Background: Core body temperature (CBT) plays a pivotal role in determining the prognosis of patients with neurological impairments. This study aimed to develop and evaluate a machine learning (ML) algorithm capable of forecasting CBT, as well as predicting fever and hypothermia, several hours in advance. Methods: We conducted a multicenter retrospective observational study in three mixed intensive care units (ICUs): two university hospitals in France (Hopital de la Timone and Nord), and one teaching military hospital in France (Sainte-Anne). We evaluated several prediction methods, including Neural Networks, Gradient Boosting, Random Forests, linear regression models, LSTM, and XGBoost. Inputs consisted of past temperature measurements, blood pressure, heart rate, and time of day. Results: Data from 10,189 ICU patients were analyzed. A training cohort (n = 5,146) from two ICUs was used to develop the models, and an independent evaluation cohort (n = 5,043) from the third ICU was used for testing. XGBoost consistently demonstrated the highest predictive performance for both fever and hypothermia. Sensitivity for fever (and hypothermia) prediction was 93.2 % (90.2 %) at 1 h, 86.6 % (82.3 %) at 2 h, and 76.8 % (70.3 %) at 4 h. Prediction of CBT values yielded Root Mean Square Errors of 0.19 degrees C, 0.31 degrees C, and 0.46 degrees C at 1, 2, and 4 h, respectively. Conclusion: This is the first large multicenter study to evaluate the contribution of ML to CBT prediction in ICU patients. Our findings show that fever and hypothermia can be reliably detected up to four hours before their occurrence, paving the way for more proactive and personalized patient management.

OBJECTIVE:This study aimed to identify predictors of epidural blood patch (EBP) success in patients with intracranial hypotension syndrome. BACKGROUND:The epidural blood patch remains the gold standard treatment for intracranial hypotension syndrome, yet its effectiveness varies, and predictors of sustained success remain uncertain. METHODS:We performed a single-center retrospective cohort study. We analyzed 139 epidural blood patches performed for non-obstetric intracranial hypotension syndrome between April 2015 and July 2025. Demographic, clinical, biological, radiological, and procedural data were collected. Complete symptom resolution or highly significant improvement at 1 month was defined as treatment success. RESULTS:Among 93 patients, 1-month complete success was achieved after 31% of procedures (43/139). Early improvement within 48 h was associated with higher odds of 1-month EBP success (adjusted odds ratio [aOR] = 9.70, 95% confidence interval [CI]: 3.66-28.96; p < 0.001) as was the occurrence of rebound headache (aOR = 5.34, 95% CI: 1.27-26.44; p = 0.028). Conversely, symptom exacerbation during the Valsalva maneuver was associated with lower odds of 1-month EBP success (aOR = 0.30, 95% CI: 0.10-0.81; p = 0.020). Lower baseline platelet and fibrinogen levels and osteophytic leaks were negatively associated with early effectiveness but not with 1-month outcome. Targeted epidural blood patches and shorter delay from symptom onset to procedure were associated with higher success rates in univariate analysis, though not independently. Model performance was robust with an area under the curve (AUC) of 0.88 (95% CI: 0.80-0.90). No infectious complications were observed; rebound headaches and transient back pain were the most common secondary events. CONCLUSION:Early clinical improvement and rebound headache are strong positive predictors of durable epidural blood patch effectiveness in intracranial hypotension syndrome, whereas Valsalva-related symptom worsening indicates a higher risk of failure. Radiological severity did not predict outcomes in our study. These easily identifiable clinical factors can assist in individualized management and reduce unnecessary repeat procedures.

External ventricular drain (EVD)-associated infections are a significant cause of morbidity and mortality. Nosocomial meningitis (NM) poses diagnostic challenges, and its prognosis heavily relies on the timely initiation of treatment. The aim of this study was to investigate the epidemiology of NM and risk factors in ICU patients. We conducted a retrospective single-center cohort study of adult patients who received an EVD in a French ICU between 2018 and 2022. Patients were classified into those with NM or without meningitis based on biological and microbiological criteria. We assessed risk factors related to the patient, the device, and the primary pathology, treatment regimens, length of stay, and survival. Of 275 patients with EVD, 32 (11.6

BACKGROUND:Proximal femur fractures (PFF) are common in the elderly, representing a significant public health issue. This study aims to define the epidemiology and morbidity of PFF and identify factors associated with 90-day mortality in patients with osteoporotic PFF. METHODS:We conducted a retrospective, bicentric, observational study in Marseille from November 2018 to June 2023, including patients operated for osteoporotic PFF. Clinical, biological, therapeutic, and socio-economic data were collected to analyse their influence on 90-day mortality and construct a mortality predictive model using a neural network. RESULTS:During the study period, 2442 patients were included, the mean age at diagnosis being 81 (13.7) years. The 279 (11.4%)non-survivors at 90 days were older (87.2 (0.8) vs. 79.8 (0.3) years; p < 0.0001), predominantly males (36.6% vs. 27.8%; p = 0.003), and had higher Charlson score (1[0-3] vs. 1[0-2]; p < 0.0001) and ASA score (3[3-3] vs. 3[2-3]; p < 0.0001). No significant differences were found in the use of cement, type of anaesthesia, and socio-economic level. A neural network predictive model for 90-day mortality included age, gender, ASA score, perioperative confusion, and haemoglobin, creatinine, and albumin at inclusion. The model performed with an area under the receiving operating characteristic curve of 0.91 [0.91-0.92], sensitivity of 50.5%, specificity of 75.0%, positive predictive value of 20.6%, and negative predictive value of 92.1% on the test set. CONCLUSION:Our results provide interesting elements to optimize the perioperative management of these patients. The future perspectives include validating the predictive model on external cohorts and integrating new variables to improve its accuracy.

Health is shaped by a complex network of socio-economic, environmental and behavioral factors, known as social determinants of health (SDOH). SDOH can be optionally documented using Z codes from the International Classification of Diseases, Tenth Revision (ICD-10) in the French national hospital database. This study aimed to (a) describe the use of SDOH codes among adult inpatients in France in 2022, and temporal trends from 2014 to 2022; and (b) identify the characteristics of hospital stays associated with the presence of SDOH codes. We conducted a nationwide retrospective, cross-sectional, observational study using the French national hospital database. All stays for patients aged 18 years or older in acute care hospitals between 2014 and 2022 were included. The outcome was the presence of at least one SDOH code (Z55-Z75). Temporal trends in the use of SDOH codes from 2014 to 2022 were analyzed using univariable linear regression. Univariable and multivariable mixed-effects models were used to identify characteristics of hospital stays associated with SDOH codes for the year 2022. From 2014 to 2022, 83,741,127 stays were identified, of which 6,321,390 (7.6

Abstract Background Severe trauma is the leading cause of disability and mortality in the patients under 35 years of age. Surgical site infections (SSI) represent a significant complication in this patient population. However, they are often inadequately investigated, potentially impacting the quality of patient outcomes. The aim of this study was to investigate the epidemiology of SSI and risk factors in severe trauma patients. Methods We conducted a multicenter retrospective cohort study screening the severe trauma patients (STP) admitted to two intensive care units of an academic institution in Marseille between years2018 and 2019. Those who underwent orthopedic or spinal surgery within 5 days after admission were included and classified into two groups according to the occurrence of SSI (defined by the Centers for Disease Control (CDC) international diagnostic criteria) or not. Our secondary goal was to evaluate STP survival at 48 months, risk factors for SSI and microbiological features of SSI. Results Forty-seven (23%) out of 207 STP developed an SSI. Mortality at 48-months did not differ between SSI and non-SSI patients (12.7% vs. 10.0%; p = 0.59). The fractures of 22 (47%) severe trauma patients with SSI were classified as Cauchoix 3 grade and 18 (38%) SSI were associated with the need for external fixators. Thirty (64%) severe trauma patients with SSI had polymicrobial infection, including 34 (72%) due to Gram-positive cocci. Empirical antibiotic therapy was effective in 31 (66%) cases. Multivariate analysis revealed that risk factors such as low hemoglobin, arterial oxygenation levels, hyperlactatemia, high serum creatinine and glycemia, and Cauchoix 3 grade on the day of surgery were associated with SSI in severe trauma patients. The generated predictive model showed a good prognosis performance with an AUC of 0.80 [0.73–0.88] and a high NPV of 95.9 [88.6–98.5] %. Conclusions Our study found a high rate of SSI in severe trauma patients, although SSI was not associated with 48-month mortality. Several modifiable risk factors for SSI may be effectively managed through enhanced perioperative monitoring and the implementation of a patient blood management strategy.

Background: In intensive care units (ICUs), accurate mortality prediction is crucial for effective patient management and resource allocation. The Simplified Acute Physiology Score II (SAPS -2), though commonly used, relies heavily on comprehensive clinical data and blood samples. This study sought to develop an artificial intelligence (AI) model utilizing key hemodynamic parameters to predict ICU mortality within the first 24 h and assess its performance relative to SAPS -2. Methods: We conducted an analysis of select hemodynamic parameters and the structure of heart rate curves to identify potential predictors of ICU mortality. A machine -learning model was subsequently trained and validated on distinct patient cohorts. The AI algorithm's performance was then compared to the SAPS -2, focusing on classification accuracy, calibration, and generalizability. Measurements and main results: The study included 1298 ICU admissions from March 27th, 2015, to March 27th, 2017. An additional cohort from 2022 to 2023 comprised 590 patients, resulting in a total dataset of 1888 patients. The observed mortality rate stood at 24.0%. Key determinants of mortality were the Glasgow Coma Scale score, heart rate complexity, patient age, duration of diastolic blood pressure below 50 mmHg, heart rate variability, and specific mean and systolic blood pressure thresholds. The AI model, informed by these determinants, exhibited a performance profile in predicting mortality that was comparable, if not superior, to the SAPS -2. Conclusions: The AI model, which integrates heart rate and blood pressure curve analyses with basic clinical parameters, provides a methodological approach to predict in -hospital mortality in ICU patients. This model offers an alternative to existing tools that depend on extensive clinical data and laboratory inputs. Its potential integration into ICU monitoring systems may facilitate more streamlined mortality prediction processes.

Summary Global warming is a major public health concern. Volatile anaesthetics are greenhouse gases that increase the carbon footprint of healthcare. Modelling studies indicate that total intravenous anaesthesia is less carbon intensive than volatile anaesthesia, with equivalent quality of care. In this observational study, we aimed to apply the findings of previous modelling studies to compare the carbon footprint per general anaesthetic of an exclusive TIVA strategy vs. a mixed TIVA‐volatile strategy. This comparative retrospective study was conducted over 2 years in two French hospitals, one using total intravenous anaesthesia only and one using a mixed strategy including both intravenous and inhalation anaesthetic techniques. Based on pharmacy procurement records, the quantity of anaesthetic sedative drugs was converted to carbon dioxide equivalents. The primary outcome was the difference in carbon footprint of hypnotic drugs per intervention between the two strategies. From 1 January 2021 to 31 December 2022, 25,137 patients received general anaesthesia in the hospital using the total intravenous anaesthesia strategy and 22,020 in the hospital using the mixed strategy. The carbon dioxide equivalent footprint of hypnotic drugs per intervention in the hospital using the total intravenous anaesthesia strategy was 20 times lower than in the hospital using the mixed strategy (emissions of 2.42 kg vs. 48.85 kg carbon dioxide equivalent per intervention, respectively). The total intravenous anaesthesia strategy significantly reduces the carbon footprint of hypnotic drugs in general anaesthesia in adult patients compared with a mixed strategy. Further research is warranted to assess the risk–benefit ratio of the widespread adoption of total intravenous anaesthesia.

Background: Core body temperature (CBT) is an essential parameter linked to health outcomes. Monitoring methods in clinical settings provide only real-time or retrospective data, failing to exploit historical trends for predictive analysis. This limitation is particularly critical in ICU environments, where early detection and proactive management of temperature deviations are vital to prevent prognosis worsening in severe neurological injuries. The purpose of this work is to develop an artificial intelligence algorithm to forecast patient CBT one, two, and four hours ahead, predicting the onset of fever or hypothermia.Methods: We conducted a multicenter retrospective observational study in the mixed intensive care units (ICU) of two university hospitals in Marseille, France (Hôpital de la Timone and Hôpital Nord). We analyzed surveillance data from January 2011 to January 2019. We evaluated prediction methods including neural networks, Gradient Boosting, Random Forest methods, support vector machines, and linear regressions. Inputs were past temperatures, blood pressures and heart rate values.Findings: The study period included data from 5,146 patients. We used a learning cohort (n=2,062) from one ICU and tested the algorithms on an evaluation cohort from the second ICU (n=3,084). For fever (respectively hypothermia) prediction, CBT, neural networks (resp. Gradient Boosting) models demonstrated high sensitivity and specificity. Sensitivity for fever (and hypothermia) predictions was 95.7% (95%), 90.7% (88%), and 74.1% (75%) at 1, 2, and 4 hours, respectively for fever (respectively hypothermia). Finally, the prediction of CBT at 1, 2, and 4 hours had a Root Mean Square Error of 0.07, 0.18, and 0.37°C, respectively.Interpretation: Our study is the first to evaluate the contribution of AI to predict CBT in a large number of ICU patients. The detection of fever or hypothermia episodes is reliable up to four hours before their occurrence.Funding: This work did not receive any specific fundings.Declaration of Interest: SB, AM, NB LV, and FA have no conflict of interest related or not to this work, ML consultant for AOP Pharma, Viatris and speaker for Shionogi.Ethical Approval: The study was approved by the Comité de Protection des Personnes (CCP 1) Mediterranée local ethical comittee (2015/17) and by the local computer and freedoms committee (RGDP - 2019/117). Patient consent for the use of these data was not required as patients were informed about the anonymous use of their data for research purposes, and they could opt-out according to French regulations.

Background:Traumatic hemorrhage guidelines include point-of-care viscoelastic tests as a standard of care. Quantra (Hemosonics) is a device based on sonic estimation of elasticity via resonance (SEER) sonorheometry to assess whole blood clot formation.Objectives:Our study aimed to assess the ability of an early SEER evaluation to detect blood coagulation test abnormalities in trauma patients.Methods:We conducted an observational retrospective cohort study with data collected at hospital admission of consecutive multiple trauma patients from September 2020 to February 2022 at a regional level 1 trauma center. We performed a receiving operator characteristic curve analysis to determine the ability of the SEER device to detect blood coagulation test abnormalities. Four values on the SEER device were analyzed: clot formation time, clot stiffness (CS), platelet contribution to CS, and fibrinogen contribution to CS.Results:A total of 156 trauma patients were analyzed. The clot formation time value predicted an activated partial thromboplastin time ratio of >1.5 with an area under the curve (AUC) of 0.93 (95% CI, 0.86-0.99). The AUC of the CS value in detecting an international normalized ratio of prothrombin time of >1.5 was 0.87 (95% CI, 0.79-0.95). The AUC of fibrinogen contribution to CS to detect a fibrinogen concentration of <1.5 g/L was 0.87 (95% CI, 0.80-0.94). The AUC of platelet contribution to CS to detect a platelet concentration of <50 G/L was 0.99 (95% CI, 0.99-1.00).Conclusion:Our results suggest that the SEER device may be useful for the detection of blood coagulation test abnormalities at trauma admission.

This retrospective study aimed to describe the association between the "beta-lactam allergy" labeling (BLAL) and the outcomes of a cohort of intensive care unit (ICU) patients. Retrospective cohort study. Seven ICU of the Aix Marseille University Hospitals from Marseille in France. We collected the uses of the label "beta-lactam allergy" in the electronic medical files of patients aged 18 years or more who required more than 48 hours in the ICU with mechanical ventilation and/or vasopressors admitted to 7 ICUs of a single institution. We retrospectively compared the patients with this labeling (BLAL group) with those without this labeling (control group). The primary outcome was the duration of ICU stay. Among the 7146 patients included in the analysis, 440 and 6706 patients were classified in the BLAL group and the control group, respectively. The prevalence of BLAL was 6.2%. In univariate and multivariate analyses, BLAL was weakly or not associated with the duration of ICU and hospital stays (respectively, 6 [3-14] vs 6 [3-14] days, standardized beta -0.09, P = .046; and 18 [10-29] vs 15 [8-28] days, standardized beta -0.09, P = .344). In multivariate analysis, the ICU and 28-day mortality rates were both lower in the BLAL group than in the control group (aOR 0.79 95% CI [0.64-0.98] P = .032 and 0.79 [0.63-0.99] P = .042). Antibiotic use differed between the 2 groups, but the outcomes were similar in the subgroups of septic patients in the BLAL group and the control group. In our cohort, the labeling of a beta-lactam allergy was not associated with prolonged ICU and hospital stays. An association was found between the labeling of a beta-lactam allergy and lower ICU and 28-day mortality rates. Trial registration: Retrospectively registered.

Background - There is limited information describing the presenting characteristics and outcomes of patients with schizophrenia (SCZ) requiring hospitalization for coronavirus disease 2019 (COVID-19). Aims- We aimed to compare the clinical characteristics and outcomes of COVID-19 SCZ patients with those of non-SCZ patients. Method - This was a case-control study of COVID-19 patients admitted to 4 APHM/AMU acute care hospitals in Marseille, southern France. COVID-19 infection was confirmed by a positive result on polymerase chain reaction testing of a nasopharyngeal sample and/or on chest computed scan among patients requiring hospital admission. The primary outcome was in-hospital mortality. The secondary outcome was intensive care unit (ICU) admission. Results - A total of 1092 patients were included. The overall in-hospital mortality rate was 9.0%. The SCZ patients had an increased mortality compared to the non-SCZ patients (26.7% vs. 8.7%, P = 0.039), which was confirmed by the multivariable analysis after adjustment for age, sex, smoking status, obesity and comorbidity (adjusted odds ratio 4.36 [95% CI: 1.0917.44]; P = 0.038). In contrast, the SCZ patients were not more frequently admitted to the ICU than the non-SCZ patients. Importantly, the SCZ patients were mostly institutionalized (63.6%, 100% of those who died), and they were more likely to have cancers and respiratory comorbidities. Conclusions - This study suggests that SCZ is not overrepresented among COVID-19 hospitalized patients, but SCZ is associated with excess COVID-19 mortality, confirming the existence of health disparities described in other somatic diseases. (C) 2020 L'Encephale, Paris.

Abstract This retrospective study aimed to describe the association between the “β-lactam allergy” labeling (BLAL) and the outcomes of a cohort of intensive care unit (ICU) patients. Retrospective cohort study. Seven ICU of the Aix Marseille University Hospitals from Marseille in France. We collected the uses of the label “β-lactam allergy” in the electronic medical files of patients aged 18 years or more who required more than 48 hours in the ICU with mechanical ventilation and/or vasopressors admitted to 7 ICUs of a single institution. We retrospectively compared the patients with this labeling (BLAL group) with those without this labeling (control group). The primary outcome was the duration of ICU stay. Among the 7146 patients included in the analysis, 440 and 6706 patients were classified in the BLAL group and the control group, respectively. The prevalence of BLAL was 6.2%. In univariate and multivariate analyses, BLAL was weakly or not associated with the duration of ICU and hospital stays (respectively, 6 [3–14] vs 6 [3–14] days, standardized beta −0.09, P = .046; and 18 [10–29] vs 15 [8–28] days, standardized beta −0.09, P = .344). In multivariate analysis, the ICU and 28-day mortality rates were both lower in the BLAL group than in the control group (aOR 0.79 95% CI [0.64–0.98] P = .032 and 0.79 [0.63–0.99] P = .042). Antibiotic use differed between the 2 groups, but the outcomes were similar in the subgroups of septic patients in the BLAL group and the control group. In our cohort, the labeling of a β-lactam allergy was not associated with prolonged ICU and hospital stays. An association was found between the labeling of a β-lactam allergy and lower ICU and 28-day mortality rates. Trial registration: Retrospectively registered.

Background An association was reported between the left ventricular longitudinal strain (LV-LS) and preload. LV-LS reflects the left cardiac function curve as it is the ratio of shortening over diastolic dimension. The aim of this study was to determine the sensitivity and specificity of LV-LS variations after a passive leg raising (PLR) maneuver to predict fluid responsiveness in intensive care unit (ICU) patients with acute circulatory failure (ACF). Methods Patients with ACF were prospectively included. Preload-dependency was defined as a velocity time integral (VTI) variation greater than 10% between baseline (T0) and PLR (T1), distinguishing the preload-dependent (PLD+) group and the preload-independent (PLD-) group. A 7-cycles, 4-chamber echocardiography loop was registered at T0 and T1, and strain analysis was performed off-line by a blind clinician. A general linear model for repeated measures was used to compare the LV-LS variation (T0 to T1) between the two groups. Results From June 2018 to August 2019, 60 patients (PLD+ = 33, PLD- = 27) were consecutively enrolled. The VTI variations after PLR were +21% (±8) in the PLD+ group and -1% (±7) in the PLD- group (p<0.01). Mean baseline LV-LS was -11.3% (±4.2) in the PLD+ group and -13.0% (±4.2) in the PLD- group (p = 0.12). LV-LS increased in the whole population after PLR +16.0% (±4.0) (p = 0.04). The LV-LS variations after PLR were +19.0% (±31) (p = 0.05) in the PLD+ group and +11.0% (±38) (p = 0.25) in the PLD- group, with no significant difference between the two groups (p = 0.08). The area under the curve for the LV-LS variations between T0 and T1 was 0.63 [0.48–0.77]. Conclusion Our study confirms that LV-LS is load-dependent; however, the variations in LV-LS after PLR is not a discriminating criterion to predict fluid responsiveness of ICU patients with ACF in this cohort.

PURPOSE:To compare the effects of two therapeutic bundles of management in SARS-CoV2 ICU patients. MATERIALS AND METHODS:Our retrospective, observational study was performed in a university ICU from March to June 2020 (first wave) and from September 2020 to January 2021 (second wave). In first wave, patients received bundle 1 including early invasive ventilation, hydroxychloroquine, cefotaxime and azithromycin. In second wave, bundle 2 included non-invasive oxygenation support and dexamethasone. The main outcome was in-hospital mortality. Secondary outcomes included ICU and hospital length of stay, ICU supportive therapies, viral clearance and antimicrobial resistance emergence. RESULTS:129 patients with SARS-CoV-2 pneumonia were admitted to our ICU. Thirty-five were treated according to bundle 1 and 76 to bundle 2. In-hospital mortality was similar in the two groups (23%, p = 1). The hospital (p = 0.003) and ICU (p = 0.01) length of stay and ventilator-free days at 28 days (p = 0.03) were significantly reduced in bundle 2. Increasing age, vasopressor use and PaO2/FiO2 ratio < 125 were associated with in-hospital mortality. CONCLUSION:Within the limitations of our study, changes in therapeutic bundles for SARS-Cov-2 ICU patients might have no effect on in-hospital mortality but were associated with less exposure to mechanical ventilation and reduced hospital length of stay.

Selective digestive decontamination (SDD) reduces the rate of infection and improves the outcomes of patients admitted to an intensive care unit (ICU). A risk associated with its use is the development of multi-drug-resistant organisms. We hypothesized that a 1-day reduction in systemic antimicrobial exposure in the SDD regimen would not affect the outcomes of our patients. In this before-and-after study design, 199 patients and 248 patients were included in a 3-day SDD group and a 2-day SDD group, respectively. The rates of hospital-acquired pneumonia and ICU infections were similar in both groups. The rates of bloodstream infection and bacteriuria were significantly lower in the 2-day SDD group than in the 3-day SDD group. Compared with the patients in the 3-day group, the patients in the 2-day SDD group received fewer antibiotics and less exposure to mechanical ventilation, and they used fewer ICU resources. The rates of ICU mortality and 28-day mortality were similar in both groups. The incidence of multi-drug-resistant organisms was similar in both groups. Within the limitations inherent to our study design, reducing the exposure of prophylactic systemic antibiotics in the SDD setting from 3 days to 2 days was not associated with impaired outcomes. Future randomized controlled trials should be conducted to test this hypothesis and investigate the effects on the development of multi-drug resistant organisms.

Background: Postoperative pulmonary complications are associated with increased morbidity. Identifying patients at higher risk for such complications may allow preemptive treatment. METHODS: Patients with an American Society of Anesthesiologists (ASA) score >1 and who were scheduled for major surgery of >2 hours were enrolled in a single-center prospective study. After extubation, lung ultrasound was performed after a median time of 60 minutes by 2 certified anesthesiologists in the postanesthesia care unit after a standardized tracheal extubation. Postoperative pulmonary complications occurring within 8 postoperative days were recorded. The association between lung ultrasound findings and postoperative pulmonary complications was analyzed using logistic regression models. RESULTS: Among the 327 patients included, 69 (19%) developed postoperative pulmonary complications. The lung ultrasound score was higher in the patients who developed postoperative pulmonary complications (12 [7-18] vs 8 [4-12]; P < .001). The odds ratio for pulmonary complications in patients who had a pleural effusion detected by lung ultrasound was 3.7 (95% confidence interval, 1.2-11.7). The hospital death rate was also higher in patients with pleural effusions (22% vs 1.3%; P < .001). Patients with pulmonary consolidations on lung ultrasound had a higher risk of postoperative mechanical ventilation (17% vs 5.1%; P = .001). In all patients, the area under the curve for predicting postoperative pulmonary complications was 0.64 (95% confidence interval, 0.57-0.71). CONCLUSIONS: When lung ultrasound is performed precociously <2 hours after extubation, detection of immediate postoperative alveolar consolidation and pleural effusion by lung ultrasound is associated with postoperative pulmonary complications and morbi-mortality. Further study is needed to determine the effect of ultrasound-guided intervention for patients at high risk of postoperative pulmonary complications.

Abstract Background Circadian clock alterations were poorly reported in trauma patients, although they have a critical role in human physiology. Core body temperature is a clinical variable regulated by the circadian clock. Our objective was to identify the circadian temperature disruption in trauma patients and to determine whether these disruptions were associated with the 28-day mortality rate. Methods A retrospective and observational single-center cohort study was conducted. All adult severe trauma patients admitted to the intensive care unit of Aix Marseille University, North Hospital, from November 2013 to February 2018, were evaluated. The variations of core body temperature for each patient were analyzed between days 2 and 3 after intensive care unit admission. Core body temperature variations were defined by three parameters: mesor, amplitude, and period. A logistic regression model was used to determine the variables influencing these three parameters. A survival analysis was performed assessing the association between core body temperature rhythm disruption and 28-day mortality rate. A post hoc subgroup analysis focused on the patients with head trauma. Results Among the 1584 screened patients, 248 were included in this study. The period differed from 24 h in 177 (71%) patients. The mesor value (°C) was associated with body mass index and ketamine use. Amplitude (°C) was associated with ketamine use only. The 28-day mortality rate was 18%. For all trauma patients, age, body mass index, intracranial hypertension, and amplitude were independent risk factors. The patients with a mesor value < 36.9 °C (p < 0.001) and an amplitude > 0.6 °C (p < 0.001) had a higher 28-day mortality rate. Among the patients with head trauma, mesor and amplitude were identified as independent risk factors (HR = 0.40, 95% CI [0.23–0.70], p = 0.001 and HR = 4.73, 95% CI [1.38–16.22], p = 0.01). Conclusions Our results highlight an association between core body temperature circadian alteration and 28-day mortality rate. This association was more pronounced in the head trauma patients than in the non-head trauma patients. Further studies are needed to show a causal link and consider possible interventions.

Purpose: This study aimed to describe by mathematical modeling an accurate course of core body temperature (CBT) in severe trauma patients and its relation to sepsis. Methods: In a cohort of severe trauma, the CBT measurements were collected for 24 h on day 2 after admission and rhythmicity assessed by Fourier transform and Cosinor analysis to describe circadian features (frequency and amplitude). CBT was compared between patients who developed sepsis or not during the early ICU stay. Results: 33 patients were included in this analysis. 24 patients (73%) had a predominant rhythm of 24 h (period). The main period was lower in the 9 remaining patients (6 of 12 h, 1 of 8 h, and 2 of 6 h). Other significant frequencies of oscillation (second and third frequencies) were found, which showed an association of several well marked rhythms. Patients with sepsis (n = 12) had a significantly higher level of CBT, but also more intense rhythms and higher amplitudes of CBT. Conclusion: Trauma patients exhibit complex temperature circadian rhythms. Early exacerbation of the temperature rhythmicity (in frequency and amplitude) is associated with the development of sepsis. This observation accentuates the concept of circadian disruption and sepsis in ICU patients. (C) 2020 Elsevier Inc. All rights reserved.