Examination of intra-operative core temperature in joint arthroplasty: a single-institution prospective observational study

Cross-Combination Analyses of Random Forest Feature Selection and Decision Tree Model for Predicting Intraoperative Hypothermia in Total Joint Arthroplasty

BACKGROUND

In total joint arthroplasty patients, intraoperative hypothermia (IOH) is associated with perioperative complications and an increased economic burden. Previous models have some limitations and mainly focus on regression modeling. Random forest (RF) algorithms and decision tree modeling are effective for eliminating irrelevant features and making predictions that aid in accelerating modeling and reducing application difficulty.

METHODS

We conducted this prospective observational study using convenience sampling and collected data from 327 total joint arthroplasty patients in a tertiary hospital from March 4, 2023, to September 11, 2023. Of those, 229 patients were assigned to the training and 98 to the testing sets. The Chi-square, Mann-Whitney U, and t-tests were used for baseline analyses. The feature variables selection used the RF algorithms, and the decision tree model was trained on 299 examples and validated on 98. The sensitivity, specificity, recall, F1 score, and area under the curve were used to test the model's performance.

RESULTS

The RF algorithms identified the preheating time, the volume of flushing fluids, the intraoperative infusion volume, the anesthesia time, the surgical time, and the core temperature after intubation as risk factors for IOH. The decision tree was grown to 5 levels with 9 terminal nodes. The overall incidence of IOH was 42.13%. The sensitivity, specificity, recall, F1 score, and area under the curve were 0.651, 0.907, 0.916, 0.761, and 0.810, respectively. The model indicated strong internal consistency and predictive ability.

CONCLUSIONS

The preheating time, the volume of flushing fluids, the intraoperative infusion volume, the anesthesia time, the surgical time, and the core temperature after intubation could accurately predict IOH in total joint arthroplasty patients. By monitoring these factors, the clinical staff could achieve early detection and intervention of IOH in total joint arthroplasty patients.

Dexamethasone with aggressive warming facilitates pain reduction, reduced blood loss, and quicker recovery after total hip arthroplasty

This study aimed to evaluate the optimal frequency of dexamethasone (DEX) administration and the efficacy of DEX with aggressive warming in total hip arthroplasty (THA), which remains unclear. A total of 150 patients were treated with DEX (10 mg) once before and once or twice after surgery with or without intraoperative aggressive warming. On postoperative day 3, the dynamic visual analogue scale scores and C-reactive protein (CRP) and interleukin-6 (IL-6) levels in participants administered with DEX twice after surgery were significantly lower than those who did not receive the second dose. The range of motion (ROM), postoperative fatigue based on Identity-Consequence-Fatigue Scale, average temperature at different stages, intraoperative blood loss, and postoperative drainage volume in patients who were subjected to warming were significantly higher than those who were not. The degree of satisfaction was also higher in the patients who received both second dose and warming than those who received neither. No differences in complications were observed based on the treatments. An additional dose of DEX at 48 h post-surgery has short-term advantages in terms of analgesia, anti-inflammatory effects, and accelerated rehabilitation after THA. DEX combined with aggressive warming further optimises short-term ROM and fatigue and improves the degree of satisfaction.Clinical trial was registered in the International Clinical Trial Registry, and the date of registration is 2/12/2020 (ChiCTR2000040560).

Construction and validation of a risk prediction model for intraoperative hypothermia in elderly patients undergoing total hip arthroplasty

AIMS

To construct and validate an intraoperative hypothermia risk prediction model for elderly patients undergoing total hip arthroplasty (THA).

METHODS

We collected data from 718 patients undergoing THA in a tertiary hospital from January 2021 to December 2022. Of these patients, 512 were assigned to the modeling group from January 2021 to April 2022, and 206 participants were assigned to the validation group from May 2022 to December 2022. A logistic regression analysis was performed to construct the model. The area under the curve (AUC) was used to test the model's predictive ability.

RESULTS

The incidence rate of intraoperative hypothermia was 51.67%. The risk factors entered into the risk prediction model were age, preoperative hemoglobin level, intraoperative blood loss, postoperative hemoglobin level, and postoperative systolic blood pressure. The model was constructed as follows: logit (P) = - 10.118 + 0.174 × age + 1.366 × 1 (preoperative hemoglobin level) + 0.555 × 1 (postoperative hemoglobin level) + 0.009 × 1 (intraoperative blood loss) + 0.066 × 1 (postoperative systolic blood pressure). Using the Hosmer-Lemeshow test, the P value was 0.676 (AUC, 0.867). The Youden index, sensitivity, and specificity were 0.602, 0.790, and 0.812, respectively. The incidence rates of intraoperative hypothermia in the modeling and validation groups were 53.15% and 48.06%, respectively. The correct practical application rate was 89.81%. This model had good application potential.

CONCLUSIONS

This risk prediction model has good predictive value and can accurately predict the occurrence of intraoperative hypothermia in patients who undergo THA, which provides reliable guidance for clinical work and has good clinical application value.

Nurse anesthetists' perceptions of heat conservation measures in connection with surgery - a phenomenographic study

BACKGROUND

To minimize the risk of perioperative hypothermia, it is recommended that healthcare professionals be familiar with heat conservation measures and use passive and active warming methods, in line with international guidelines. However, there is a low level of adherence perioperatively to the use of heat conservation measures. To understand why, there is a need to capture the nurse anesthetists' perspective. The aim is to describe nurse anesthetists' perceptions of heat conservation measures in connection with surgery.

METHODS

An inductive descriptive design with a phenomenographic approach was chosen. A total of 19 nurse anesthetists participated and were interviewed. Data were analyzed according to Larsson and Holmström's phenomenographic seven-step model.

RESULTS

Six ways of understanding the phenomenon heat conservation measures in connection with surgery were found: the preventive, the useable, the untenable, the caring, the adaptive, and the routine care approach. These approaches were related to each other in a flexible way, allowing for several to co-exist at the same time, depending on the situation.

CONCLUSIONS

Nurse anesthetists want to prevent the patients' heat loss and maintain normothermia, regardless of the type of surgery. This willingness, motivation, and intention enable the use of heat conservation measures. However, there are perceptions that have an impact, such as doubts and uncertainty, access, time and financial constraints, preconditions, routines or habits, and lack of availability of education/training. These barriers will require support from an organizational level to promote lifelong education and guidelines. As well as offer education at the nurse anesthetists' program.

Comparison of zero heat flux and double sensor thermometers during spinal anaesthesia: a prospective observational study

Because of the difficulties involved in the invasive monitoring of conscious patients, core temperature monitoring is frequently neglected during neuraxial anaesthesia. Zero heat flux (ZHF) and double sensor (DS) are non-invasive methods that measure core temperature from the forehead skin. Here, we compare these methods in patients under spinal anaesthesia. Sixty patients scheduled for elective unilateral knee arthroplasty were recruited and divided into two groups. Of these, thirty patients were fitted with bilateral ZHF sensors (ZHF group), and thirty patients were fitted with both a ZHF sensor and a DS sensor (DS group). Temperatures were saved at 5-min intervals from the beginning of prewarming up to one hour postoperatively. Bland–Altman analysis for repeated measurements was performed and a proportion of differences within 0.5 °C was calculated as well as Lin`s concordance correlation coefficient (LCCC). A total of 1261 and 1129 measurement pairs were obtained. The mean difference between ZHF sensors was 0.05 °C with 95% limits of agreement − 0.36 to 0.47 °C, 99% of the readings were within 0.5 °C and LCCC was 0.88. The mean difference between ZHF and DS sensors was 0.33 °C with 95% limits of agreement − 0.55 to 1.21 °C, 66% of readings were within 0.5 °C and LCCC was 0.59. Bilaterally measured ZHF temperatures were almost identical. DS temperatures were mostly lower than ZHF temperatures. The mean difference between ZHF and DS temperatures increased when the core temperature decreased.

Trial registration: The study was registered in ClinicalTrials.gov on 13th May 2019, Code NCT03408197.

Variable selection methods for identifying predictor interactions in data with repeatedly measured binary outcomes

Introduction:

Identifying predictors of patient outcomes evaluated over time may require modeling interactions among variables while addressing within-subject correlation. Generalized linear mixed models (GLMMs) and generalized estimating equations (GEEs) address within-subject correlation, but identifying interactions can be difficult if not hypothesized a priori. We evaluate the performance of several variable selection approaches for clustered binary outcomes to provide guidance for choosing between the methods.

Methods:

We conducted simulations comparing stepwise selection, penalized GLMM, boosted GLMM, and boosted GEE for variable selection considering main effects and two-way interactions in data with repeatedly measured binary outcomes and evaluate a two-stage approach to reduce bias and error in parameter estimates. We compared these approaches in real data applications: hypothermia during surgery and treatment response in lupus nephritis.

Results:

Penalized and boosted approaches recovered correct predictors and interactions more frequently than stepwise selection. Penalized GLMM recovered correct predictors more often than boosting, but included many spurious predictors. Boosted GLMM yielded parsimonious models and identified correct predictors well at large sample and effect sizes, but required excessive computation time. Boosted GEE was computationally efficient and selected relatively parsimonious models, offering a compromise between computation and parsimony. The two-stage approach reduced the bias and error in regression parameters in all approaches.

Conclusion:

Penalized and boosted approaches are effective for variable selection in data with clustered binary outcomes. The two-stage approach reduces bias and error and should be applied regardless of method. We provide guidance for choosing the most appropriate method in real applications.

Intraoperative thermal insulation in off-pump coronary artery bypass grafting surgery: a prospective, double blind, randomized controlled, single-center study

Background

About 50% patients who underwent off-pump coronary artery bypass grafting (OPCAB) experienced perioperative hypothermia. Pre-warming and intraoperative infusion of amino acid injection are the most popular perioperative insulation measures in recent years, but neither of them can completely prevent intraoperative hypothermia. The objective is to investigate the effect of preoperative warming and/or intraoperative infusion of amino acid injection on body temperature in patients undergoing OPCAB.

Methods

A prospective, double blind, randomized controlled, single-center study. Seventy-two patients were randomly divided into 4 groups: control group, pre-warming group, amino-acid group and multi-mode group. Pre-warming and multi-mode group were pre-heated with warming blankets and forced-air warming system before induction. After that, amino-acid and multi-mode group were infused with 18-amino acid solution. The perioperative temperature and complications were monitored.

Results

The temperature of control and amino-acid group decreased significantly, but amino-acid group recovered to preoperative level faster. The temperature of pre-warming group was stable, and that in multi-mode group increased at 60 min after the start of surgery. There was a significant difference in temperature at each time, and no difference in the incidence of complications between the groups.

Conclusions

Preoperative warming and/or intraoperative infusion of amino acid injection can effectively reduce hypothermia in OPCAB surgery. Pre-warming before anesthesia is more effective, and the combination of the two methods has the best effect.

Prevention of Prosthetic Joint Infection: From Traditional Approaches towards Quality Improvement and Data Mining

A projected increased use of total joint arthroplasties will naturally result in a related increase in the number of prosthetic joint infections (PJIs). Suppression of the local peri-implant immune response counters efforts to eradicate bacteria, allowing the formation of biofilms and compromising preventive measures taken in the operating room. For these reasons, the prevention of PJI should focus concurrently on the following targets: (i) identifying at-risk patients; (ii) reducing “bacterial load” perioperatively; (iii) creating an antibacterial/antibiofilm environment at the site of surgery; and (iv) stimulating the local immune response. Despite considerable recent progress made in experimental and clinical research, a large discrepancy persists between proposed and clinically implemented preventative strategies. The ultimate anti-infective strategy lies in an optimal combination of all preventative approaches into a single “clinical pack”, applied rigorously in all settings involving prosthetic joint implantation. In addition, “anti-infective” implants might be a choice in patients who have an increased risk for PJI. However, further progress in the prevention of PJI is not imaginable without a close commitment to using quality improvement tools in combination with continual data mining, reflecting the efficacy of the preventative strategy in a particular clinical setting.

The Impact of Intraoperative Hypothermia on Blood Loss and Allogenic Blood Transfusion in Total Knee and Hip Arthroplasty: A Retrospective Study

Background

Total joint arthroplasty (TJA) usually leads to substantial blood loss, which may cause allogenic blood transfusion. Hypothermia occurring during operation has been reported to increase blood loss and transfusion rates in nonorthopedic cohorts. However, the relationship between intraoperative hypothermia and blood loss remains controversial in patients undergoing orthopedic surgeries. The aims of this study were to investigate the incidence of hypothermia and identify the impact of intraoperative body temperature and hypothermia on blood loss and transfusion rates in total knee and hip arthroplasty (TKA and THA, respectively).

Methods

This retrospective study enrolled 616 consecutive patients, who underwent primary unilateral TKA or THA at our institution during the period from April 2012 to July 2014. The occurrence of a temperature below 36°C during the operation was documented to identify the incidence of hypothermia. Univariate analysis was performed to find the risk factors for hypothermia. Multiple regression analysis and multivariate logistic regression analysis were employed to explore the association of intraoperative temperature and hypothermia with intraoperative blood loss and perioperative blood transfusion.

Results

The incidence of intraoperative hypothermia was 13.5%, 14.0%, and 13.1% in TJA, TKA, and THA, respectively. Intraoperative temperature (P = 0.045, P = 0.006) and hypothermia (P = 0.042, P < 0.001) were associated with intraoperative blood loss and perioperative transfusion in TKA. Intraoperative temperature (P = 0.002) was negatively related to the amount of blood loss, and hypothermia (P = 0.031) was the independent risk factor for transfusion in THA.

Conclusion

Intraoperative hypothermia is associated with increased blood loss and transfusion rates in TJA. Efforts should be made to maintain normothermia during operation in these patients.