Prevalence and multivariable factors associated with inadvertent intraoperative hypothermia in video-assisted thoracoscopic surgery: a single-center retrospective study

Development and validation of an intraoperative hypothermia nomograph model for patients undergoing video-assisted thoracoscopic lobectomy: a retrospective study

This study aimed to develop and internally validate a nomogram model for assessing the risk of intraoperative hypothermia in patients undergoing video-assisted thoracoscopic (VATS) lobectomy. This study is a retrospective study. A total of 530 patients who undergoing VATS lobectomy from January 2022 to December 2023 in a tertiary hospital in Wuhan were selected. Patients were divided into hypothermia group (n = 346) and non-hypothermia group (n = 184) according to whether hypothermia occurred during the operation. Lasso regression was used to screen the independent variables. Logistic regression was used to analyze the risk factors of hypothermia during operation, and a nomogram model was established. Bootstrap method was used to internally verify the nomogram model. Receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the model. Calibration curve and Hosmer Lemeshow test were used to evaluate the accuracy of the model. Decision curve analysis (DCA) was used to evaluate the clinical utility of the model. Intraoperative hypothermia occurred in 346 of 530 patients undergoing VATS lobectomy (65.28%). Logistic regression analysis showed that age, serum total bilirubin, inhaled desflurane, anesthesia duration, intraoperative infusion volume, intraoperative blood loss and body mass index were risk factors for intraoperative hypothermia in patients undergoing VATS lobectomy (P < 0.05). The area under ROC curve was 0.757, 95% CI (0.714-0.799). The optimal cutoff value was 0.635, the sensitivity was 0.717, and the specificity was 0.658. These results suggested that the model was well discriminated. Calibration curve has shown that the actual values are generally in agreement with the predicted values. Hosmer-Lemeshow test showed that χ2 = 5.588, P = 0.693, indicating that the model has a good accuracy. The DCA results confirmed that the model had high clinical utility. The nomogram model constructed in this study showed good discrimination, accuracy and clinical utility in predicting patients with intraoperative hypothermia, which can provide reference for medical staff to screen high-risk of intraoperative hypothermia in patients undergoing VATS lobectomy.

A multi-center study to predict the risk of intraoperative hypothermia in gynecological surgery patients using preoperative variables

OBJECTIVES

Hypothermia is highly common in patients undergoing gynecological surgeries under general anesthesia, so the length of hospitalization and even the risk of mortality are substantially increased. Our aim was to develop a simple and practical model to preoperatively identify gynecological surgery patients at risk of intraoperative hypothermia.

METHODS

In this retrospective study, we collected data from 802 patients who underwent gynecological surgery at three medical centers from June 2022 to August 2023. We further allocated the patients to a training group, an internal validation group, or an external validation group. The preliminary predictive factors for intraoperative hypothermia in gynecological patients were determined using the least absolute shrinkage and selection operator (LASSO) method. The final predictive factors were subsequently identified through multivariate logistic regression analysis, and a nomogram for predicting the occurrence of hypothermia was established.

RESULTS

A total of 802 patients were included, with 314 patients in the training cohort (mean age 48.5 ± 12.6 years), 130 patients in the internal validation cohort (mean age 49.9 ± 12.5 years), and 358 patients in the external validation cohort (mean age 47.6 ± 14.0 years). LASSO regression and multivariate logistic regression analyses indicated that body mass index, minimally invasive surgery, baseline heart rate, baseline body temperature, history of previous surgery, and aspartate aminotransferase level were associated with intraoperative hypothermia in gynecological surgery patients. This nomogram was constructed based on these six variables, with a C-index of 0.712 for the training cohort.

CONCLUSIONS

We established a practical predictive model that can be used to preoperatively predict the occurrence of hypothermia in gynecological surgery patients.

CLINICAL TRIAL REGISTRATION

chictr.org.cn, identifier ChiCTR2300071859.

Perioperative hypothermia in robotic-assisted thoracic surgery: Incidence, risk factors, and associations with postoperative outcomes

OBJECTIVE

Inadvertent perioperative hypothermia has been associated with poor surgical outcomes. The purpose of this study was to evaluate the incidence and associated postoperative complications of inadvertent perioperative hypothermia in patients undergoing robotic-assisted thoracic surgery lung resections.

METHODS

This was a single-center, retrospective cohort study evaluating all consecutive patients who underwent robotic-assisted thoracic surgery lung resection between January 1, 2021, and November 30, 2022. Temperatures were measured at 5 time points: preprocedure unit, anesthesia induction, 30 minutes postinduction, extubation, and recovery room arrival. Temperature changes were calculated at each interval. Adjusted and unadjusted comparison was performed between those who experienced varying levels of inadvertent perioperative hypothermia (Hypothermia I: <36 °C, Hypothermia II: <35.5 °C, and Hypothermia III: <35 °C) and those who did not.

RESULTS

A total of 313 patients were included, and 201 (64.2%) lobectomies, 50 (16.0%) segmentectomies, and 62 (19.8%) wedge resections were performed. Across all patients, 291 (93.0%) had a temperature less than 36 °C, 195 (62.3%) had a temperature less than 35.5 °C, and 100 (31.9%) had a temperature less than 35.0 °C. Patients experienced significant temperature change at all intervals (P < .001), with the greatest loss occurring during the preprocedure interval (between leaving preprocedure unit and anesthesia induction). On adjusted analysis, patients who experienced inadvertent perioperative hypothermia less than 35.5 °C were older (odds ratio, 1.03; 95% CI, 1.01-1.05), had lower body mass index (odds ratio, 0.95; 95% CI, 0.87-0.98), and had increasing operative time (odds ratio, 1.00; 95% CI, 1.00-1.01). Patients who experienced inadvertent perioperative hypothermia had higher risk-adjusted rates of overall morbidity and infectious postoperative complications.

CONCLUSIONS

The majority of patients undergoing robotic-assisted thoracic surgery lung resections experience some degree of inadvertent perioperative hypothermia and have associated increased rates of 30-day morbidity. Structured and interval-specific interventions should be implemented to decrease rates of inadvertent perioperative hypothermia and subsequent complications.

Factors Influencing the Occurrence of Intraoperative Hypothermia in Patients Undergoing General Anesthesia Intervention: A Study in a Tertiary Care Hospital

BACKGROUND Intraoperative and postoperative hypothermia of patients can be caused by the use of anesthetic drugs and the complicated and time-consuming procedures of interventional surgery. This retrospective study included 184 patients to investigate the incidence and factors associated with hypothermia during intraoperative anesthesia in a single center in China between January and October 2023. MATERIAL AND METHODS A convenient sampling method was used to select 184 patients who underwent general anesthesia intervention in a tertiary hospital in Sichuan Province from January to October 2023 as the study population. The independent factors influencing the occurrence of intraoperative hypothermia were analyzed. A survey was conducted to collect 5 demographic factors, 4 preoperative-related factors, and 10 surgically related factors. According to the occurrence of intraoperative hypothermia, the independent influencing factors of unplanned hypothermia during perioperative period were further analyzed. RESULTS Among 184 patients, 64 (34.78%) experienced perioperative unplanned hypothermia, of which 5 (7.81%) cases occurred before the start of surgery, 7 (10.94%) occurred before the start of surgery after anesthesia, and 52 (81.25%) occurred during surgery. Logistic regression analysis showed that body temperature at the beginning of surgery (P<0.001), set operating room temperature (P<0.001), duration of anesthesia (P=0.006), and age (P=0.001) were independent influencing factors for unplanned hypothermia during perioperative period. CONCLUSIONS The incidence of intraoperative hypothermia is high in patients undergoing general anesthesia interventions. Age, duration of anesthesia, set operating room temperature, and body temperature at the beginning of the operation were independent influencing factors for the occurrence of unplanned hypothermia during the perioperative period.

Measurement and Thermodynamic Modeling of Energy Flux During Intercostal Nerve Cryoablation

INTRODUCTION

Intercostal nerve cryoablation is an increasingly adopted technique to decrease postoperative pain in patients undergoing surgical correction of pectus excavatum (SCOPE). Concerns regarding cryo-induced systemic hypothermia have been raised in pediatric patients; however, assessment of a cooled cryoprobe on body temperature has not been performed. We aimed to determine the energy flux from a maximally cooled cryoprobe and model the possible effects on a whole-body system.

METHODS

To directly measure energy flux, a maximally cooled cryoSPHERE probe (AtriCure, Inc, Mason, OH) was isolated in a well-mixed water bath at 37°C. Real-time temperatures were recorded. Three models were created to estimate intraoperative flux. Perioperative temperatures of 50 patients who received cryoablation during SCOPE were compared to 50 patients who did not receive cryoablation.

RESULTS

Direct calorimetry measured average energy flux of the maximally cooled cryoprobe to be 28 J/s. Thermodynamic modeling demonstrated the following: 1) The highest possible cryoprobe flux is less than estimated basal metabolic rate (BMR) of the average teenager undergoing SCOPE and 2) Flux in a best model of human tissue energy transfer using available literature is far less than the effects of BMR and insensible losses. Clinically, there were no significant differences in the minimum intraoperative, end procedure or first postoperative body temperatures for patients who received cryoablation and those who did not.

CONCLUSIONS

Cryoprobe flux is significantly fewer joules per second than BMR. Furthermore, in a clinical series there were no empiric differences in body temperature due to cryoablation employment, contradicting concerns regarding hypothermia secondary to cryoablation.

Inadvertent perioperative hypothermia and surgical site infections after liver resection

BACKGROUND

In the overall surgical population, inadvertent perioperative hypothermia has been associated with an increased incidence of surgical site infection (SSI). However, recent clinical trials did not validate this notion. This study aimed to investigate the potential correlation between inadvertent perioperative hypothermia and SSIs following liver resection.

METHODS

This retrospective cohort study included all consecutive patients who underwent liver resection between January 2019 and December 2021 at the First Affiliated Hospital, Zhejiang University School of Medicine. Perioperative temperature managements were implemented for all patients included in the analysis. Estimated propensity score matching (PSM) was performed to reduce the baseline imbalances between the normothermia and hypothermia groups. Before and after PSM, univariate analyses were performed to evaluate the correlation between hypothermia and SSI. Multivariate regression analysis was performed to determine whether hypothermia was an independent risk factor for postoperative transfusion and major complications. Subgroup analyses were performed for diabetes mellitus, age > 65 years, and major liver resection.

RESULTS

Among 4000 patients, 2206 had hypothermia (55.2%), of which 150 developed SSI (6.8%). PSM yielded 1434 individuals in each group. After PSM, the hypothermia and normothermia groups demonstrated similar incidence rates of SSI (6.3% vs. 7.0%, P = 0.453), postoperative transfusion (13.3% vs. 13.7%, P = 0.743), and major complications (9.0% vs. 10.1%, P = 0.309). Univariate regression analysis revealed no significant effects of hypothermia on the incidence of SSI in the group with the highest hypothermia exposure [odds ratio (OR) = 1.25, 95% confidence interval (CI): 0.84-1.87, P = 0.266], the group with moderate exposure (OR = 1.00, 95% CI: 0.65-1.53, P = 0.999), or the group with the lowest exposure (OR = 1.11, 95% CI: 0.73-1.65, P = 0.628). The subgroup analysis revealed similar results. Regarding liver function, patients in the hypothermia group demonstrated lower γ-glutamyl transpeptidase (37 vs. 43 U/L, P = 0.001) and alkaline phosphatase (69 vs. 72 U/L, P = 0.016). However, patients in the hypothermia group exhibited prolonged activated partial thromboplastin time (29.2 vs. 28.6 s, P < 0.01).

CONCLUSIONS

In our study of patients undergoing liver resection, we found no significant association between mild perioperative hypothermia and SSI. It might be due to the perioperative temperature managements, especially active warming measures, which limited the impact of perioperative hypothermia on the occurrence of SSI.

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.

Assessing the Precision of Surgery Duration Estimation: A Retrospective Study

Background and Objectives

The operating room (OR) is considered the highest source of cost and earnings. Therefore, measuring OR efficiency, which means how time and resources are allocated precisely for their intended purposes in the operating room is crucial. Both overestimation and underestimation negatively impact OR efficiency Therefore, hospitals defined metrics to Measuring OR Effeciency. Many studies have discussed OR efficiency and how surgery scheduling accuracy plays a vital role in increasing OR efficiency. This study aims to evaluate OR efficiency using surgery duration accuracy.

Methods

This retrospective, quantitative study was conducted at King Abdulaziz Medical City. We extracted data on 97,397 surgeries from 2017 to 2021 from the OR database. The accuracy of surgery duration was identified by calculating the duration of each surgery in minutes by subtracting the time of leaving the OR from the time of entering the OR. Based on the scheduled duration, the calculated durations were categorized as either underestimation or overestimation. Descriptive and bivariate analyses (Chi-square test) were performed using the Statistical Package for the Social Sciences (SPSS) software.

Results

Sixty percent out of the 97,397 surgeries performed were overestimated compared to the time scheduled by the surgeons. Patient characteristics, surgical division, and anesthesia type showed statistically significant differences (p <0.05) in their OR estimation.

Conclusion

Significant proportion of procedures have overestimated. This finding provides insight into the need for improvement.

Recommendations

It is recommended to enhance the surgical scheduling method using machine learning (ML) models to include patient characteristics, department, anesthesia type, and even the performing surgeon increases the accuracy of duration estimation. Then, evaluate the performance of an ML model in future studies.

Risk factors and prediction model for inadvertent intraoperative hypothermia in patients undergoing robotic surgery: a retrospective analysis

This study explored the risk factors and established a prediction model for intraoperative hypothermia (IOH) in patients undergoing robotic surgery. We conducted a retrospective survey of patients undergoing elective robotic surgery at the China-Japan Union Hospital of Jilin University during June 2020-October 2021 using institutional medical records. Intraoperative core temperatures and potential influencing factors were collected, and regression analyses were used to assess the risk factors for IOH and establish a prediction model for the incidence of IOH. Overall, 833 patients who underwent robotic surgery were included in the final analysis; IOH was observed in 344 patients (incidence, 0.41; 95% confidence interval [CI] 0.38-0.45). A higher body mass index (BMI) and baseline core temperature were protective factors for IOH. A final prediction model for IOH was developed based on the determining factors with an area under the receiver operating characteristic curve of 0.85 under fivefold cross validation (95% CI 0.83-0.88). Accordingly, a lower BMI and baseline core temperature, thoracic surgeries, morning surgeries, and surgeries with longer durations were risk factors for IOH during robotic surgeries. Our prediction model has an excellent discrimination ability for predicting IOH in robotic surgeries.

The effects of prolonged intraoperative hypothermia on patient outcomes in immediate implant-based breast reconstruction

BACKGROUND

The importance of thermoregulation in surgical procedures has become a recent focus for anesthesiologists and surgeons to improve patient outcomes. In breast surgery, maintenance of normothermia has been shown to reduce surgical-site infections. However, there is a paucity of information evaluating the relationship between intraoperative core body temperatures and reconstructive surgical outcomes.

METHODS

A retrospective review of patients who underwent immediate breast reconstruction following mastectomy from 2015 to 2020 was performed. Patients were classified into a majority normothermic (NT) group if patients spent greater than half of the operative time ≥36 °C or a majority hypothermic (HT) group if patients spent greater than or equal to half of the operative time <36 °C. Patient demographics, comorbidities, surgical techniques, and postoperative complications were recorded. Complications were classified according to the Clavien-Dindo Classification. Univariate and multivariate statistics were used to assess significant relationships.

RESULTS

A total of 329 patients met inclusion criteria, of which 174 were in the NT group and 155 were in the HT group, yielding 302 and 264 total breasts, respectively. There was no significant difference in rates of infection (p = 1.0), seroma (p = 0.27), hematoma (p = 0.61), or wound dehiscence (p = 1.0). However, patients in the HT group had significantly more overall ischemic complications (p = 0.009) and, specifically, grade IIIb ischemic complications (p = 0.04). After controlling for tobacco use, body mass index, mastectomy pattern, radiation, operating surgeon, and mastectomy weight, multivariate analysis showed increased ischemic complications in the HT group (p = 0.04).

CONCLUSION

Prolonged intraoperative hypothermia can increase the risk for the development of ischemic wounds such as tissue necrosis or eschar formation that require operative intervention. This presents reconstructive complications that increase both patient and health system burdens that could be addressed through the maintenance of normothermia. Further studies using real-time flap temperature would provide more accurate insight into the relationship between temperature and implant-based breast reconstruction.

Thoracic Paravertebral Block Decreased Body Temperature in Thoracoscopic Lobectomy Patients: A Randomized Controlled Trial

Purpose

Thoracic paravertebral block (TPVB) may be highly beneficial for thoracoscopic lobectomy patients, but it may increase the risk of hypothermia. Apart from its anesthetic-reducing effects, this randomized controlled trial aimed to investigate the hypothermic effect of TPVB, and thus optimize its clinical use.

Patients and methods

Adult patients were randomly allocated to two groups: TPVB + general anesthesia (GA) group or GA group. In the TPVB+GA group, the block was performed after GA induction by an experienced but unrelated anesthesiologist. Both the lower esophageal and axillary temperature were recorded at the beginning of surgery (T₀) and every 15 min thereafter (T₁-T₈), and the end of surgery (T_p). The primary outcome was the lower esophageal temperature at T_p. The secondary outcomes included lower esophageal temperature from T₀-T₈ and axillary temperature from T₀-T_p. The total propofol, analgesics, and norepinephrine consumption and the incidence of adverse events were also recorded.

Results

Forty-eight patients were randomly allocated to the TPVB+GA (n=24) and GA (n=24) groups. The core temperature at the end of the surgery was lower in the TPVB+GA group than the GA group (35.90±0.30°C vs 36.35±0.33°C, P<0.001), with a significant difference from 45 min after the surgery began until the end of the surgery (P<0.05). In contrast, the peripheral temperature showed a significant difference at 60 min after the surgery began till the end (P<0.05). TPVB+GA exhibited excellent analgesic and sedative-sparing effects compared to GA alone (P<0.001), though it increased norepinephrine consumption due to hypotension (P<0.001).

Conclusion

Although thorough warming strategies were used, TPVB combined with GA remarkably reduced the body temperature, which is an easily neglected side effect. Further studies on the most effective precautions are needed to optimize the clinical use of TPVB.

An Overview of the Implications for Perianesthesia Nurses in terms of Intraoperative Changes in Temperature and Factors Associated with Unintentional Postoperative Hypothermia

Patients undergo surgery and anaesthesia on a daily basis across the United States and throughout the world. A major source of worry for these patients continues to be inadvertent hypothermia, once core temperature <36°C (96.8°F). Despite well-documented adverse physiological consequences, anaesthesia nurses continue to have a difficult task in keeping patient warmth pre-/peri-/post-surgical procedure. Thermostasis within postoperative patient necessitates the collaboration of many individuals. In order to provide safe and high-quality treatment, it is essential to use the most up-to-date data to guide therapeutic procedures targeted at achieving balance body temperature in surgical patients. Providing a review of the physiology of perioperative temperature variations and the comorbidities linked with accidental intraoperative hypothermia, this article will also provide preventive and treatment methods.

Risk Factors for Postoperative Hypothermia in Patients Undergoing Robot-Assisted Gynecological Surgery: A Retrospective Cohort Study

Since postoperative hypothermia increases the morbidity and mortality rates of surgery, identifying its risk factors is an important part of perioperative management. Considering the increasing demand for robot-assisted surgery and other characteristics of conventional laparoscopic surgery, identifying the risk factors for hypothermia in robot-assisted surgery is necessary. However, this has not yet been clearly established. This study aimed to identify the risk factors and incidence rate of postoperative hypothermia in patients undergoing robot-assisted gynecological surgery. In total, 516 patients aged ≥ 19 years undergoing robot-assisted gynecological surgery at a single university hospital between January 2018 and November 2020 were retrospectively analyzed. Postoperative hypothermia was defined as 36.0°C or lower body temperature at the end of the surgery, and multivariate logistic regression analysis was performed to identify the risk factors for postoperative hypothermia. Among the 516 patients, the incidence rate of postoperative hypothermia was 28.1% in 145 patients. The independent risk factors for postoperative hypothermia included body mass index ≤ 22.9 kg/m², baseline heart rate ≤ 73 rate/min, baseline body temperature ≤ 36.8°C, use of intraoperative nicardipine, and amount of administered intravenous fluid larger than 800 mL. Therefore, to prevent hypothermia in patients undergoing robot-assisted gynecological surgery, these risk factors must be considered.

Risk Prediction Models for Inadvertent Intraoperative Hypothermia: A Systematic Review

PURPOSES

Inadvertent intraoperative hypothermia (core temperature <36°C) is a common surgical complication with several adverse events. Hypothermia prediction models can be a tool for providing the healthcare staff with information on the risk of inadvertent hypothermia. Our systematic review aimed to identify, demonstrate, and evaluate the available intraoperative hypothermia risk prediction models in surgical populations.

DESIGN

This study is a systematic review of literature.

METHODS

We systematically searched multiple databases (Ovid MEDLINE, Web of Science, Embase, and Cochrane Center Register of Controlled Trials). Two reviewers independently examined abstracts and the full text for eligibility. Data collection was guided by the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS checklist), and methodological quality and applicability were assessed by the Prediction model Risk Of Bias ASsessment Tool (PROBAST).

FINDINGS

A total of 3,672 references were screened, of which eight articles were included in this study. All the models had a high risk of bias since most of them lacked model validation. Also, they failed to report the model performance and final model presentations, which restricted their clinical application.

CONCLUSIONS

The researchers should present models in a more standard way and improve the existing models to increase their predictive values for clinical application.

Risk factors for inadvertent intraoperative hypothermia in patients undergoing laparoscopic surgery: A prospective cohort study

Background

Inadvertent intraoperative hypothermia is frequent during open surgeries; however, few studies on hypothermia during laparoscopic abdominal surgery have been reported. We aimed to investigate the incidence and risk factors for hypothermia in patients undergoing laparoscopic abdominal surgery.

Methods

This single-center prospective cohort observational study involved patients undergoing laparoscopic surgery between October 2018 and June 2019. Data on core body temperature and potential variables were collected. A multivariate logistic regression analysis was performed to identify the risk factors associated with hypothermia. A Cox regression analysis was used to verify the sensitivity of the results.

Results

In total, 690 patients were included in the analysis, of whom 200 (29.0%, 95% CI: 26%−32%) had a core temperature < 36°C. The core temperature decreased over time, and the incident hypothermia increased gradually. In the multivariate logistic regression analysis, age (OR = 1.017, 95% CI: 1.000–1.034, P = 0.050), BMI (OR = 0.938, 95% CI: 0.880–1.000; P = 0.049), baseline body temperature (OR = 0.025, 95% CI: 0.010–0.060; P < 0.001), volume of irrigation fluids (OR = 1.001, 95% CI: 1.000–1.001, P = 0.001), volume of urine (OR = 1.001, 95% CI: 1.000–1.003, P = 0.070), and duration of surgery (OR = 1.010, 95% CI: 1.006–1.015, P < 0.001) were significantly associated with hypothermia. In the Cox analysis, variables in the final model were age, BMI, baseline body temperature, volume of irrigation fluids, blood loss, and duration of surgery.

Conclusions

Inadvertent intraoperative hypothermia is evident in patients undergoing laparoscopic surgeries. Age, BMI, baseline body temperature, volume of irrigation fluids, and duration of surgery are significantly associated with intraoperative hypothermia.

Intraoperative hypothermia in patients undergoing Total knee arthroplasty: a cross-sectional study from a developing country

Background

Intraoperative hypothermia is associated with various risk factors, morbidity, and mortality in patients undergoing total knee arthroplasty (TKA), increasing the emotional and financial burden on patients. This study aimed to identify risk factors of intraoperative hypothermia in patients undergoing TKA.

Materials and methods

All adult patients (⩾18 years) who underwent TKA from January 2016 to December 2017 at a tertiary-care hospital in Pakistan were included in this retrospective, cross-sectional study. Temperature < 36 °C was defined as hypothermia.

Results

The study included 286 patients (77.6% female) with a mean age of 61.4 ± 10.4 years. The overall proportion of intraoperative hypothermia was 26.6%. Of the total patients, 66.1% underwent bilateral TKA whereas 33.9% underwent unilateral TKA. 73.8% of the patients were ASA Level 2. Only 13.3% of patients had postoperative hypothermia.

Conclusion

Intraoperative hypothermia was significantly associated with age, bilateral procedure, ASA level and postoperative hypothermia in patients undergoing TKA. The surgeon and the operative team should be aware of the risk factors and the adverse outcomes associated with intraoperative hypothermia, especially in resource constrained settings to plan preventive strategies.

Trial registration

This study was retrospectively registered on ClinicalTrials.gov on 3rd October 2020. The registration ID is NCT04575246.

Comparison of upper and lower body forced air blanket to prevent perioperative hypothermia in patients who underwent spinal surgery in prone position: A randomized controlled trial

Background

We compared upper- and lower-body forced-air blankets in terms of their ability to prevent perioperative hypothermia, defined as a reduction in body temperature to < 36.0°C, during the perioperative period in patients undergoing spine surgery in the prone position.

Methods

In total, 120 patients scheduled for elective spine surgery under general anesthesia were divided into an upper-warming group (n = 60) and a lower-warming group (n = 60). After inducing anesthesia and preparing the patient for surgery, including prone positioning, the upper and lower bodies of the patients in the upper- and lower-warming groups, respectively, were warmed using a forced-air warmer with specified upper and lower blankets. Body temperature was measured using a tympanic membrane thermometer during the pre- and post-operative periods and using a nasopharyngeal temperature probe during the intraoperative period. Patients were evaluated in terms of shivering, thermal comfort, and satisfaction in the post-anesthesia care unit (PACU).

Results

The incidence of intraoperative and postoperative hypothermia was lower in the upper-warming group than in the lower-warming group ([55.2% vs. 75.9%, P = 0.019] and [21.4% vs. 49.1%, P = 0.002]). Perioperative body temperature was higher in the upper-warming group (P < 0.001). However, intraoperative blood loss, postoperative thermal comfort scale and shivering scores, patient satisfaction, and PACU duration were similar in the two groups.

Conclusions

The upper-body blanket was more effective than the lower-body blanket for preventing perioperative hypothermia in patients who underwent spine surgery in the prone position.

Correlation between the Perfusion Index and Intraoperative Hypothermia: A Prospective Observational Pilot Study

Background and Objectives: We examined the association between the baseline perfusion index (PI) and changes in intraoperative body temperature during general anesthesia. The PI reflects the peripheral perfusion state. The PI may be associated with changes in body temperature during general anesthesia because the degree of redistribution of body heat from the central to the peripheral compartment varies depending on the peripheral perfusion state. Materials and Methods: Thirty-eight patients who underwent brain surgery were enrolled in this study. The baseline PI and body temperature of the patients were measured on entering the operating room. Body temperature was recorded every 15 min after induction of anesthesia using an esophageal temperature probe. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for intraoperative hypothermia. Results: Eighteen patients (47 %) developed hypothermia intraoperatively. The baseline PI was significantly lower among patients in the hypothermia group (1.8 ± 0.7) than among those in the normothermia group (3.0 ± 1.2) (P < 0.001). The baseline PI and body temperature were independently associated with intraoperative hypothermia (PI: odds ratio [OR], 0.270; 95% confidence interval [CI], 0.105-0.697; P = 0.007, baseline body temperature: OR, 0.061; 95% CI, 0.005-0.743; P = 0.028). Conclusions: This study showed that low baseline PI was the factor most related to the development of intraoperative hypothermia. Future studies should consider the PI as a predictor of intraoperative hypothermia.

Analysis of the Risk Factors for the Onset of Postoperative Hypothermia in the Postanesthesia Care Unit

PURPOSE

Recent studies on hypothermia typically focused on a single anesthesia method or a particular surgical procedure. Although there are multiple risk factors leading to hypothermia, such as the use of cold solutions or nonhumidified and nonheated anesthetic gases, few studies have reported the incidence of postoperative hypothermia among patients in the postanesthesia care unit (PACU).

DESIGN

This is a retrospective analysis of patients who underwent surgery and were admitted to the PACU immediately after surgery at the Fourth Affiliated Hospital, College of Medicine, Zhejiang University, from September 2018 to March 2019.

METHODS

Patient data were collected and analyzed in two groups to understand the factors affecting the occurrence of hypothermia. Hypothermia was defined as a core temperature of less than 36°C. On the basis of body temperature, patients in the PACU were divided into hypothermic and nonhypothermic groups. Factors influencing hypothermia were studied by the univariate method, followed by logistic regression analysis to identify the risk factors for hypothermia onset.

FINDINGS

Of a total of 1,788 patients were enrolled in the study, 113 (6.32%) exhibited hypothermia (<36°C) in the PACU. The hypothermic and nonhypothermic groups displayed significant differences (P < .05) in the anesthesia method used as well as the American Society of Anesthesiologists physical classification status. The body temperature at the time the patients were admitted to the operating room influenced the occurrence of postoperative hypothermia (P < .01). These parameters were recognized as independent risk factors for postoperative hypothermia in the PACU.

CONCLUSIONS

Significant risk factors for the onset of hypothermia were general anesthesia and higher American Society of Anesthesiologists grade. However, epidural anesthesia was found to have a protective effect.

Effects of a preoperative forced-air warming system for patients undergoing video-assisted thoracic surgery: A randomized controlled trial

BACKGROUND

The incidence of intraoperative hypothermia is still high despite the proposal of different preventive measures during thoracoscopic surgery. This randomized control study evaluated the effects of 30-minute prewarming combined with a forced-air warming system during surgery to prevent intraoperative hypothermia in patients undergoing video-assisted thoracic surgery under general anesthesia combined with erector spinae nerve block.

METHODS

Ninety-eight patients were randomly and equally allocated to prewarming or warming groups (n = 49 each). The primary outcome was the incidence of intraoperative hypothermia. Secondary outcomes were core temperature, irrigation and infused fluid, estimated blood loss, urine output, type of surgery, intraoperative anesthetic dosage, hemodynamics, recovery time, the incidence of postoperative shivering, thermal comfort, postoperative sufentanil consumption and pain intensity, patient satisfaction, and adverse events.

RESULTS

The incidence of intraoperative hypothermia was significantly lower in the prewarming group than the warming group (12.24% vs 32.65%, P = .015). Core temperature showed the highest decrease 30 minutes after surgery start in both groups; however, the rate was lower in the prewarming than in the warming group (0.31 ± 0.04°C vs 0.42 ± 0.06°C, P < .05). Compared with the warming group, higher core temperatures were recorded for patients in the prewarming group from T1 to T6 (P < .05). Significantly fewer patients with mild hypothermia were in the prewarming group (5 vs 13, P = .037) and recovery time was significantly reduced in the prewarming group (P < .05). Although the incidence of postoperative shivering was lower in the prewarming group, it was not statistically significant (6.12% vs 18.37%, P = .064). Likewise, the shivering severity was similar for both groups. Thermal comfort was significantly increased in the prewarming group, although patient satisfaction was comparable between the 2 groups (P > .05). No adverse events occurred associated with the forced-air warming system. Both groups shared similar baseline demographics, type of surgery, total irrigation fluid, total infused fluid, estimated blood loss, urine output, intraoperative anesthetic dosage, hemodynamics, duration of anesthesia and operation time, postoperative sufentanil consumption, and pain intensity.

CONCLUSION

In patients undergoing video-assisted thoracic surgery, prewarming for 30 minutes before the induction of anesthesia combined with a forced-air warming system may improve perioperative core temperature and the thermal comfort, although the incidence of postoperative shivering and severity did not improve.