The epidemiology of spontaneous fever and hypothermia on admission of brain injury patients to intensive care units: a multicenter cohort study

Clinical article

Full access

Object

Fever and hypothermia (dysthermia) are associated with poor outcomes in patients with brain injuries. The authors sought to study the epidemiology of dysthermia on admission to the intensive care unit (ICU) and the effect on in-hospital case fatality in a mixed cohort of patients with brain injuries.

Methods

The authors conducted a multicenter retrospective cohort study in 94 ICUs in the United States. Critically ill patients with neurological injuries, including acute ischemic stroke (AIS), aneurysmal subarachnoid hemorrhage (aSAH), intracerebral hemorrhage (ICH), and traumatic brain injury (TBI), who were older than 17 years and consecutively admitted to the ICU from 2003 to 2008 were selected for analysis.

Results

In total, 13,587 patients were included in this study; AIS was diagnosed in 2973 patients (22%), ICH in 4192 (31%), aSAH in 2346 (17%), and TBI in 4076 (30%). On admission to the ICU, fever was more common among TBI and aSAH patients, and hypothermia was more common among ICH patients. In-hospital case fatality was more common among patients with hypothermia (OR 12.7, 95% CI 8.4–19.4) than among those with fever (OR 1.9, 95% CI 1.7–2.1). Compared with patients with ICH (OR 2.0, 95% CI 1.8–2.3), TBI (OR 1.5, 95% CI 1.3–1.8), and aSAH (OR 1.4, 95% CI 1.2–1.7), patients with AIS who developed fever had the highest risk of death (OR 3.1, 95% CI 2.5–3.7). Although all hypothermic patients had an increased mortality rate, this increase was not significantly different across subgroups. In a multivariable analysis, when adjusted for all other confounders, exposure to fever (adjusted OR 1.3, 95% CI 1.1–1.5) or hypothermia (adjusted OR 7.8, 95% CI 3.9–15.4) on admission to the ICU was found to be significantly associated with in-hospital case fatality.

Conclusions

Fever is frequently encountered in the acute phase of brain injury, and a small proportion of patients with brain injuries may also develop spontaneous hypothermia. The effect of fever on mortality rates differed by neurological diagnosis. Both early spontaneous fever and hypothermia conferred a higher risk of in-hospital death after brain injury.

Abbreviations used in this paper:AIS = acute ischemic stroke; APACHE II = Acute Physiology And Chronic Health Evaluation II; aSAH = aneurysmal subarachnoid hemorrhage; GCS = Glasgow Coma Scale; ICH = intracerebral hemorrhage; ICU = intensive care unit; PI = Project IMPACT; TBI = traumatic brain injury.

Object

Fever and hypothermia (dysthermia) are associated with poor outcomes in patients with brain injuries. The authors sought to study the epidemiology of dysthermia on admission to the intensive care unit (ICU) and the effect on in-hospital case fatality in a mixed cohort of patients with brain injuries.

Methods

The authors conducted a multicenter retrospective cohort study in 94 ICUs in the United States. Critically ill patients with neurological injuries, including acute ischemic stroke (AIS), aneurysmal subarachnoid hemorrhage (aSAH), intracerebral hemorrhage (ICH), and traumatic brain injury (TBI), who were older than 17 years and consecutively admitted to the ICU from 2003 to 2008 were selected for analysis.

Results

In total, 13,587 patients were included in this study; AIS was diagnosed in 2973 patients (22%), ICH in 4192 (31%), aSAH in 2346 (17%), and TBI in 4076 (30%). On admission to the ICU, fever was more common among TBI and aSAH patients, and hypothermia was more common among ICH patients. In-hospital case fatality was more common among patients with hypothermia (OR 12.7, 95% CI 8.4–19.4) than among those with fever (OR 1.9, 95% CI 1.7–2.1). Compared with patients with ICH (OR 2.0, 95% CI 1.8–2.3), TBI (OR 1.5, 95% CI 1.3–1.8), and aSAH (OR 1.4, 95% CI 1.2–1.7), patients with AIS who developed fever had the highest risk of death (OR 3.1, 95% CI 2.5–3.7). Although all hypothermic patients had an increased mortality rate, this increase was not significantly different across subgroups. In a multivariable analysis, when adjusted for all other confounders, exposure to fever (adjusted OR 1.3, 95% CI 1.1–1.5) or hypothermia (adjusted OR 7.8, 95% CI 3.9–15.4) on admission to the ICU was found to be significantly associated with in-hospital case fatality.

Conclusions

Fever is frequently encountered in the acute phase of brain injury, and a small proportion of patients with brain injuries may also develop spontaneous hypothermia. The effect of fever on mortality rates differed by neurological diagnosis. Both early spontaneous fever and hypothermia conferred a higher risk of in-hospital death after brain injury.

Brain injuries from stroke and head trauma are leading causes of morbidity and death in the world.3,27 In patients with these injuries, early fever9 and hypothermia13,29 (dysthermia) and the onset of systemic complications are associated with poor outcomes. Plausible theories of the underlying reasons for disturbance in thermoregulation after brain injury are based on observations in animal models. These findings suggest that potential causes of fever include damage to the hypothalamus, midbrain, or pons by enhanced sympathetic activity; acute or delayed ischemia; toxic blood metabolites; physical distortion; or inflammation.7,34 Accordingly, dysfunction of or damage to these thermoregulatory pathways is common in patients with brain injuries, putting them at increased risk for dysthermia.7,30,34 Because dysthermia is known to be associated with poor outcomes in all forms of brain injury,9,25 early recognition of this condition and modulation of the physiopathological mechanisms leading to dysthermia may be part of strategies aimed at limiting systemic complications, primary and secondary neuronal injury, and improving long-term outcomes.16

Although much is known about the effects of dysthermia on neurological outcomes after brain injury, only limited data based on neurological diagnosis are available for addressing the epidemiology and risk factors of this phenomenon. In particular, little is known about the differential effect of dysthermia on in-hospital case fatality dependent on neurological diagnosis. Therefore, the primary aims of this study were to determine the temperature profiles and incidence of dysthermia among a mixed cohort of brain injury patients admitted to the intensive care unit (ICU) and to evaluate the effects of dysthermia on in-hospital case fatality. Specifically, we wanted to determine the following: 1) the occurrence of spontaneous dysthermia on admission to the ICU, 2) the impact of dysthermia on in-hospital case fatality, and 3) whether dysthermia on admission to the ICU was an early predictor of in-hospital case fatality. Data were analyzed by taking into account neurological observations and by adjusting a multivariable analysis for known confounders of poor outcomes. We hypothesized the following: 1) dysthermia would be associated with in-hospital case fatality and 2) the effect of dysthermia on death would not be different across subgroups of patients with brain injuries.

Methods

This was a retrospective multicenter study, using a prospectively compiled and maintained registry (Cerner Corporation – Project IMPACT, Bel Air, MD). Project IMPACT (PI) is a large administrative database (initially developed by the Society of Critical Care Medicine) designed for critical care units across all disciplines. Intensive care units for adults from 131 US hospitals participate in PI, and data from more than 400,000 patients have been collected prospectively.

For this analysis, critically ill patients with acute ischemic stroke (AIS), aneurysmal subarachnoid hemorrhage (aSAH), intracerebral hemorrhage (ICH), or traumatic brain injury (TBI) who were older than 17 years and consecutively admitted to the ICU from 2003 to 2008 were selected for the analysis. The following variables were recorded for all patients admitted to the ICU during the study period: origin (emergency department vs inpatient admission); emergency department boarder status;24 donot-resuscitate rates; demographics; comorbidities; and variables within 24 hours of admission to an ICU, including Acute Physiology And Chronic Health Evaluation II (APACHE II) score, Glasgow Coma Scale (GCS) score, vital signs, laboratory results, and admission and hospital discharge status (alive and independent, alive and partially dependent, alive and fully dependent, or dead)36 (Table 1).

TABLE 1:

Demographics of the patients in this study*

VariableAllHypothermiaNormothermiaFeverp Value
no. of patients13,58714164816965
mean age (SD), yrs61 (15)62.4 (21)62.4 (18)56.7 (20)<0.0001
men7587 (56)65 (46)3477 (54)4045 (58)<0.0001
race/ethnicity (13,183 patients)0.0001
 white10,421 (79)109 (77)5049 (78)5263 (76)
 non-white, or not stated2762 (21)18 (13)1234 (19)1510 (22)
preadmission functional status (13,401 patients)<0.0001
 independent11,154 (82)109 (77)5200 (80)5845 (84)
 partially dependent1596 (12)8 (6)934 (14)654 (9)
 fully dependent651 (5)13 (9)281 (4)357 (5)
DNR status<0.0001
 full code12,821 (94)114 (81)6047 (93)6580 (94)
 DNR/no CPR/limited intervention699 (5)18 (13)351 (5)321 (5)
ED boarder516 (4)1 (<1)238 (4)276 (4)0.1
hospital size<0.0001
 extra large6905 (51)83 (59)3127 (48)3662 (523
 large5830 (42)49 (35)2837 (44)2903 (42)
 small to medium959 (7)9 (6)518 (8)412 (6)
hospital location<0.0001
 urban8956 (66)86 (61)4158 (64)4666 (67)
 suburban2712 (20)31 (22)1451 (22)1210 (17)
 rural2027 (15)24 (17)874 (13)1101 (16)
hospital type<0.0001
 academic4119 (30)47 (33)1631 (25)2441 (35)
 non-academic8416 (62)87 (62)4417 (68)3912 (56)
 public1052 (8)7 (5)433 (7)612 (9)
site of origin before ICU arrival<0.0001
 ED9234 (68)102 (72)4632 (71)4500 (65)
 in-patient4366 (32)39 (28)1850 (29)2477 (36)
diagnosis<0.0001
 AIS2973 (22)15 (11)1842 (28)1116 (16)
 aSAH2346 (17)26 (18)1055 (16)1265 (18)
 ICH4192 (31)56 (40)2047 (32)2089 (30)
 TBI4076 (30)44 (31)1580 (24)2452 (35)
GCS score<0.0001
 <84004 (29)109 (77)1003 (15)2814 (40)
 8–122662 (20)5 (4)1093 (17)1559 (22)
 >127029 (52)27 (19)4387 (68)2604 (37)
median APACHE II score (IQR)13 (9–19)28 (14–35)12 (9–16)15 (10–21)<0.0001
comorbidities
 cardiovascular disease382 (3)4 (3)184 (3)193 (3)NS
 pulmonary disease177 (1)2 (1)73 (1)102 (1)NS
 renal disease228 (2)2 (1)118 (2)108 (2)NS
 chronic liver disease92 (<1)040 (<1)52 (<1)NS
 chronic HIV infection28 (<1)016 (<1)12 (<1)NS
 cancer/metastatic159 (1)1 (<1)90 (1)68 (1)NS
organ dysfunction
 cardiovascular1391 (10)50 (35)441 (7)886 (13)<0.0001
 metabolic (lactic acidosis)237 (2)6 (4)52 (<1)178 (3)<0.0001
 respiratory1581 (12)28 (20)341 (5)1204 (17)<0.0001
 renal374 (3)8 (6)148 (2)218 (3)0.002
 hematological596 (4)9 (6)182 (3)401 (6)<0.0001
 hepatic156 (1)1 (<1)50 (<1)103 (1)0.0004
 neurological295 (2)10 (7)106 (2)176 (2)<0.0001
ICP monitoring per Dx2313 (17)15 (13)645 (10)1627 (24)<0.0001
 AIS58 (2)019 (3)13 (<1)NS
 aSAH764 (33)6 (40)237 (37)521 (32)<0.0001
 ICH624 (27)4 (27)180 (28)440 (27)<0.0001
 TBI867 (37)5 (33)209 (32)653 (40)0.02

Number of patients (%) are indicated, unless indicated otherwise. CPR = cardiopulmonary resuscitation; DNR = do not resuscitate; Dx = diagnosis; ED = emergency department; ICP = intracranial pressure; IQR = interquartile range; NS = not significant.

Defined as independent (the patient is living at home requiring no assistance in completing activities of daily living, which includes people who are homeless, or who are incarcerated, but otherwise physically and mentally functional), partially dependent (the patient is living at home, in a group home, or in a care facility and requires some assistance in completing the activities of daily living and the limitation[s] requiring assistance may be physical or mental), and fully dependent (the patient is living at home or in a care facility and is unable to perform the activities of daily living, must be cared for by other[s], and the limitations requiring assistance may be physical or mental).

Cardiovascular disease (defined as baseline symptoms such as angina or shortness of breath at rest or on minimal exertion, New York Heart Association Class IV, plus one or more of the following diagnoses: severe coronary artery disease, severe valvular heart disease, or severe cardiomyopathy), respiratory disease (defined as chronic obstructive, restrictive, or vascular pulmonary disease resulting in severe exercise restriction, such as being unable to climb stairs or to perform household duties; dependence on respirator because of active respiratory disease; or documented chronic hypoxia, hypercapnia, or pulmonary hypertension > 40 mm Hg), cirrhosis, chronic renal disease or end-stage renal disease, HIV status, and cancer).

To assess the effect of medical complications during ICU admission on in-hospital case fatality, we collected data on the following acute organ dysfunctions during the ICU stay according to the definitions of the PI database: cardiovascular dysfunction (a systolic blood pressure < 90 mm Hg or a mean arterial pressure < 70 mm Hg; or vasopressor requirement to keep systolic blood pressure > 90 mm Hg or mean arterial pressure > 70 mm Hg for a duration of > 1 hour), metabolic dysfunction (lactic acidosis > 2.0 mmol/dl), respiratory dysfunction (acute lung injury with a PaO2/FiO2 < 300 or positive end-expiratory pressure > 5 cm H2O), renal dysfunction (serum creatinine increased > 1 mg/dl from baseline despite fluid resuscitation, or creatinine > 2.0 mg/dl regardless of baseline), hepatic dysfunction (acute elevation of serum bilirubin > 2 mg/dl), hematological (platelet count < 100,000/mm3 or prothrombin time/partial thromboplastin time > 1.5 times baseline), and neurological dysfunction (onset delirium or GCS score < 12). These definitions have also been used in previous studies using the PI repository.5,12

Hospitals were defined by location as urban, suburban, or rural; by type as community (non-academic), university based (academic), or public; and according to the Halpern criteria10 as small-to-medium size (≤ 300 beds), large (301–499 beds), or extra large (> 500 beds). We also collected the total hospital length of stay. Specific data on the National Institutes of Health Stroke Scale scores, the Hunt and Hess grades, the ICH scores, or other indices of disease severity or admission imaging were not available from the PI repository.

The main exposure variable was temperature, and for the purpose of this analysis, fever was defined as any temperature ≥ 37.5°C within the first 24 hours of admission to the ICU, hypothermia as any temperature < 36.0°C, and normothermia as a temperature not defined as fever or hypothermia. These cutoffs were defined a priori by consensus, and they conform to published results from clinical observations14,22,25,31,33 and practice guidelines.16 A preplanned secondary analysis was also performed, using a definition of fever as ≥ 38.3°C.14,17 The PI database does not collect information on the technique or anatomical sites used to collect temperature data. The primary outcome measure was in-hospital case fatality.

Continuous data are presented as means and SDs or as medians and interquartile ranges as appropriate, depending on the distribution of the data. Continuous variables were assessed for normality with the Kolmogorov-Smirnov test. Categorical data are reported as proportions and 95% CIs. For evaluation of differences at the univariable level, 1-way ANOVA was conducted, and differences between means were compared with the Tukey-Kramer post hoc test, the Mann-Whitney U-test for nonparametric data, or the chi-square or Fisher exact test for proportions. The outcome of interest was compared among the exposed groups using the Cochran-Mantel-Haenszel statistic. To test for the homogeneity of the odds ratios, we used the post hoc Breslow-Day test. For multivariable analysis, generalized estimating equations were used to account for potential correlations in mortality rates among patients sampled within hospital clusters.15 We examined an alternative to the independence assumption (that is, no association with mortality rates) for withinhospital correlation, using the quasi-likelihood independence criterion. An exchangeable correlation structure provided a better fit than the independence assumption, suggesting that a hospital effect was present in the model.

All patient data in Tables 1 and 2 were considered to be potential candidate variables for the models. Because other indicators of disease severity were lacking, we used the APACHE II score to account for potential effects of comorbid conditions and acute physiological derangements on our outcome of interest. As a surrogate of elevated intracranial pressure or hydrocephalus, we adjusted our multivariable models by intracranial pressure monitoring upon admission to the ICU or during the ICU stay. To test if dysthermia exposure remained a significant independent predictor of in-hospital case fatality when the model was adjusted for propensity of individuals to be exposed to dysthermia, a sensitivity analysis was performed, using propensity scores and adding the result of the propensity scoring into the final multivariable model.2 Finally, we tested for possible first-order interactions in those variables retained in the model. In all multivariable analyses, all factors of interest were included, and parsimonious models were identified by systematically removing the least significant factor and recalculating the model.

TABLE 2:

Physiological variables on admission to the ICU

Variable*TotalHypothermiaNormothermiaFever
high heart rate (per min)97 (84–112)90 (76–110)91 (80–103)103 (90–118)
low respiratory rate (per min)12 (11–15)12 (10–15)13 (11–15)12 (11–15)
high respiratory rate (per min)22 (20–26)20 (16–24)22 (20–26)23 (23–27)
MAP, mmHg
 lowest72 (63–82)69 (53–80)73 (65–83)71 (62–81)
 highest109 (98–121)106 (94–122)109 (98–120)109 (99–122)
 <60 mm Hg, no. of patients (%)2138 (16)151 (32)837 (13)1150 (16)
 >120 mm Hg, no. of patients (%)3399 (25)127 (27)1528 (24)1744 (25)
hematocrit (%)
 lowest37 (33–41)35 (31–40)36 (36–40)35 (30–40)
 highest37 (33–41)36 (32–41)37 (33–41)36 (32–40)
white blood cells/μl
 lowest10 (8–13)9 (6.7–12)10 (7.3–12)11 (8.7–14)
 highest11 (8.6–15)10 (7.4–13)10 (7.7–13)13 (9.8–16)
sodium, mEq/L
 lowest138 (136–140)139 (136–141)138 (136–140)138 (136–141)
 highest139 (137–142)139 (136–142)139 (137–141)140 (137–142)
potassium, mEq/L
 lowest3.7 (3.4–4.0)4.0 (3.5–4.2)4.0 (3.5–4.1)4.0 (3.4–4.0)
 highest4.0 (3.7–4.3)4.0 (3.7–4.4)4.0 (3.7–4.3)4.0 (3.7–4.3)
bicarbonate, mEq/L
 lowest24 (22–26)25 (20–27)25 (23–27)23 (21–26)
 highest25 (23–26)24 (22–27)25 (23–28)25 (23–27)
blood urea nitrogen, mg/dl14 (10–21)16 (11–25)15 (11–21)14 (10–21)
creatinine, mg/dl
 low1 (0.7–1.1)1 (0.7–1.3)1 (0.7–1.1)1 (0.7–1.1)
 high1 (0.7–1.2)1 (0.8–1.4)1 (0.7–1.2)1 (0.7–1.2)
bilirubin, mg/dl1 (0.5–1.1)1 (0.5–1.0)1 (0.5–1.1)1 (0.5–1.1)

Values for the variables indicated are medians (IQR), unless indicated otherwise. MAP = mean arterial pressure.

Statistical analyses were conducted using SPSS software version 20.0 (SPSS Inc.). Our reporting of observational data conforms with the strengthening the reporting of observational studies in epidemiology (STROBE) guidelines.37 Based on the de-identified nature of the database used, the institutional review board at our institution exempted this analysis from full review.

Results

In total, 13,587 patients from 94 different hospitalbased ICUs met the inclusion criteria. All ICUs were nonneurological or neurosurgical models. Neurological diagnosis included AIS in 22%, ICH in 31%, aSAH in 17%, and TBI in 30% (Table 1). The cohort contained more men than women, and patients were predominantly white from community (non-academic), urban, and extra-large hospitals; 82% of the patients were living independently before being admitted to the hospital. Do-not-resuscitate status on admission applied to 5% of the cohort. Of all patients admitted to the ICU, 48% were normothermic (mean temperature 37.0°C ± 0.3°C), 1% were hypothermic (mean temperature 35.1°C ± 1.0°C), and 51% had fever (mean temperature 38.3°C ± 0.7°C) (p < 0.001 for differences in temperature between all pairs). Patients with hypothermia were more likely to be older than febrile patients, and had worse pre-admission functional status, higher APACHE II scores, and lower GCS scores. Additional physiological data over the first 24 hours in the ICU for all groups are shown in Table 2.

On admission to the ICU, fever was more frequent in patients with TBI and aSAH, and hypothermia was more frequent in ICH patients (Table 3). The average temperature of patients at admission for TBI patients was 37.8°C ± 0.9°C (p < 0.001 vs all others); for aSAH patients, 37.6°C ± 0.8°C (p < 0.001 vs TBI or AIS); for AIS patients, 37.4°C ± 0.8°C (p < 0.001 vs all others); and ICH patients, 37.6°C ± 0.9°C (p < 0.001 vs TBI or AIS).

TABLE 3:

Outcomes among the patients*

VariableAllAISaSAHICHTBI
no. of patients13,587 (100)2973 (22)2346 (17)4192 (31)4076 (30)
 death3145 (23)570 (19)552 (24)1370 (33)662 (16)
fever6965 (51)1116 (37)1265 (54)2089 (50)2452 (60)
 death1956 (28)337 (30)335 (26)841 (40)443 (18)
 OR (95% CI) §1.9 (1.7–2.1)3.1 (2.5–3.7)1.4 (1.2–1.7)2.0 (1.8–2.3)1.5 (1.3–1.8)
hypothermia141 (1)15 (<1)26 (1)56 (1)44 (1)
 death110 (78)9 (60)20 (77)48 (86)33 (75)
 OR (95% CI) 12.7 (8.4–19.4)6.4 (2.3–18.1)13.3 (4.9–35.6)12.8 (6.1–27.2)16.8 (8.4–33.3)
median overall hospital LOS (IQR)6 (3–12)6 (4–10)8 (3–15)6 (3–12)6 (3–12)**

Number of patients (%) are indicated for each variable, unless indicated otherwise. LOS = length of stay.

Status at hospital discharge.

p < 0.0001, Cochran-Mantel-Haenszel test, for conditional independence.

p < 0.0001, Breslow-Day test, for homogeneity of the OR. The stratum ORs and 95% CIs are significantly different, so we report the stratum OR and 95% CI.

p = 0.3, Breslow-Day test, for homogeneity of the OR. The stratum ORs and 95% CI were not significantly different, so we report the common OR and 95% CI.

p < 0.0001, Kruskal-Wallis test (statistical significance of differences between injury types were assessed with the Wilcoxon method and were identified for AIS vs aSAH, aSAH vs TBI, and aSAH vs ICH).

The outcomes among the patients in this study are shown in Table 3. Overall, 23% of all patients met the primary outcome of in-hospital case fatality, which was more common among patients with ICH, followed by patients with aSAH, AIS, or TBI. Similarly, mortality rates were overall higher among patients with hypothermia (crude OR 12.7, 95% CI 8.4–19.4) than among those with fever (crude OR 1.9, 95% CI 1.7–2.1). In a subgroup analysis, AIS patients with fever had the highest risk of death when compared with patients with ICH, TBI, or aSAH (p value < 0.0001 for Cochran-Mantel-Haenszel test for conditional independence, and p < 0.0001 for Breslow-Day test for homogeneity of the OR; Table 3). Although the mortality rate was higher in patients with hypothermia, this increase was not statistically significantly different across subgroups (p < 0.0001 for Cochran-Mantel-Haenszel test for conditional independence, and p = 0.2 for Breslow-Day test for homogeneity of the OR; Table 3).

In the secondary preplanned analysis, defining fever as a temperature ≥ 38.3°C, the overall risk of death was even higher in the fever group (OR 3.0, 95% CI 2.7–3.3). With this definition, AIS patients with fever had a higher risk of death (OR 4.7, 95% CI 3.7–6.0) than patients with ICH (OR 3.7, 95% CI 3.1–4.5), aSAH (OR 2.7, 95% CI 2.1–3.5), or TBI (OR 2.5, 95% CI 2.1–3.0) (p value < 0.0001 for Cochran-Mantel-Haenszel test for conditional independence, and p < 0.0001 for Breslow-Day test for homogeneity of the OR). The median hospital length of stay for survivors in the cohort was 6 days (IQR 3–12 days) but was slightly higher among the patients with aSAH (Table 3).

In the multivariable analysis using generalized estimating equations, the following were found to be significantly associated with in-hospital case fatality: APACHE II score, do not resuscitate on admission, organ dysfunction, intracranial pressure monitoring, and neurological disease (AIS, ICH, or aSAH when compared with TBI) (Table 4). An ICH was associated with the highest risk of case fatality followed by aSAH and AIS. Exposure to fever or hypothermia was found to be significantly associated with in-hospital death, and this effect remained significant even after adjusting for all other factors. The multivariable analysis also suggested a significant effect of hospital size: a higher risk of death was associated with hospitals that had a lower number of patients (Fig. 1).

TABLE 4:

Multivariable regression model indicating risk for in-hospital case fatality*

Model VariablesOR (95% CI)p Value
male sex0.9 (0.7–1.0)0.07
white race1.1 (0.9–1.4)0.06
APACHE II score1.2 (1.19–1.21)<0.001
DNR on admission1.7 (1.3–2.2)<0.001
ED boarder1.3 (0.8–1.9)0.3
ED origin (reference: in-patient)1.1 (0.9–1.3)0.2
hospital size (reference: extra large)
 small1.0 (0.8–1.3)0.8
 medium to large1.1 (0.8–1.5)0.6
hospital type (reference: urban academic)
 urban non-academic1.0 (0.8–1.4)0.9
 rural0.9 (0.6–1.4)0.6
neurological diagnosis (reference: TBI)
 AIS1.6 (1.4–1.9)<0.001
 aSAH1.8 (1.5–2.3)<0.001
 ICH2.0 (1.7–2.4)<0.001
in-hospital organ dysfunction (any)2.4 (2.1–2.8)<0.001
ICP monitoring1.4 (1.2–1.7)0.001
temperature group (reference: normo-thermia)
 hypothermia exposure7.8 (3.9–15.4)<0.001
 fever exposure1.3 (1.1–1.5)0.002

Model used generalized estimating equations; main effects were assessed.

Indicating relative likelihood of in-hospital death.

Fig. 1.
Fig. 1.

Relationship between discharge volume and in-hospital death of patients with brain injuries among hospitals of different sizes. The proportion of deaths (as percentage, right y-axis) is lower in hospitals with larger volumes of discharged patients (left y-axis).

Finally, in the sensitivity analysis, we found that the following variables were significantly associated with dysthermia in our cohort: male sex, white race, presence of comorbidities, APACHE II score, small and medium-to-large size of hospital, urban and non-academic hospital, and emergency department origin (Table 5). The probabilities, expressed in quintiles, were included in the final generalized estimating equation multivariable model (Table 6). When the calculated propensity score was accounted for, as seen in Table 6, the ORs for in-hospital case fatality associated with fever or hypothermia did not significantly change (for fever, an adjusted OR 1.2, 95% CI 1.04–1.41, p = 0.02; and for hypothermia, an adjusted OR 7.6, 95% CI 3.4–14.7, p < 0.0001, Table 6). These data indicate that fever and hypothermia remained significant independent predictors of in-hospital death when these factors were adjusted for the probability of a patient being exposed to dysthermia. We also found statistically significant interactions in our data, indicating a significant effect of fever on case fatality in the AIS and ICH subpopulations (Table 7).

TABLE 5:

Multivariable regression model (logistic regression) of risk factors for dysthermia on admission to the ICU

VariableOR (95% CI)p Value
white race1.23 (1.11–1.37)<0.001
AIS2.13 (1.88–2.40)<0.001
aSAH1.32 (1.16–1.51)<0.001
ICH1.54 (1.38–1.72)<0.001
male sex1.17 (1.08–1.28)<0.001
1 comorbidity1.27 (1.09–1.49)0.003
2 or more comorbidities1.87 (1.53–2.28)<0.001
APACHE II score1.05 (1.047–1.061)<0.001
ED boarder0.93 (0.75–1.15)0.509
ED origin1.27 (1.16–1.39)<0.001
DNR1.10 (0.89–1.35)0.365
small hospital size1.12 (1.01–1.23)0.025
medium-to-large hospital size1.30 (1.08–1.57)0.005
urban non-academic hospital1.30 (1.17–1.43)<0.001
rural hospital0.98 (0.83–1.15)0.775
ICP monitoring0.58 (0.52–0.66)<0.001
TABLE 6:

Multivariable regression model with in-hospital case fatality as the dependent variable with extant propensity of being exposed to dysthermia*

VariableOR (95% CI)p Value
white race1.30 (1.11–1.52)0.001
male sex0.93 (0.78–1.10)0.4
APACHE II score1.18 (1.15–1.20)<0.0001
DNR admission1.85 (1.39–2.46)<0.0001
ED boarder1.18 (0.74–1.86)0.5
ED origin1.17 (1.01–1.37)0.04
small hospital size1.12 (0.86–1.46)0.4
medium-to-large hospital size1.33 (0.90–1.98)0.2
urban non-academic hospital1.19 (0.87–1.62)0.4
rural hospital0.91 (0.60–1.39)0.2
ICP monitoring1.12 (0.92–1.37)0.2
in-hospital organ dysfunction2.40 (2.10–2.80)<0.0001
AIS2.43 (1.85–3.17)<0.0001
aSAH2.01 (1.63–2.47)<0.0001
ICH2.51 (2.12–2.97)<0.0001
fever (T >37.5°C)1.21 (1.04–1.41)0.02
hypothermia7.56 (3.89–14.7)<0.0001
propensity score (per quintile)1.25 (1.11–1.40)<0.0001

Model used generalized estimating equations; main effects were assessed. T = temperature.

Indicating relative likelihood of in-hospital death.

TABLE 7:

Multivariable regression model indicating risk for in-hospital case fatality*

Model VariablesOR (95.0% CI)p Value
male sex0.9 (0.7–1.0)0.06
white race1.2 (0.9–1.3)0.04
APACHE II score1.2 (1.1–1.2)<0.001
DNR upon admission1.7 (1.3–2.2)<0.001
ED origin (reference: inpatient)1.1 (0.9–1.2)0.2
ED boarder1.2 (0.8–1.9)0.3
hospital size (reference: extra large)
 small1.1 (0.8–1.4)0.4
 medium to large1.3 (0.8–1.7)0.2
hospital type (reference: urban academic)
 urban non-academic1.0 (0.7–1.3)0.8
 rural0.9 (0.6–1.2)0.5
neurological diagnosis (reference: TBI)
 AIS1.1 (0.8–1.5)0.5
 ASAH1.8 (1.3–2.5)0.001
 ICH1.5 (1.1–2.0)0.01
in-hospital organ dysfunctions (any)2.4 (2.1–2.8)<0.001
ICP monitoring1.5 (1.2–1.7)<0.0001
temperature group (reference: normo-thermia)
 hypothermia exposure7.3 (3.8–14)<0.0001
 fever exposure0.9 (0.7–1.2)0.5
interaction terms
 AIS × fever1.9 (1.3–2.6)<0.0001
 ASAH × fever1.0 (0.7–1.4)0.8
 ICH × fever1.6 (1.2–2.3)0.002

Model used generalized estimating equations; interactive effects were assessed.

Indicating relative likelihood of in-hospital death.

Discussion

In this large multicenter study of patients with brain injuries who were admitted to an ICU, we have confirmed that fever frequently occurs after brain injury.9,25,31,32 We also identified spontaneous hypothermia among a small proportion of these patients. Both fever and hypothermia were independently associated with increased in-hospital case fatality even after adjustment for other confounders during admission and ICU stay. The effect of these dysthermic conditions on in-hospital death remained independent after adjusting for the propensity or probability of a patient's exposure to dysthermia. Our study confirms results from previous reports addressing the effect of dysthermia on clinical outcomes after brain injury.9,25,31,32 Our results also suggest that the effect of fever on case fatality varies with the type of neurological injury. This may suggest disease-specific mechanisms in the onset of fever, which could contribute to worsening neurological outcomes depending on the type of brain injury. While we acknowledge that association does not necessarily imply causation, these data support the hypothesis that dysthermia upon admission to the ICU poses an increased risk for poor outcomes after brain injury.

Patients with brain injuries may develop fever as early as 24 hours after admission to the ICU9,31–33 and throughout the ICU stay.28 In our study, up to 51% of the patients with neurological injuries experienced fever on admission to the ICU. Fever was more frequent in TBI and aSAH patients, followed by patients with ICH and AIS. Several studies have reported the incidence of fever after TBI,1,35 which may be seen in up to 42% of the patients during the first 24 hours of admission.8 Similarly, aSAH patients in our cohort were more likely to have fever on admission to the ICU. Most studies of fever in patients with aSAH have addressed the incidence of fever throughout the ICU stay.6,18 Fernandez et al.6 demonstrated that fever in aSAH, with an average temperature elevation of about 0.6°C ± 0.58°C, is seen as early as the first 24 hours of admission. These studies also suggest that in 91% of TBI patients35 and 73% aSAH patients18 staying in an ICU the development of fever may be explained by infections. As infection or sepsis may be unlikely within the first 24 hours of ICU admission in patients with TBI or aSAH, it is possible that an early fever represents an acute response to injury or inflammation, or that it may be related to damage of thermoregulatory pathways.30 Theories of human thermoregulatory disturbances after brain injury are based on observations in animal models of brain hemorrhage and propose that damage to the hypothalamus, midbrain, or pons by enhanced sympathetic activity; acute or delayed ischemia; toxic blood metabolites; or physical distortion may be potential causes of fever.7,34

In our cohort, patients with AIS, followed by patients with ICH, had the lowest incidence of fever upon admission to the ICU. Animal studies have shown that during focal cerebral ischemia, brain temperatures can drop and return to normal after recirculation, perhaps mediated by changes in cerebral blood flow.11 Schwarz et al.33 reported that the incidence of fever was higher during the first 72 hours after ICH and that it decreased over time. Rincon et al.22 did not find a significant increase in the incidence of fever during the first 24 hours after onset of symptoms in a cohort of ICH patients. However, the frequency of fever increased after the first 24 hours of symptom onset in patients with ICH.22 The results of these studies are in agreement with our observations. They may support the notion that the mechanisms in ischemia–reperfusion injury in AIS and the onset of local or systemic inflammatory responses to hematoma growth and cerebral edema in ICH may be responsible for the slightly lower incidence of early fever seen in these groups.22 In contrast, both TBI and aSAH are considered global forms of brain injury, different from AIS or ICH, which are associated with more focal forms of brain damage.

Because of the retrospective nature of our study, we were unable to study in detail the association between dysthermia and stroke location, which makes our explanations merely speculative. It is possible that infarcts or hematomas in thermoregulatory pathways could be associated with temperature dysregulation after AIS or ICH. Rincon et al.21 d id not fi nd a n a ssociation b etween hematoma location and fever after ICH. Nevertheless, regardless of the difference in the incidence of fever upon admission to the ICU, fever was associated with higher in-hospital case fatality in all patients as has been suggested by other studies.9

Spontaneous hypothermia on ICU admission was seen in 1% of our patients and was more frequent in patients with ICH followed by TBI patients. The variables associated with hypothermia in our study, such as older age, comorbid conditions, nonindependent functional status, and comatose state, reflect known interactions between disease severity and temperature dysregulation.4 In other cohorts of critically ill patients, such as trauma, sepsis, and postsurgery patients, spontaneous hypothermia on ICU admission is also associated with poor outcomes.14,19,38 In our study, compared with the effects of fever, hypothermia remarkably increased the risk for in-hospital death. Studies in patients with injuries other than of the brain have also confirmed this association.14 Laupland et al. demonstrated that both fever and hypothermia increase the risk of in-hospital death in medical and surgical patients.14 Therefore, hypothermia on admission to the ICU may be used as an alert for an increased risk of unfavorable outcomes in all brain injury patients. However, it appears that the risk for poor outcome may be higher in critically ill, brain injury patients25 when compared with patients with other injuries.14 Rincon et al. recently demonstrated that the risk of in-hospital death was higher in critically ill patients with neurological injuries who had fever than in critically ill patients with other injuries who had similar disease severities and who were also similar in terms of age, sex, acute physiological derangements, and comorbidities.25 Our reported in-hospital mortality rate is also higher than the in-hospital mortality rates reported by Laupland et al. for hypothermic patients (60% vs 79%) and patients with fever (21% vs 28%) admitted to the ICU.14 These data suggest that patients with brain injuries may be at higher risk of dysthermia and poorer outcomes overall.

The strengths of our study are the methods used to test our hypotheses, the multicenter basis of the cohort ascertainment, and our mortality rates being in agreement with other reports from the literature.20,23,26 We also acknowledge the limitations of our study. First, our analysis is observational in nature, limiting the inferences that can be made about causal relationships. Second, the database used to perform our analysis was designed from an ICU perspective rather than to collect prospective data and end points commonly used in research of neuroscience outcomes. Moreover, the absence of data on disease-specific indexes of severity (National Institutes of Health Stroke Scale; ICH and Hunt and Hess scores; radiological variables; and surrogates of brain damage such as pupillary abnormalities) and on treatments for the advanced management of stroke and TBI precluded estimating associations or interactions within these variables. This suggests the possibility of some unmeasured confounding, which may have influenced our observed associations.

Third, because of the content in our database, we were unable to determine the effect of dysthermia beyond 24 hours and its effect on our prespecified outcomes. However, our data are robust and indicate that the effects of dysthermia could be significant as early as 24 hours, at least for our outcome of interest. We acknowledge that a single daily measurement of temperature may have not captured the whole impact of fever or hypothermia on our proposed outcomes. Most importantly, we did not know the technique used to ascertain the patient's temperature in each of the participating ICUs. So, it is possible that some patients would have been categorized differently if a systematic measurement protocol had been used.

Fourth, our study is an observational analysis of important clinical variables used in the ICU. We did not have access to other biological assays such as inflammatory markers, which would have been valuable at the time of explaining our results. To this end, future studies are needed to better understand the pathophysiology and molecular basis of temperature dysregulation and the influence of treatment modalities on the outcome of critically ill patients with brain injuries. Fifth, our data are limited by the quality of the PI repository. It is important to note that this analysis does not address longer-term or overall mortality. We were unable to examine or link data on mortality rates beyond the hospital admission, which may be more important from a public health perspective. Therefore, the advantages of our robust sample size are potentially offset by our inability to audit these and other data elements.

Sixth, our cohort may have been subjected to selection bias in the sense that our sample may not be representative of the whole population under study or in ICUs in the United States, so our results should be interpreted with this in mind. To this end, additional studies within specific populations of brain injury patients may be needed to further expand our knowledge in the field and to confirm our results. Finally, because the study focuses on nonneurological and neurosurgical ICUs in the United States, our results may not be generalizable to other settings where patients' characteristics, management strategies, and outcome may differ substantially.

Conclusions

Fever is frequently encountered in the acute phase of brain injury. The incidence of fever and its effect on mortality rates differ according to neurological diagnosis. This effect may be related to inherent disease processes and their interaction with local or systemic responses to injury such as inflammation. A small proportion of patients also may have spontaneous hypothermia. Both early spontaneous fever and hypothermia carry a higher risk for in-hospital death after brain injury. These data underscore the need for additional studies aimed at studying the mechanisms associated with the onset of fever after brain injury.

Acknowledgments

We would like to thank Dr. Andrew Kramer, Ph.D., and the Cerner Corporation for permitting access to the Project IMPACT database. Neither funding sources nor Cerner Corporation had a role in the design of this study or in the decision to submit it for publication.

Disclosure

Dr. Rincon has received salary support from the American Heart Association (AHA 12CRP12050342). Drs. Rincon and Zanotti-Cavazzoni and Mrs. Hunter had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Author contributions to the study and manuscript preparation include the following. Conception and design: Rincon, Schorr, Zanotti-Cavazzoni. Acquisition of data: all authors. Analysis and interpretation of data: all authors. Drafting the article: Rincon, Schorr, Dellinger, Zanotti-Cavazzoni. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Rincon. Statistical analysis: Rincon, Hunter, Zanotti-Cavazzoni. Administrative/technical/material support: Rincon, Schorr, Dellinger, Zanotti-Cavazzoni. Study supervision: Rincon, Dellinger, Zanotti-Cavazzoni.

References

  • 1

    Albrecht RF IIWass CTLanier WL: Occurrence of potentially detrimental temperature alterations in hospitalized patients at risk for brain injury. Mayo Clin Proc 73:6296351998

    • Search Google Scholar
    • Export Citation
  • 2

    Austin PC: An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 46:3994242011

    • Search Google Scholar
    • Export Citation
  • 3

    Coronado VGXu LBasavaraju SVMcGuire LCWald MMFaul MD: Surveillance for traumatic brain injury-related deaths—United States, 1997-2007. MMWR Surveill Summ 60:1322011

    • Search Google Scholar
    • Export Citation
  • 4

    den Hartog AWde Pont ACRobillard LBBinnekade JMSchultz MJHorn J: Spontaneous hypothermia on intensive care unit admission is a predictor of unfavorable neurological outcome in patients after resuscitation: an observational cohort study. Crit Care 14:R1212010

    • Search Google Scholar
    • Export Citation
  • 5

    Diringer MNEdwards DF: Admission to a neurologic/neurosurgical intensive care unit is associated with reduced mortality rate after intracerebral hemorrhage. Crit Care Med 29:6356402001

    • Search Google Scholar
    • Export Citation
  • 6

    Fernandez ASchmidt JMClaassen JPavlicova MHuddleston DKreiter KT: Fever after subarachnoid hemorrhage: risk factors and impact on outcome. Neurology 68:101310192007

    • Search Google Scholar
    • Export Citation
  • 7

    Frosini MSesti CValoti MPalmi MFusi FParente L: Rectal temperature and prostaglandin E2 increase in cerebrospinal fluid of conscious rabbits after intracerebroventricular injection of hemoglobin. Exp Brain Res 126:2522581999

    • Search Google Scholar
    • Export Citation
  • 8

    Geffroy ABronchard RMerckx PSeince PFFaillot TAlbaladejo P: Severe traumatic head injury in adults: which patients are at risk of early hyperthermia?. Intensive Care Med 30:7857902004

    • Search Google Scholar
    • Export Citation
  • 9

    Greer DMFunk SEReaven NLOuzounelli MUman GC: Impact of fever on outcome in patients with stroke and neurologic injury: a comprehensive meta-analysis. Stroke 39:302930352008

    • Search Google Scholar
    • Export Citation
  • 10

    Halpern NAPastores SMThaler HTGreenstein RJ: Changes in critical care beds and occupancy in the United States 1985-2000: differences attributable to hospital size. Crit Care Med 34:210521122006

    • Search Google Scholar
    • Export Citation
  • 11

    Hayward JNBaker MA: Role of cerebral arterial blood in the regulation of brain temperature in the monkey. Am J Physiol 215:3894031968

    • Search Google Scholar
    • Export Citation
  • 12

    Kilgannon JHJones AEShapiro NIAngelos MGMilcarek BHunter K: Association between arterial hyperoxia following resuscitation from cardiac arrest and in-hospital mortality. JAMA 303:216521712010

    • Search Google Scholar
    • Export Citation
  • 13

    Konstantinidis AInaba KDubose JBarmparas GTalving PDavid JS: The impact of nontherapeutic hypothermia on outcomes after severe traumatic brain injury. J Trauma 71:162716312011

    • Search Google Scholar
    • Export Citation
  • 14

    Laupland KBZahar JRAdrie CSchwebel CGoldgran-Toledano DAzoulay E: Determinants of temperature abnormalities and influence on outcome of critical illness. Crit Care Med 40:1451512012

    • Search Google Scholar
    • Export Citation
  • 15

    Localio ARBerlin JATen Have TRKimmel SE: Adjustments for center in multicenter studies: an overview. Ann Intern Med 135:1121232001

    • Search Google Scholar
    • Export Citation
  • 16

    Nunnally MEJaeschke RBellingan GJLacroix JMourvillier BRodriguez-Vega GM: Targeted temperature management in critical care: a report and recommendations from five professional societies. Crit Care Med 39:111311252011

    • Search Google Scholar
    • Export Citation
  • 17

    O'Grady NPBarie PSBartlett JGBleck TCarroll KKalil AC: Guidelines for evaluation of new fever in critically ill adult patients: 2008 update from the American College of Critical Care Medicine and the Infectious Diseases Society of America. Crit Care Med 36:133013492008

    • Search Google Scholar
    • Export Citation
  • 18

    Oliveira-Filho JEzzeddine MASegal AZBuonanno FSChang YOgilvy CS: Fever in subarachnoid hemorrhage: relationship to vasospasm and outcome. Neurology 56:129913042001

    • Search Google Scholar
    • Export Citation
  • 19

    Peres Bota DLopes Ferreira FMélot CVincent JL: Body temperature alterations in the critically ill. Intensive Care Med 30:8118162004

    • Search Google Scholar
    • Export Citation
  • 20

    Rincon FGhosh SDey SMaltenfort MVibbert MUrtecho J: Impact of acute lung injury and acute respiratory distress syndrome after traumatic brain injury in the United States. Neurosurgery 71:7958032012

    • Search Google Scholar
    • Export Citation
  • 21

    Rincon FLyden PMayer SA: Early and late predictors of hyperthermia after spontaneous ICH: on behalf of VISTA Collaborators. Stroke 43:A36582012. (Abstract)

    • Search Google Scholar
    • Export Citation
  • 22

    Rincon FLyden PMayer SA: Relationship between temperature, hematoma growth, and functional outcome after intracerebral hemorrhage. Neurocrit Care 18:45532013

    • Search Google Scholar
    • Export Citation
  • 23

    Rincon FMayer SA: The epidemiology of intracerebral hemorrhage in the United States from 1979 to 2008. Neurocrit Care 19:951022013

    • Search Google Scholar
    • Export Citation
  • 24

    Rincon FMayer SARivolta JStillman JBoden-Albala BElkind MS: Impact of delayed transfer of critically ill stroke patients from the Emergency Department to the Neuro-ICU. Neurocrit Care 13:75812010

    • Search Google Scholar
    • Export Citation
  • 25

    Rincon FPatel USchorr CLee ERoss SDellinger RP: Brain injury as a risk factor for fever upon admission to the intensive care unit and association with in-hospital case fatality: a matched cohort study. J Intensive Care Med [epub ahead of print]2013

    • Search Google Scholar
    • Export Citation
  • 26

    Rincon FRossenwasser RHDumont A: The epidemiology of admissions of nontraumatic subarachnoid hemorrhage in the United States. Neurosurgery 73:2172232013

    • Search Google Scholar
    • Export Citation
  • 27

    Roger VLGo ASLloyd-Jones DMBenjamin EJBerry JDBorden WB: Heart disease and stroke statistics—2012 update: a report from the American Heart Association. Circulation 125:e2e2202012. (Erratum in Circulation 125: e1002 2012)

    • Search Google Scholar
    • Export Citation
  • 28

    Rossi SZanier ERMauri IColumbo AStocchetti N: Brain temperature, body core temperature, and intracranial pressure in acute cerebral damage. J Neurol Neurosurg Psychiatry 71:4484542001

    • Search Google Scholar
    • Export Citation
  • 29

    Rubiano AMSanchez AIEstebanez GPeitzman ASperry JPuyana JC: The effect of admission spontaneous hypothermia on patients with severe traumatic brain injury. Injury 44:121912252013

    • Search Google Scholar
    • Export Citation
  • 30

    Sacho RHChilds C: The significance of altered temperature after traumatic brain injury: an analysis of investigations in experimental and human studies: part 2. Br J Neurosurg 22:4975072008

    • Search Google Scholar
    • Export Citation
  • 31

    Sacho RHVail ARainey TKing ATChilds C: The effect of spontaneous alterations in brain temperature on outcome: a prospective observational cohort study in patients with severe traumatic brain injury. J Neurotrauma 27:215721642010

    • Search Google Scholar
    • Export Citation
  • 32

    Saini MSaqqur MKamruzzaman ALees KRShuaib A: Effect of hyperthermia on prognosis after acute ischemic stroke. Stroke 40:305130592009

    • Search Google Scholar
    • Export Citation
  • 33

    Schwarz SHäfner KAschoff ASchwab S: Incidence and prognostic significance of fever following intracerebral hemorrhage. Neurology 54:3543612000

    • Search Google Scholar
    • Export Citation
  • 34

    Shibata M: Hyperthermia in brain hemorrhage. Med Hypotheses 50:1851901998

  • 35

    Stocchetti NRossi SZanier ERColombo ABeretta LCiterio G: Pyrexia in head-injured patients admitted to intensive care. Intensive Care Med 28:155515622002

    • Search Google Scholar
    • Export Citation
  • 36

    Trzeciak SJones AEKilgannon JHMilcarek BHunter KShapiro NI: Significance of arterial hypotension after resuscitation from cardiac arrest. Crit Care Med 37:289529032009

    • Search Google Scholar
    • Export Citation
  • 37

    von Elm EAltman DGEgger MPocock SJGøtzsche PCVandenbroucke JP: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370:145314572007

    • Search Google Scholar
    • Export Citation
  • 38

    Wang HECallaway CWPeitzman ABTisherman SA: Admission hypothermia and outcome after major trauma. Crit Care Med 33:129613012005

    • Search Google Scholar
    • Export Citation

If the inline PDF is not rendering correctly, you can download the PDF file here.

Article Information

Address correspondence to: Fred Rincon, M.D., M.Sc., F.C.C.M., Department of Neurological Surgery, Thomas Jefferson University and Jefferson College of Medicine, Division of Critical Care and Neurotrauma, 909 Walnut St., 3rd Floor, Philadelphia, PA 19107. email: fred.rincon@jefferson.edu.

Please include this information when citing this paper: published online August 8, 2014; DOI: 10.3171/2014.7.JNS132470.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    Relationship between discharge volume and in-hospital death of patients with brain injuries among hospitals of different sizes. The proportion of deaths (as percentage, right y-axis) is lower in hospitals with larger volumes of discharged patients (left y-axis).

References

  • 1

    Albrecht RF IIWass CTLanier WL: Occurrence of potentially detrimental temperature alterations in hospitalized patients at risk for brain injury. Mayo Clin Proc 73:6296351998

    • Search Google Scholar
    • Export Citation
  • 2

    Austin PC: An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 46:3994242011

    • Search Google Scholar
    • Export Citation
  • 3

    Coronado VGXu LBasavaraju SVMcGuire LCWald MMFaul MD: Surveillance for traumatic brain injury-related deaths—United States, 1997-2007. MMWR Surveill Summ 60:1322011

    • Search Google Scholar
    • Export Citation
  • 4

    den Hartog AWde Pont ACRobillard LBBinnekade JMSchultz MJHorn J: Spontaneous hypothermia on intensive care unit admission is a predictor of unfavorable neurological outcome in patients after resuscitation: an observational cohort study. Crit Care 14:R1212010

    • Search Google Scholar
    • Export Citation
  • 5

    Diringer MNEdwards DF: Admission to a neurologic/neurosurgical intensive care unit is associated with reduced mortality rate after intracerebral hemorrhage. Crit Care Med 29:6356402001

    • Search Google Scholar
    • Export Citation
  • 6

    Fernandez ASchmidt JMClaassen JPavlicova MHuddleston DKreiter KT: Fever after subarachnoid hemorrhage: risk factors and impact on outcome. Neurology 68:101310192007

    • Search Google Scholar
    • Export Citation
  • 7

    Frosini MSesti CValoti MPalmi MFusi FParente L: Rectal temperature and prostaglandin E2 increase in cerebrospinal fluid of conscious rabbits after intracerebroventricular injection of hemoglobin. Exp Brain Res 126:2522581999

    • Search Google Scholar
    • Export Citation
  • 8

    Geffroy ABronchard RMerckx PSeince PFFaillot TAlbaladejo P: Severe traumatic head injury in adults: which patients are at risk of early hyperthermia?. Intensive Care Med 30:7857902004

    • Search Google Scholar
    • Export Citation
  • 9

    Greer DMFunk SEReaven NLOuzounelli MUman GC: Impact of fever on outcome in patients with stroke and neurologic injury: a comprehensive meta-analysis. Stroke 39:302930352008

    • Search Google Scholar
    • Export Citation
  • 10

    Halpern NAPastores SMThaler HTGreenstein RJ: Changes in critical care beds and occupancy in the United States 1985-2000: differences attributable to hospital size. Crit Care Med 34:210521122006

    • Search Google Scholar
    • Export Citation
  • 11

    Hayward JNBaker MA: Role of cerebral arterial blood in the regulation of brain temperature in the monkey. Am J Physiol 215:3894031968

    • Search Google Scholar
    • Export Citation
  • 12

    Kilgannon JHJones AEShapiro NIAngelos MGMilcarek BHunter K: Association between arterial hyperoxia following resuscitation from cardiac arrest and in-hospital mortality. JAMA 303:216521712010

    • Search Google Scholar
    • Export Citation
  • 13

    Konstantinidis AInaba KDubose JBarmparas GTalving PDavid JS: The impact of nontherapeutic hypothermia on outcomes after severe traumatic brain injury. J Trauma 71:162716312011

    • Search Google Scholar
    • Export Citation
  • 14

    Laupland KBZahar JRAdrie CSchwebel CGoldgran-Toledano DAzoulay E: Determinants of temperature abnormalities and influence on outcome of critical illness. Crit Care Med 40:1451512012

    • Search Google Scholar
    • Export Citation
  • 15

    Localio ARBerlin JATen Have TRKimmel SE: Adjustments for center in multicenter studies: an overview. Ann Intern Med 135:1121232001

    • Search Google Scholar
    • Export Citation
  • 16

    Nunnally MEJaeschke RBellingan GJLacroix JMourvillier BRodriguez-Vega GM: Targeted temperature management in critical care: a report and recommendations from five professional societies. Crit Care Med 39:111311252011

    • Search Google Scholar
    • Export Citation
  • 17

    O'Grady NPBarie PSBartlett JGBleck TCarroll KKalil AC: Guidelines for evaluation of new fever in critically ill adult patients: 2008 update from the American College of Critical Care Medicine and the Infectious Diseases Society of America. Crit Care Med 36:133013492008

    • Search Google Scholar
    • Export Citation
  • 18

    Oliveira-Filho JEzzeddine MASegal AZBuonanno FSChang YOgilvy CS: Fever in subarachnoid hemorrhage: relationship to vasospasm and outcome. Neurology 56:129913042001

    • Search Google Scholar
    • Export Citation
  • 19

    Peres Bota DLopes Ferreira FMélot CVincent JL: Body temperature alterations in the critically ill. Intensive Care Med 30:8118162004

    • Search Google Scholar
    • Export Citation
  • 20

    Rincon FGhosh SDey SMaltenfort MVibbert MUrtecho J: Impact of acute lung injury and acute respiratory distress syndrome after traumatic brain injury in the United States. Neurosurgery 71:7958032012

    • Search Google Scholar
    • Export Citation
  • 21

    Rincon FLyden PMayer SA: Early and late predictors of hyperthermia after spontaneous ICH: on behalf of VISTA Collaborators. Stroke 43:A36582012. (Abstract)

    • Search Google Scholar
    • Export Citation
  • 22

    Rincon FLyden PMayer SA: Relationship between temperature, hematoma growth, and functional outcome after intracerebral hemorrhage. Neurocrit Care 18:45532013

    • Search Google Scholar
    • Export Citation
  • 23

    Rincon FMayer SA: The epidemiology of intracerebral hemorrhage in the United States from 1979 to 2008. Neurocrit Care 19:951022013

    • Search Google Scholar
    • Export Citation
  • 24

    Rincon FMayer SARivolta JStillman JBoden-Albala BElkind MS: Impact of delayed transfer of critically ill stroke patients from the Emergency Department to the Neuro-ICU. Neurocrit Care 13:75812010

    • Search Google Scholar
    • Export Citation
  • 25

    Rincon FPatel USchorr CLee ERoss SDellinger RP: Brain injury as a risk factor for fever upon admission to the intensive care unit and association with in-hospital case fatality: a matched cohort study. J Intensive Care Med [epub ahead of print]2013

    • Search Google Scholar
    • Export Citation
  • 26

    Rincon FRossenwasser RHDumont A: The epidemiology of admissions of nontraumatic subarachnoid hemorrhage in the United States. Neurosurgery 73:2172232013

    • Search Google Scholar
    • Export Citation
  • 27

    Roger VLGo ASLloyd-Jones DMBenjamin EJBerry JDBorden WB: Heart disease and stroke statistics—2012 update: a report from the American Heart Association. Circulation 125:e2e2202012. (Erratum in Circulation 125: e1002 2012)

    • Search Google Scholar
    • Export Citation
  • 28

    Rossi SZanier ERMauri IColumbo AStocchetti N: Brain temperature, body core temperature, and intracranial pressure in acute cerebral damage. J Neurol Neurosurg Psychiatry 71:4484542001

    • Search Google Scholar
    • Export Citation
  • 29

    Rubiano AMSanchez AIEstebanez GPeitzman ASperry JPuyana JC: The effect of admission spontaneous hypothermia on patients with severe traumatic brain injury. Injury 44:121912252013

    • Search Google Scholar
    • Export Citation
  • 30

    Sacho RHChilds C: The significance of altered temperature after traumatic brain injury: an analysis of investigations in experimental and human studies: part 2. Br J Neurosurg 22:4975072008

    • Search Google Scholar
    • Export Citation
  • 31

    Sacho RHVail ARainey TKing ATChilds C: The effect of spontaneous alterations in brain temperature on outcome: a prospective observational cohort study in patients with severe traumatic brain injury. J Neurotrauma 27:215721642010

    • Search Google Scholar
    • Export Citation
  • 32

    Saini MSaqqur MKamruzzaman ALees KRShuaib A: Effect of hyperthermia on prognosis after acute ischemic stroke. Stroke 40:305130592009

    • Search Google Scholar
    • Export Citation
  • 33

    Schwarz SHäfner KAschoff ASchwab S: Incidence and prognostic significance of fever following intracerebral hemorrhage. Neurology 54:3543612000

    • Search Google Scholar
    • Export Citation
  • 34

    Shibata M: Hyperthermia in brain hemorrhage. Med Hypotheses 50:1851901998

  • 35

    Stocchetti NRossi SZanier ERColombo ABeretta LCiterio G: Pyrexia in head-injured patients admitted to intensive care. Intensive Care Med 28:155515622002

    • Search Google Scholar
    • Export Citation
  • 36

    Trzeciak SJones AEKilgannon JHMilcarek BHunter KShapiro NI: Significance of arterial hypotension after resuscitation from cardiac arrest. Crit Care Med 37:289529032009

    • Search Google Scholar
    • Export Citation
  • 37

    von Elm EAltman DGEgger MPocock SJGøtzsche PCVandenbroucke JP: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370:145314572007

    • Search Google Scholar
    • Export Citation
  • 38

    Wang HECallaway CWPeitzman ABTisherman SA: Admission hypothermia and outcome after major trauma. Crit Care Med 33:129613012005

    • Search Google Scholar
    • Export Citation

TrendMD

Metrics

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 423 391 19
PDF Downloads 247 222 13
EPUB Downloads 0 0 0

PubMed

Google Scholar