Preoperative laboratory testing for total hip arthroplasty: Unnecessary tests or a helpful prognosticator

Development and Validation of a Risk-Prediction Nomogram for Preoperative Blood Type and Antibody Testing in Spinal Fusion Surgery

OBJECTIVE

With advancements in minimally invasive techniques, the use of spinal fusion surgery is rapidly increasing and transfusion rates are decreasing. Routine preoperative ABO/Rh blood type and antibody screening (T&S) laboratory tests may not be appropriate for all spinal fusion patients. Herein, we constructed a nomogram to assess patient transfusion risk based on various risk factors in patients undergoing spinal fusion surgery, so that preoperative T&S testing can be selectively scheduled in appropriate patients to reduce healthcare and patient costs.

METHODS

Patients who underwent spinal fusion surgery between 01/2020 and 03/2023 were retrospectively examined and classified into the training (n = 3533, 70%) and validation (n = 1515, 30%) datasets. LASSO and multivariable logistic regression were used to analyze risk factors for blood transfusion. Nomogram predictive model was built according to the independent predictors and mode predictive power was validated using consistency index (C-index), Hosmer-Lemeshow (HL) test, calibration curve analysis and area under the curve (AUC) for receiver operating characteristic (ROC) curve. Bootstrap resampling was used for internal validation. Decision curve analysis (DCA) was applied to evaluate the model's performance in the clinic.

RESULTS

Being female, age, BMI, admission route, critical patient, operative time, heart failure, end-stage renal disease or chronic kidney disease (ESRD or CKD), anemia, and coagulation defect were predictors of blood transfusion for spinal fusion. A prediction nomogram was developed according to a multivariate model with good discriminatory power (C-index = 0.887); Bootstrap resampling internal validation C-index was 0.883. Calibration curves showed strong matching between the predicted and actual probabilities of the training and validation sets. HL tests for the training and validation sets had p-values of 0.327 and 0.179, respectively, indicating good calibration. When applied to the training set, the following parameters were found: AUC: 0.895, 95% CI: 0.871-0.919, sensitivity 78.2%, specificity 86.7%, positive predictive value 29.4% and negative predictive value 98.2%. If the model were applied in the training set, 2911 T&S tests (82.4%) would be eliminated, equaling a RMB349,320 cost reduction. The AUC in the internal validation was: 0.879, 95% CI: 0.839-0.927, sensitivity 75.2%, specificity 88.8%, positive predictive value 34.3%, negative predictive value 97.9%, would eliminate 1276 T&S tests (84.2%), saving RMB 153,120. The DCA curve indicated good clinical application value.

CONCLUSION

The nomogram based on 10 independent factors can help healthcare professionals predict the risk of transfusion for patients undergoing spinal fusion surgery to target preoperative T&S testing to appropriate patients and reduce healthcare costs.

Adverse Events After Total Hip Arthroplasty are not Sufficiently Characterized by 30-Day Follow-Up: A Database Study

BACKGROUND

Many previous studies of total hip arthroplasty (THA) have focused on adverse events occurring within 30 days of surgery. Studies examining 90-day postoperative adverse events have typically not focused on the timing of adverse events within that period. The current study evaluated the rate and timing of adverse events within 90 days of THA.

METHODS

Adult THA patients between 2010 and 2020 Q3 were identified from a large administrative dataset. Rates and timing of 90-day adverse events were determined. The median, interquartile range, and middle 80% were calculated based on the time of diagnosis for each adverse event. These were also dichotomized as occurring before or after 30 days and predictive factors for later adverse events were determined.

RESULTS

Overall, 81,158 adverse events were noted, of which 56,500 (69.0%) were diagnosed within 30 days of surgery and 25,355 (31.0%) were diagnosed 31-90 days after surgery. The proportion of adverse events occurring 31-90 days after surgery ranged from 6% (transfusion) to 45% (wound dehiscence). Patients experiencing a later adverse event were more likely to be women and to have higher Elixhauser Comorbidity Index (ECI) scores.

CONCLUSION

Almost one-third of adverse events following THA were diagnosed between postoperative days 31 and 90, highlighting the importance of looking beyond 30 days when estimating patients' risk of postoperative adverse events. These data may inform future research, patient counseling, and prevention strategies.

The association of preoperative blood markers with postoperative readmissions following arthroplasty

Aims

While preoperative bloodwork is routinely ordered, its value in determining which patients are at risk of postoperative readmission following total knee arthroplasty (TKA) and total hip arthroplasty (THA) is unclear. The objective of this study was to determine which routinely ordered preoperative blood markers have the strongest association with acute hospital readmission for patients undergoing elective TKA and THA.

Methods

Two population-based retrospective cohorts were assembled for all adult primary elective TKA (n = 137,969) and THA (n = 78,532) patients between 2011 to 2018 across 678 North American hospitals using the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) registry. Six routinely ordered preoperative blood markers - albumin, haematocrit, platelet count, white blood cell count (WBC), estimated glomerular filtration rate (eGFR), and sodium level - were queried. The association between preoperative blood marker values and all-cause readmission within 30 days of surgery was compared using univariable analysis and multivariable logistic regression adjusted for relevant patient and treatment factors.

Results

The mean TKA age was 66.6 years (SD 9.6) with 62% being females (n = 85,163/137,969), while in the THA cohort the mean age was 64.7 years (SD 11.4) with 54% being female (n = 42,637/78,532). In both cohorts, preoperative hypoalbuminemia (< 35 g/l) was associated with a 1.5- and 1.8-times increased odds of 30-day readmission following TKA and THA, respectively. In TKA patients, decreased eGFR demonstrated the strongest association with acute readmission with a standardized odds ratio of 0.75 per two standard deviations increase (p < 0.0001).

Conclusion

In this population level cohort analysis of arthroplasty patients, low albumin demonstrated the strongest association with acute readmission in comparison to five other commonly ordered preoperative blood markers. Identification and optimization of preoperative hypoalbuminemia could help healthcare providers recognize and address at-risk patients undergoing TKA and THA. This is the most comprehensive and rigorous examination of the association between preoperative blood markers and readmission for TKA and THA patients to date.

Cite this article: Bone Jt Open 2021;2(6):388–396.