Abstract
Background
Our hypothesis was that total intravenous anesthesia (TIVA) is associated with an increase in hypothermia.
Methods
Inclusion criteria were patients from the National Anesthesia Clinical Outcomes Registry undergoing a general anesthetic during 2019. Data collected included patient age, sex, American Society of Anesthesiologists physical status classification system score (ASAPS), duration of anesthetic, use of TIVA, type of procedure, and hypothermia. Continuous variables were compared using Student’s t test or Mann Whitney rank sum as appropriate. Mixed effects multiple logistic regression was performed to determine the association between independent variables and hypothermia.
Results
There was a low incidence of hypothermia (1.2%). Patients who became hypothermic were older, had a higher median ASAPS, and had a higher rate of TIVA. TIVA patients had a significantly increased odds for hypothermia when controlling for covariates. Patients undergoing obstetrical, thoracic, or radiological procedures had increased odds for hypothermia. In a matched cohort subset, TIVA was associated with a greater rate and increased odds for hypothermia.
Conclusions
The novel and noteworthy finding was the association between TIVA and perianesthesia hypothermia. Thoracic, radiologic, and obstetrical procedures were associated with greater rates of and odds for hypothermia. Other identified factors can help to stratify patients for risk for hypothermia.
Keywords: Anesthesia, hypothermia, propofol
Hypothermia in the perianesthetic period has been linked to prolonged duration of intensive care unit admission, greater cost of care, and a negative impact on perioperative outcomes.1–3 The Centers for Medicare and Medicaid Services Quality Payment Program has a defined Merit-Based Incentive Payment System (MIPS) that tracks quality metrics specific to each specialty.4 One of the indicators for anesthesiology, MIPS 424, relates to patient temperature management. The standard for the metric is defined as “patients, regardless of age, who undergo surgical or therapeutic procedures under general or neuraxial anesthesia of 60 minutes duration or longer for whom at least one body temperature greater than or equal to 35.5°C was achieved within the 30 minutes immediately before or the 15 minutes immediately after anesthesia end time.”5 The risk for developing perianesthesia hypothermia is associated with health status, volume of crystalloid infused, the use of general anesthesia (GA), and total duration of anesthesia.6,7
Previous comparisons of the risk for hypothermia between total intravenous anesthesia (TIVA) and non-TIVA GA have been limited and concluded no difference in heat dissipation between volatile gas anesthetics (VA) and propofol TIVA when used for maintenance of GA.8–11 All of these previous studies were limited to specific subsets of surgical patients who could be significantly draped and provided active rewarming via a forced air system (lumbar disc surgery patients8 or other neurosurgical patients9,10). The degree of hypothermia in these cases may have been low and led to a negative result. One other report assessed hypothermia risk between TIVA and non-TIVA in laparoscopic abdominal surgery patients and also concluded no difference.11 In this negative study, there were 25 patients in each arm, with a reported post hoc power of only 52%. The small sample size and nature of the surgery may have made any difference in heat loss difficult to detect. There may be other types of procedures with higher risk for hypothermia where a difference between anesthetic techniques might have been detectable.
Despite these negative results, there remains a possibility that TIVA imparts a greater risk for developing hypothermia than VA. TIVA regimens commonly use propofol, which appears to result in differential vasodilation than VA and, as a result, possibly greater heat loss and an increased incidence of hypothermia.12,13 A larger study comparing hypothermia rates between TIVA GA and non-TIVA GA, including various types of surgeries with differing risks for hypothermia, may be better for truly assessing for a difference.
MIPS metric data is collected by the American Society of Anesthesiologists’ Anesthesia Quality Institute’s (AQI) National Anesthesia Clinical Outcomes Registry (NACOR). We used NACOR data to assess for incidence, risk factors for, and outcomes associated with hypothermia, as defined by failure to meet the MIPS 424 standard. Our hypothesis was that TIVA would be associated with an increase in hypothermia compared to non-TIVA GA.
METHODS
Study design and approval
Prior to beginning this study, it was reviewed by the George Washington University Institutional Review Board (GWU IRB). The GWU IRB determined the study was research that was exempt from IRB review under Department of Health and Human Services regulatory category 4 (determination NCR224170). The GW IRB waived the requirement to obtain informed consent, as the data were already deidentified. The authors established a data use agreement with AQI for the use of NACOR data (AQI DUA 983). This manuscript was prepared in accordance with Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.
Study sample and variables
Patient information was extracted from the NACOR dataset. Inclusion criteria were patients in NACOR undergoing GA during calendar year 2019. Data collected included unique case identification number, practice identification number (without identifying key), location identification number (without identifying key), patient age, sex, American Society of Anesthesiologists physical status classification system score (ASAPS), duration of anesthetic, use of TIVA for GA (predefined in NACOR), surgical or procedure category as defined by clinical procedural terminology codes for 2019, emergent or nonemergent status of procedure, MIPS 424, reported perioperative mortality, and postanesthesia care reintubation. Exclusion criteria were emergency surgery, a lack of documented performance met or not met for MIPS 424, exclusion or exemption from consideration for MIPS 424, and missing data for age, sex, ASAPS, type of procedure, type of anesthesia, or duration of anesthesia. Patients were also excluded if anesthetic length was <60 minutes (consistent with the definition of MIPS 424 requiring a minimum of 60 minutes in duration, meaning they should have been exempt but MIPS 424 was potentially reported incorrectly). Children <1 year of age were excluded to minimize prematurity or congenital diseases as potential confounders. ASAPS 6 patients were also excluded. The primary outcomes were the rate of and odds for hypothermia after TIVA compared to non-TIVA GA when controlling for covariates. The secondary outcomes were rates of and odds for hypothermia associated with other measurable variables available in the NACOR dataset.
Statistical analysis
Rates were compared between groupings of patients (TIVA vs non-TIVA, hypothermic vs normothermic, etc.) using a chi-square test. Continuous variables were compared between groups using Student’s t test or Mann Whitney rank sum, as appropriate based on normality of distribution or lack thereof. A P value < 0.05 was used to determine statistical significance. A mixed effects multiple logistic regression analysis was performed to determine the association between independent fixed variables and the dependent variable of hypothermia (as defined by MIPS 424 standard not met). Practice identification number was used as a random effect variable to take into account practice or reporting differences between anesthesia groups. An interacting variable was created to account for the interaction of time and the use of TIVA. This variable was incorporated as an independent variable in the regression model.
After analyzing the larger data set, a subgroup was created for a one-to-one propensity-matched cohort analysis. The intent was to further eliminate the influence of practice and reporting variations between anesthesia groups to assess the relationship of type of anesthesia with hypothermia. TIVA patients were matched with a non-TIVA patient for type of procedure (women undergoing dilation and curettage were chosen due to high rate of both hypothermia and TIVA), exact match of practice and location, age (±2 years), ASAPS, and duration of anesthetic (±5 minutes). The rate and odds ratio (OR) for hypothermia were compared between the two groups in the propensity-matched analysis.
RESULTS
In the 2019 NACOR dataset, there were 10,258,836 entries for patients receiving any type of anesthesia, and 1,521,451 patients met all inclusion criteria and lacked any exclusion criteria (Figure 1). There was a low incidence of hypothermia among patients included in the analysis (1.2%) (Table 1). The use of TIVA, increasing age grouping, and higher ASAPS were associated with an increase in rates of hypothermia. Patients who became hypothermic were older (median age 61 years, interquartile range [IQR] 46–71 vs 57, IQR 40–69, P < 0.01), had a higher median ASAPS (3, IQR 2–3 vs 2, IQR 2–3, P < 0.01), and had a higher rate of TIVA (13.8% vs 0.4%, P < 0.01) (Table 2).
Figure 1.
CONSORT flow diagram.
Table 1.
A comparison of hypothermia rates by patient characteristic or procedure type
| Grouping | Characteristic | Normothermic | Hypothermic | P value |
|---|---|---|---|---|
| Total | All patients | 98.8% (1,503,176) | 1.2% (18,275) | |
| TIVA vs non-TIVA | Non-TIVA | 99.0% (1,496,606) | 1.0% (15,762) | <0.01 |
| TIVA | 72.6% (6,660) | 27.4% (2,513) | ||
| Age groups (years) | 1–18 | 99.4% (67,452)* | 0.6% (416)b,c,d,e* | <0.01 |
| 19–49 | 99.0% (487,366)* | 1.0%(4,879)a,c,d,e* | ||
| 50–64 | 98.8% (438,579) | 1.2% (5,369)a,b,d,e | ||
| 65–79 | 98.6% (406,112)* | 1.6% (5,830)a,b,c,e* | ||
| >80 | 98.3% (103,367)* | 1.7% (1781)a,b,c,d* | ||
| ASAPS class | 1 or 2 | 99.1% (823,918) | 0.9% (7,265) | <0.01 |
| 3–5 | 98.4% (679,258) | 1.6% (11,010) | ||
| Sex | Male | 98.9% (669,598) | 1.2% (8,220) | 0.33 |
| Female | 98.8% (833,578) | 1.2% (10,005) | ||
| Procedure | Burn | 96.1% (439)* | 3.9% (18)* | <0.01 |
| Thoracic | 97.7% (173,882)* | 2.3% (4,099)* | ||
| Obstetric | 97.8% (4,427)* | 2.2% (100)* | ||
| Radiological procedures | 98.2% (26,270)* | 1.8% (490)* | ||
| Neck | 98.6% (70,988)* | 1.4% (984)* | ||
| Head | 98.8% (100,796) | 1.2% (1,232) | ||
| Perineum | 98.8% (128,508) | 1.2% (1,592) | ||
| Spine | 98.8% (107,522) | 1.2% (1,293) | ||
| Abdomen | 98.9% (173,882)* | 1.1% (5,038)* | ||
| Upper extremity | 99.2% (166,488)* | 0.8% (1,300)* | ||
| Lower extremity | 99.2% (275,212)* | 0.8% (2,129)* | ||
| Other | 100% (27) | 0 (0) |
ASAPS indicates American Society of Anesthesiologists physical status score; TIVA, total intravenous general anesthesia. Data presented as proportion of each row (N) with adjusted residual value in italics, if applicable. * Residual values > ±2 denoting significantly different.
aSignificantly different from age group 1–18 with P < 0.01.
bSignificantly different from age group 19–49 with P < 0.01.
cSignificantly different from age group 50–64 with P < 0.01.
dSignificantly different from age group 51–79 with P < 0.01.
eSignificantly different from age group >80 with P < 0.01.
Table 2.
A comparison of variables between hypothermic and nonhypothermic patients
| Variable | Hypothermic | Normothermic | P value |
|---|---|---|---|
| Anesthetic duration (min) | 114 (75–150) | 109 (74–165) | <0.01 |
| Age (years) | 61 (46–71) | 57 (40–69) | <0.01 |
| Sex: female | 54.5% | 55.0% | 0.33 |
| ASAPS | 3 (2–3) | 2 (2–3) | <0.01 |
| TIVA | 13.8% | 0.4% | <0.01 |
ASAPS indicates American Society of Anesthesiologists physical status score; TIVA, total intravenous general anesthesia. Data compared using chi-square test for proportions and Mann Whitney U test for continuous variables.
TIVA and hypothermia
A small proportion of patients who underwent GA received TIVA (0.6%) (Table 3). TIVA patients had a significantly higher rate of hypothermia compared to non-TIVA GA patients (27.4% vs 1.0%). There was a shorter median anesthesia duration for patients undergoing TIVA compared to non-TIVA. There was also a higher rate of intrathoracic procedures among patients undergoing TIVA GA compared to non-TIVA (23.0% vs 11.6%, P < 0.01). TIVA patients had a significantly increased odds for hypothermia when controlling for covariates (OR 65.55, 95% confidence interval [CI] 60.57–70.92) (Table 4).
Table 3.
A comparison of TIVA vs non-TIVA patients
| Variable | Non-TIVA | TIVA | P value |
|---|---|---|---|
| N | 1,512,278 | 9,713 | |
| Age (years) | 57(40–69) | 61 (49–62) | <0.01 |
| Anesthesia duration (min) | 105(75–150) | 96 (66–125) | <0.01 |
| Proportion female | 54.1 | 54.4 | 0.18 |
| ASAPS | 2 (2–3) | 3 (2–3) | <0.01 |
| Thoracic procedure | 11.6% | 23.0% | <0.01 |
ASAPS indicates American Society of Anesthesiologists physical status; TIVA, total intravenous general anesthesia. Data presented as median (interquartile range) or proportion among TIVA or non-TIVA. Medians compared using Mann Whitney U test. Ratios compared using chi-square test.
Table 4.
Odds for hypothermia
| Variable | Group | Odds ratio (95% CI) | P value |
|---|---|---|---|
| TIVA | TIVA patients | 65.55 (60.57–70.92) | <0.01 |
| Anesthesia duration (change per 15 min) | 1.04 (1.04–1.04) | <0.01 | |
| TIVA × anesthesia duration (in 15-min blocks) | 0.82 (0.80–0.83) | <0.01 | |
| Age grouping (in years) | 1–18 | Reference | |
| 19–49 | 1.34 (1.21–1.48) | <0.01 | |
| 50–64 | 1.45 (1.30–1.60) | <0.01 | |
| 65–80 | 1.58 (1.40–1.73) | <0.01 | |
| >80 | 1.67 (1.49–1.87) | <0.01 | |
| ASAPS ≥3 | 1.56 (1.47–1.67) | <0.01 | |
| Female gender | 0.99 (0.96–1.02) | 0.70 | |
| Type of procedure | Burn | 2.91 (1.80–4.50) | <0.01 |
| Obstetrical | 1.99 (1.60–2.47) | <0.01 | |
| Thoracic | 1.30 (1.22–1.39) | <0.01 | |
| Head | Reference | ||
| Radiological procedure | 0.95 (0.85–1.06) | 0.35 | |
| Other | 0.04 (0–1.2317) | 0.35 | |
| Neck | 0.92 (0.84–1.0) | 0.05 | |
| Perineum | 0.85 (0.79–0.92) | <0.01 | |
| Abdomen | 0.79 (0.74–0.84) | <0.01 | |
| Spine | 0.76 (0.70–0.82) | <0.01 | |
| Lower extremity | 0.52 (0.48–0.55) | <0.01 | |
| Upper extremity | 0.51 (0.47–0.55) | <0.01 |
ASAPS indicates American Society of Anesthesiologists physical status; CI, 95% confidence interval; TIVA, total intravenous anesthesia. Data analyzed using mixed model logistic regression. Practice identification number was designated a random effect while other variables were included as independent variables of fixed effect.
Procedural factors and hypothermia
There were significantly different rates of hypothermia between types of procedures. The rates of hypothermia were greatest among burn related (3.9%), thoracic (2.3%), and obstetrical procedures (2.2%). Each of these procedures was also associated with increased multivariate odds for hypothermia (burn OR 3.10, 95% CI 1.88–5.0; obstetric OR 2.12, 95% CI 1.69–2.66; thoracic OR 1.38, 95% CI 1.25–1.52) compared to the reference group, patients undergoing surgery of the head.
The odds for hypothermia increased with increased anesthesia duration (OR 1.04, 95% CI 1.04–1.04 per each 15-minute block of duration). There was a significant contribution from the TIVA × time interaction variable on the odds for hypothermia. The adjusted risk for hypothermia among TIVA patients was higher than for non-TIVA patients but decreased with increased anesthesia duration, whereas the adjusted risk for hypothermia among non-TIVA patients was low and increased slowly with increasing anesthesia duration (Figure 2).
Figure 2.
Probability of hypothermia based on duration of anesthesia.
Patient characteristics and hypothermia
The unadjusted rate of hypothermia was directly related to age grouping. Older age groups were at increased risk for hypothermia compared to the reference group, patients ≤18 years. ASAPS ≥ 3 was associated with an increase in odds for hypothermia. Patient sex was not associated with a change in rate or risk for hypothermia.
Matched cohort analysis
There were 33 one-to-one matched pairs identified among women undergoing dilation and curettage. There was a significantly higher rate of hypothermia among TIVA patients (48.5% vs 9.1%, P < 0.01) and greater odds for hypothermia as well (OR 17.8, 95% CI 3.1–102.5, P < 0.01).
DISCUSSION
There was a low rate of perianesthesia hypothermia when measured using failure to achieve the MIPS 424 standard (1.2%). Several factors were associated with odds for hypothermia. Some findings agreed with previous reports. The association between TIVA and hypothermia is novel and potentially noteworthy.
The low incidence of hypothermia as measured by failure to meet MIPS 424 standard was a stark contrast to some of the existing literature. Previous works have reported incidence rates up to 60%, depending on the definition of hypothermia, time of measurement, and patient population.14,15 The likely reason for the difference was that NACOR data captures temperature at one point in time near or after the conclusion of the anesthetic, whereas other reports look at temperature nadir at any point. The overall rate of hypothermia in NACOR was most similar to the findings of Sun et al, who reported a 3.3% rate of hypothermia in 672 propensity-matched patients in the postanesthesia care unit after anesthesia.16 This endpoint was similar to MIPS 424 criteria, which is the attainment of 35.5°C within 30 minutes of the end of the anesthetic. In both patient samples, vasodilating anesthetics had been presumably discontinued for a significant period of time, and patients may also have been rewarmed prior to sampling temperature. This may have led to the lower rate of hypothermia compared to intraoperative nadirs reported by others.
The associations between certain risk factors and hypothermia were similar to those in previous reports. The lowest rate of hypothermia was in the youngest patients. Every successive patient age grouping had a significantly higher incidence rate than younger groupings. Older age had previously been linked to a greater incidence of hypothermia.17 In contrast, neonates had previously been linked to a higher risk for perianethesia hypothermia, even compared to infants.1,18 NACOR data is limited to age in years, so it was challenging to ascertain the exact age of children under 1 year. To remove any confounder, patients <1 were removed from this analysis. Higher ASAPS was associated with an increased risk for hypothermia, in agreement with existing literature.19 Longer duration of anesthesia was associated with increased hypothermia, also consistent with previous reports.20
The association between TIVA and increased hypothermia incidence stands in opposition to existing literature. Previously studied populations, such as neurosurgery patients, may have been at lower risk for hypothermia, thus minimizing any difference resulting from TIVA. NACOR data included a broad list of procedures associated with a heterogeneity of rates of hypothermia. The diversity of procedures, including higher risk ones, combined with the sample size may have allowed for detection of a previously missed relationship.
TIVA may lead to increased hypothermia incidence through several possible mechanisms. One may be the pharmacodynamic properties of commonly used components of a TIVA regimen, such as propofol. The majority of heat loss during anesthesia results from vasodilation and heat redistribution from the core and loss to the environment.21 Conversely, vasoconstriction via pharmacological agents has been shown to reduce heat redistribution during GA.22 Propofol and VA have been shown to induce differing degrees of vasodilation, which could result in differential heat redistribution.12,13 Further, patients sedated in an intensive care unit with VA have a more robust ability to manifest a fever than those sedated with propofol, also supporting the suggestion that some property of propofol may play a role.23
TIVA may also be related to hypothermia through the method of administration, rather than propofol’s pharmacodynamics. The volume of intravenous fluid (IVF) administered during a TIVA compared to non-TIVA GA may play a role. Increased volumes of IVF have been associated with hypothermia.6 While there is no literature to support the assertion that TIVA leads to greater fluid administration, an increase in IVF volume administered due to the need for a carrier fluid is a reasonable assumption and a plausible link between TIVA and hypothermia. NACOR does not contain sufficient data on total IVF administered for analysis.
Another possible etiology may be the pattern of administration of medications with TIVA. Patients may be administered a relatively lower effective dose of VAs compared to propofol due to the ability to measure expired concentration and the well-established concept of minimum alveolar concentration for VAs. Propofol serum levels are not easily estimated and the value at which a patient is amnestic or will not move in response to surgical stimulus is not as well defined, potentially leading to a therapeutic overdose with TIVA relative to the dose of VA administered. This relative overdose may lead to greater vasodilation and greater heat loss. With these two potential etiologies related to medication administration, TIVA may secondarily cause increased hypothermia.
There were several procedural-related risk factors for hypothermia. There was an overall increase in hypothermia with increasing duration of anesthesia. The relationship between duration of anesthesia and hypothermia was different between TIVA and VA patients. There was a far greater difference in hypothermia rates with shorter anesthetic durations. The difference in adjusted risk for hypothermia between the two groups decreased as anesthetic duration increased. This accentuation of the difference in hypothermia risk between TIVA and non-TIVA groups may be the result of either greater vasodilation with propofol compared to an equipotent dose of VA or from a therapeutic overdose of propofol compared to VA, as mentioned above. While the use of MIPS 424 is not equivalent to intraoperative temperature or temperature nadir, it suggests that a difference in temperature regulation occurs between TIVA and non-TIVA early in an anesthetic.
While the accentuated early heat loss among TIVA patients may be the result of pharmacodynamics or administration patterns, there are also a few potential reasons the gap may close over time. First, the decrease in the rate of hypothermia among TIVA patients of increasing anesthesia duration may be related to greater heat regeneration with TIVA. VAs inhibit nonshivering thermogenesis in brown fat whereas propofol does not.24 Nonshivering thermogenesis may play a role in the decreasing rate of hypothermia over time in the TIVA group. Additionally, the lipid emulsion used in commercially available preparations of propofol may aid in thermogenesis. Jeong et al found less hypothermia with lipid emulsion propofol compared to microemulsion propofol and theorized it was the result of lipid metabolism.25 Alternatively, the difference in hypothermia rates between groups may be related to intraoperative warming strategies. For brief procedures, patients may preferentially be administered TIVA but may also not have an active warming strategy utilized, whereas in longer procedures, patients may preferentially receive VA and be actively warmed. Regardless of the etiology or limited nature of the conclusion, our finding of an exaggerated difference in hypothermia rates with TIVA of shorter duration is novel and an area for further study. Pharmacology or practice pattern may be contributing to increased hypothermia. Addressing either factor may be an opportunity for improving patient care.
NACOR data also suggested a difference in rates of hypothermia based on the nature of the procedure. Thoracic surgical procedures were associated with greater rates of hypothermia, regardless of TIVA or non-TIVA. This finding is logical since exposure of the thorax likely leads to greater heat loss to the environment than many other procedures involving a less exposed surface area. The exaggerated difference in hypothermia rates between TIVA and non-TIVA among thoracic surgery patients may be due to the exposure of a greater percentage of body surface area, accentuating greater heat dissipation with TIVA. Obstetrical surgeries were also associated with increased hypothermia, while intraabdominal nonobstetrical surgeries were not. This may be mediated by greater blood loss or by a responsive administration of fluids or blood which possibly occurs during obstetrical surgery. Greater blood loss has been linked to greater heat loss and increased rates of hypothermia.7
This study has several limitations. It was performed retrospectively so one cannot conclude causality, only associations. Data were lacking for body mass index, specific medications, blood loss, and fluid or blood administered. Additionally, the endpoint of MIPS 424 doesn’t measure intraoperative temperature nadir or severity of hypothermia. There is also no way to determine the site or method of temperature measurement, as this was not recorded in the database. NACOR also lacks data on the use of patient warming devices. There was also a low incidence of the use of TIVA in the sample, which may signify a difference in patients or procedures that wasn’t accounted for in the analysis despite our best efforts.
TIVA appears to be associated with an increase in perianesthesia hypothermia. Patients should be risk stratified based on patient and procedural factors when deciding to use TIVA. Further studies are indicated. A more advanced database that contains temperature measurements throughout the anesthetic and site of sampling could allow for a better assessment for hypothermia. Future studies should also focus on high-risk patients undergoing high-risk procedures, both of which we have identified. They should also compare procedures of various durations to assess for a change in impact from TIVA with different durations. Further, other factors including room temperature and the use of warming strategies should be assessed.
Disclosure statement/Funding
The authors report no funding or conflicts of interest.
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