blood transfusion, while a higher preoperative hemoglobin level (P < 0.001) and male sex (P = 0.002) were protective.

CONCLUSIONS

Our analysis identified older age, lower body mass index, greater Elixhauser comorbidity index, longer operative duration, more levels fused, and lower preoperative hemoglobin levels as independent predictors of requiring a blood transfusion following lumbar spinal fusion. Different surgical approaches were not found to be associated with transfusion.

Systematic review highlights high risk of bias of clinical prediction models for blood transfusion in patients undergoing elective surgery

BACKGROUND

Blood transfusion can be a lifesaving intervention after perioperative blood loss. Many prediction models have been developed to identify patients most likely to require blood transfusion during elective surgery, but it is unclear whether any are suitable for clinical practice.

STUDY DESIGN AND SETTING

We conducted a systematic review, searching MEDLINE, Embase, PubMed, The Cochrane Library, Transfusion Evidence Library, Scopus, and Web of Science databases for studies reporting the development or validation of a blood transfusion prediction model in elective surgery patients between January 1, 2000 and June 30, 2021. We extracted study characteristics, discrimination performance (c-statistics) of final models, and data, which we used to perform risk of bias assessment using the Prediction model risk of bias assessment tool (PROBAST).

RESULTS

We reviewed 66 studies (72 developed and 48 externally validated models). Pooled c-statistics of externally validated models ranged from 0.67 to 0.78. Most developed and validated models were at high risk of bias due to handling of predictors, validation methods, and too small sample sizes.

CONCLUSION

Most blood transfusion prediction models are at high risk of bias and suffer from poor reporting and methodological quality, which must be addressed before they can be safely used in clinical practice.

Development and validation of a nomogram to predict complications in patients undergoing simultaneous bilateral total knee arthroplasty: A retrospective study from two centers

Purpose

Complications were significantly increased 30 days after Simultaneous bilateral total knee arthroplasty (SBTKA). In this study, an individualized nomogram was established and validated to predict the complications within 30 days after SBTKA.

Methods

The general data of 861 patients (training set) who received SBTKA in The Affiliated Hospital of Qingdao University between January 1, 2012 and March 31, 2017 were retrospectively analyzed. All patients were divided into complication group (n = 96) and non-complication group (n = 765) according to the incidence of complications within 30 years after SBTKA. Independent risk factors for postoperative SBTKA complications were identified and screened by binary logistic regression analyses, and then a nomogram prediction model was constructed using R software. The area under curve (AUC), calibration curve, and decision curve analysis (DCA) were selected to evaluate the line-chart. Meanwhile, 396 patients receiving SBTKA in the Third Hospital of Hebei Medical University who met the inclusion and exclusion criteria (test set) were selected to verify the nomogram.

Results

Five independent predictors were identified by binary logistic regression analyses and a nomogram was established. The AUC of this nomogram curve is 0.851 (95% CI: 0.819–0.883) and 0.818 (95% CI: 0.735–0.900) in the training and testing sets, respectively. In the training set and test set, calibration curves show that nomogram prediction results are in good agreement with actual observation results, and DCA shows that nomogram prediction results have good clinical application value.

Conclusion

Older age, lower preoperative hemoglobin level, higher preoperative blood urea nitrogen (BUN) level, longer operation time, ASA grade ≥ III are independent predictors of SBTKA complications within 30 days after surgery. A nomogram containing these five predictors can accurately predict the risk of complications within 30 days after SBTKA.

Predict Postoperative Anemia of Patients: Nomogram Construction and Validation

Introduction

The loss of blood is a significant problem in Total Knee Arthroplasty (TKA). Anemia often occurs after such surgeries, leading to serious consequences, such as higher postoperative infection rates and longer hospital stays. Tools for predicting possible anemia can provide additional guidance in realizing better blood management of patients.

Methods

2,165 patients who underwent TKA from 2015 to 2019 in the same medical center were divided into training and validation cohorts. Both univariate and multivariate logistic regression analyses were performed to identify independent preoperative risk factors for anemia. Based on these predictors, a nomogram was established using the area under the curve (AUC), calibration curve (AUC), and the area under the curve (AUC). The model was then applied to the validation cohort, and decision curve analyses (DCA) were also plotted.

Results

Through analysis of both univariate and multivariate logistic regression, five independent predictors were found in the training cohort: female, relatively low BMI, low levels of preoperative hemoglobin, abnormally high levels of ESR, and simultaneously two sides of TKA in the same surgery. The AUCs of the nomogram were 74.6% (95% CI, 71.35%–77.89%) and 68.8% (95% CI, 63.37%–74.14%) of training and the validation cohorts separately. Furthermore, the calibration curves of both cohorts illustrated the consistency of the nomogram with the actual condition of anemia of patients after TKA. The DCA curve was higher for both treat-none and treat-all, further indicating the relatively high practicality of the model.

Conclusion

Female, lower BMI, lower levels of preoperative Hb, simultaneous bilateral TKA, and high levels of preoperative ESR were figured out as five independent risk factors for postoperative anemia (&lt;9.0 g/dL) in patients undergoing TKA. Based on the findings, a practical nomogram was constructed to predict risk of postoperative anemia. The evidence level should be level 4 according to guideline.

Effect of severity and cause of preoperative anemia on the transfusion rate after total knee arthroplasty

This study aimed to (1) evaluate the preoperative Hb cut-off value for transfusion after unilateral and bilateral staged (1 week apart) TKAs, respectively, and (2) determine whether cause of preoperative anemia can affect transfusion rate after TKA. A total of 951 patients who underwent TKA (unilateral: 605, bilateral staged: 346) from 2016 to 2019 were reviewed retrospectively. Patient demographics, comorbidities, preoperative Hb level, surgery types, and cause of anemia were evaluated as possible risk factors. The cut-off values for preoperative Hb level to reduce transfusion after TKA were evaluated in each surgery type. Preoperative Hb level, surgery type, and cardiac disease were identified as the risk factors for transfusion after TKA, and preoperative Hb levels of 11.8 (AUC 0.88) and 12.8 (AUC 0.76) were the cut-off values for transfusion after unilateral and staged bilateral TKAs, respectively. Although transfusion rate was higher in anemia with iron deficiency (ID) group than anemia without ID group, preoperative Hb level was also lower in anemia with ID group than anemia without ID group. Single use of preoperative Hb level with different cut-offs depending on the surgery types can be useful indicator for preoperative optimization regardless of cause of anemia.

Establishment and Verification of a Perioperative Blood Transfusion Model After Posterior Lumbar Interbody Fusion: A Retrospective Study Based on Data From a Local Hospital

Objective: We aimed to analyze the related risk factors for blood transfusion and establish a blood transfusion risk model during the per-ioperative period of posterior lumbar interbody fusion (PLIF). It could provide a reference for clinical prevention and reduction of the risk of blood transfusion during the peri-operative period. Methods: We retrospectively analyzed 4,378 patients who underwent PLIF in our hospital. According to whether they were transfused blood or not, patients were divided into the non-blood transfusion group and the blood transfusion group. We collected variables of each patient, including age, sex, BMI, current medical history, past medical history, surgical indications, surgical information, and preoperative routine blood testing. We randomly divide the whole population into training group and test group according to the ratio of 4:1. We used the multivariate regression analyses get the independent predictors in the training set. The nomogram was established based on these independent predictors. Then, we used the AUC, calibration curve and DCA to evaluate the nomogram. Finally, we verified the performance of the nomogram in the validation set. Results: Three or more lumbar fusion segments, preoperative low hemoglobin, with hypertension, lower BMI, and elder people were risk factors for blood transfusion. For the training and validation sets, the AUCs of the nomogram were 0.881 (95% CI: 0.865-0.903) and 0.890 (95% CI: 0.773-0.905), respectively. The calibration curve shows that the nomogram is highly consistent with the actual observed results. The DCA shows that the nomogram has good clinical application value. The AUC of the nomogram is significantly larger than the AUCs of independent risk factors in the training and validation set. Conclusion: Three or more lumbar fusion segments, preoperative low hemoglobin, with hypertension, lower BMI, and elder people are associated with blood transfusion during the peri-operative period. Based on these factors, we established a blood transfusion nomogram and verified that it can be used to assess the risk of blood transfusion after PLIF. It could help clinicians to make clinical decisions and reduce the incidence of peri-operative blood transfusion.

Efficacy and Safety of Intravenous Ferric Carboxymaltose in Patients with Postoperative Anemia Following Same-Day Bilateral Total Knee Arthroplasty: A Randomized Controlled Trial

(1) Background: The purpose of this study was to evaluate the efficacy and safety of intravenous (IV) ferric carboxymaltose (FCM) to treat acute postoperative anemia following same-day bilateral total knee arthroplasty (TKA). (2) Methods: A total of 118 patients who underwent same-day bilateral TKA were randomly assigned to two groups: an FCM group (FCM infusion, 58 patients) and a Control group (placebo with normal saline, 60 patients). The primary endpoint was the number of responders with a Hb increase of two or more points by the second postoperative week. The secondary endpoints were Hb level, iron metabolism variables and blood transfusion rate at 2, 6 and 12 weeks after surgery. (3) Results: The FCM group had more Hb responders than the Control group (62.1% vs. 31.6%, p < 0.001). The Hb level was significantly higher in the FCM group during 12 weeks after surgery (all p < 0.05). Ferritin, iron and transferrin saturation levels were significantly higher in the FCM group from 2 to 12 weeks postoperatively (all p < 0.05). There was no difference in transfusion rate after surgery (p > 0.05). (4) Conclusion: In patients with postoperative anemia after same-day bilateral TKA, IV FCM infusion significantly improved Hb response two weeks after surgery without severe adverse events compared to placebo. In contrast, transfusion rate and various parameters of quality of life assessment up to 12 weeks did not vary between these groups. Level of evidence: Level I.