Background

Reported differences in treatment and mortality between male and female patients in the ICU are inconsistent. Previous studies suggest that age might influence sex differences, partly explaining earlier discrepancies. This study aimed to compare patient characteristics, care intensity, and mortality between male and female ICU patients while examining potential age-varying sex differences.

Methods

All adult (≥18 yr) ICU patients between 2012 and 2024 were identified in the Swedish Intensive Care Registry. Multivariable logistic regression models, adjusted for age and Simplified Acute Physiology Score 3, investigated associations between patient sex and 30-day mortality, continuous renal replacement therapy, and invasive ventilation. Analyses included the entire cohort and six diagnostic subgroups. To describe the varying effect of sex across ages, a multivariable logistic regression model, using natural cubic splines, allowed age to interact with sex.

Results

This study included 303 875 ICU patients (median [interquartile range] age: 67 [51–76] yr; 42.8% female). Crude mortality was higher in male patients (odds ratio [OR] 0.94, confidence interval [CI] 0.92–0.95). In multivariable models, female sex was associated with higher 30-day mortality (OR 1.03, CI 1.01–1.05). Male patients were more likely to receive continuous renal replacement therapy and invasive ventilation. Female patients had lower mortality risk at younger ages and higher mortality risk at older ages.

Conclusions

Although males constitute a larger proportion of ICU patients and receive more advanced treatments, females have higher adjusted mortality. This is nuanced by age-specific variations, which underscore the complexity and necessity of considering age when evaluating sex-based differences in ICU outcomes.

Purpose of review

Vascular surgical patients represent one of the most complex populations in the intensive care unit, due to a combination of extensive comorbidities and high perioperative risk. Postoperative complications such as major adverse cardiovascular events, acute kidney injury, neurological complications, thromboembolism and coagulopathy are common and often intersect. We present the latest evidence on complications most encountered in critically ill patients exposed to vascular surgery and best practices for their management.

Recent findings

Although short-term mortality rates for vascular surgical procedures are decreasing, complications continue to be challenging with some procedures incurring higher long-term complication rates. Major adverse cardiovascular events, kidney injury, infections, bleeding, thrombosis and mesenteric ischaemia are some of the most common complications requiring critical care. Optimal management requires early recognition of complications, personalized organ support, and multidisciplinary coordination.

Summary

We present an updated, evidence-based overview of management strategies for critically ill vascular surgical patients, with a focus on optimizing perioperative outcomes in this high-risk population. The review highlights best practices in hemodynamic monitoring and addresses the prevention and management of common postoperative complications encountered in critical care.

Objectives This study aimed to investigate the impact of socioeconomic status and country of origin on COVID-19 outcomes in Swedish intensive care units (ICUs), hypothesising that these factors are independently associated with 90-day mortality.

Design Registry-based cohort study.

Setting Swedish ICUs, from 6 March 2020 to 31 December 2022.

Participants Adults (≥18 years) with confirmed SARS-CoV-2 infection and acute hypoxaemic respiratory failure. A total of 5833 patients were included in the multivariable model.

Interventions Not applicable.

Primary and secondary outcome measures The primary outcome was 90-day mortality. Secondary outcomes included 1-year mortality and ventilator and renal replacement therapy-free days within 60 days post-ICU admission.

Results Non-European country of origin was independently associated with higher 90-day and 1-year mortality adjusted OR (aOR) 1.34 [95% CI 1.13 to 1.61], p=0.001, aOR 1.26 [95% CI 1.01 to 1.5], p=0.01, respectively. Socioeconomic variables did not significantly impact mortality or organ support-free days. Other predictors of 90-day mortality included age, sex, chronic heart and lung disease, Simplified Acute Physiology Score 3 score, immunosuppression, time in hospital prior to ICU admission, pandemic wave and admission Partial pressure of oxygen in arterial blood/Fraction of inspired oxygen-ratio.

Conclusions The study identified significant disparities in COVID-19 outcomes based on country of origin, with non-European patients facing higher mortality risks. These findings could challenge the notion of equitable healthcare in Sweden and underscore the need for further research into systemic inequalities.

Background: A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are the traditional ICU mortality prediction models. With the emergence of machine learning (machine learning) and artificial intelligence, new possibilities arise to create prediction models that have the potential to sharpen predictive accuracy and reduce the likelihood of misclassification in the prediction of 30-day mortality. Methods: We used the Swedish Intensive Care Registry (SIR) to identify and include all patients >= 18 years of age admitted to general ICUs in Sweden from 2008 to 2022 with SAPS 3 score registered. Only data collected within 1 h of ICU admission was used. We had 153 candidate predictors including baseline characteristics, previous medical conditions, blood works, physiological parameters, cause of admission, and initial treatment. We stratified the data randomly on the outcome variable 30-day mortality and created a training set (80% of data) and a test set (20% of data). We evaluated several hundred prediction models using multiple ML frameworks including random forest, gradient boosting, neural networks, and logistic regression models. Model performance was evaluated by comparing the receiver operator characteristic area under the curve (AUC-ROC). The best performing model was fine-tuned by optimizing hyperparameters. The model's calibration was evaluated by a calibration belt. Ultimately, we simplified the best performing model with the top 1-20 predictors. Results: We included 296,344 first-time ICU admissions. We found age, Glasgow Coma Scale, creatinine, systolic blood pressure, and pH being the most important predictors. The AUC-ROC was 0.884 in test data using all predictors, specificity 95.2%, sensitivity 47.0%, negative predictive value of 87.9% and positive predictive value of 70.7%. The final model showed excellent calibration. The ICU risk evaluation for 30-day mortality (ICURE) prediction model performed equally well to the SAPS 3 score with only eight variables and improved further with the addition of more variables. Conclusion: The ICURE prediction model predicts 30-day mortality rate at first-time ICU admission superiorly compared to the established SAPS 3 score.

Svenska intensivvårdsregistret samlar in och analyserar data avseende intensivvård i Sverige. 

Data från registret kan ge en överblick gällande tillgängliga vårdplatser och beläggning på svenska intensivvårdsavdelningar samt patienternas demografiska och kliniska karakteristika och i vilken grad de överlever. 

Därigenom kan patientgrupper med sämre prognos identifieras, vilket kan vara en del i ett underlag för den enskilda patientens prognos och ger möjlighet till reflektion kring rimligheten av intensivvård och invasiva åtgärder som potentiellt kan innebära obehag för patienterna.

The Swedish Intensive Care Registry collects and analyses data regarding intensive care in Sweden. Based on this data an overview can be created regarding available hospital beds and occupancy rates in Swedish intensive care, as well as demographic and clinical characteristics of the patients, and their survival. Through this, identification of patient groups with poorer prognosis is possible, facilitating reflection of the appropriateness of intensive care and invasive procedures that may cause discomfort to the patient. 

Background: Aneurysmal subarachnoid haemorrhage (aSAH) is a life-threatening disease with high mortality and morbidity. Patients with aSAH in Sweden are cared for at one of six neuro intensive care units (NICU) or at a general intensive care unit (ICU).This study aimed to describe the incidence, length of stay, time in ventilator and mortality for these patients. Methods: This is a retrospective, descriptive study of patients with aSAH, registered in the Swedish Intensive care Registry between 2017 and 2019. The cohort was divided in sub-cohorts (NICU and general ICU) and regions. Mortality was analysed with logistic regression. Results: A total of 1520 patients with aSAH from five regions were included in the study. Mean age of the patients were 60.6 years and 58% were female. Mortality within 180 days of admission was 30% (n = 456) of which 17% (n = 258) died during intensive care. A majority of the patients were treated at one hospital and in one ICU (70%, n = 1062). More than half of the patients (59%, n = 897) had their first intensive care admission at a hospital with a NICU. Patients in the North region had the lowest median GCS (10) and the highest SAPS3 score (60) when admitted to NICU. Treatment with invasive mechanical ventilation differed significantly between regions; 91% (n = 80) in the region with highest proportion versus 56% (n = 94) in the region with the lowest proportion, as did mortality; 16% (n = 44) versus 8% (n = 23). No differences between regions were found regarding age, sex and length of stay. Conclusions: Patients with aSAH treated in a NICU or in an ICU in Sweden differs in characteristics. The study further showed some differences between regions which might be reduced if there were national consensus and treatment guidelines implemented.

BACKGROUND Mortality among patients admitted to intensive care units (ICUs) with COVID-19 is unclear due to variable follow-up periods. Few nationwide data are available to compare risk factors, treatment and outcomes of COVID-19 patients after ICU admission. OBJECTIVE To evaluate baseline characteristics, treatments and 30-day outcomes of patients admitted to Swedish ICUs with COVID-19. DESIGN Registry-based cohort study with prospective data collection. SETTING Admissions to Swedish ICUs from 6 March to 6 May 2020 with laboratory confirmed COVID-19 disease. PARTICIPANTS Adult patients admitted to Swedish ICUs. EXPOSURES Baseline characteristics, intensive care treatments and organ failures. MAIN OUTCOMES AND MEASURES The primary outcome was 30-day all-cause mortality. A multivariable model was used to determine the independent association between potential predictor variables and death. RESULTS We identified 1563 patients with complete 30-day follow-up. The 30-day all-cause mortality was 26.7%. Median age was 61 [52 to 69], Simplified Acute Physiology Score III (SAPS III) was 53 [46 to 59] and 62.5% had at least one comorbidity. Median PaO2/FiO(2) on admission was 97.5 [75.0 to 140.6] mmHg, 74.7% suffered from moderate-to-severe acute respiratory failure. Age, male sex [adjusted odds ratio (aOR) 1.5 (1.1 to 2.2)], SAPS III score [aOR 1.3 (1.2 to 1.4)], severe respiratory failure [aOR 3.0 (2.0 to 4.7)], specific COVID-19 pharmacotherapy [aOR 1.4 (1.0 to 1.9)] and continuous renal replacement therapy [aOR 2.1 (1.5 to 3.0)] were associated with increased mortality. Except for chronic lung disease, the presence of comorbidities was not independently associated with mortality. CONCLUSIONS Thirty-day mortality rate in COVID-19 patients admitted to Swedish ICUs is generally lower than previously reported despite a severe degree of hypoxaemia on admission. Mortality was driven by age, baseline disease severity, the presence and degree of organ failure, rather than pre-existing comorbidities.

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We present a case of a patient who ingested excessive amounts of the antidepressant Venlafaxine, a Selective Serotonin-Norepinephrine Reuptake Inhibitor (SNRI). She developed cardiogenic shock with clinical and echocardiographic signs of takotsubo syndrome, TTS; a life-threatening condition characterized by a transient regional cardiac dysfunction not solely caused by coronary artery occlusion. The pathogenesis remains unclear but catecholamines play a key role. Venlafaxine increases plasma catecholamine levels and with high probability it was judged to be the trigger for our patients serious state. Our case study included clinical and laboratory data, as well as a literature review on published cases of SNRI associated TTS. Most cases of TTS fortunately show spontaneous recovery of cardiac function with conservative management and supportive treatment. No evidence-based treatment recommendations exist, but traditional inotropic and vasoactive drugs are considered potentially harmful, which can be a dilemma for the treating clinician, when facing an acutely decompensated TTS patient.

Takotsubosyndrom är ett akut hjärtsviktssyndrom som är övergående och kan utlösas av flera olika faktorer.

Venlafaxin är ett antidepressivt läkemedel tillhörande gruppen SNRI vars potentierande effekt av transmittorsubstanser såsom noradrenalin kan utlösa syndromet.

Vi beskriver ett fall där venlafaxin misstänks ha utlöst ett livshotande takotsubosyndrom.

Takotsubosyndrom bör övervägas vid SNRI-intoxikation och samtidig kardiogen chock, där tidig ekokardiografi och identifiering av utflödesobstruktion av vänsterkammaren kan vägleda behandlingsval.

Åsikterna går isär om lämplig handläggning avinstabila patienter med takotsubosyndrom, där inotropaoch vasoaktiva läkemedel anses kontraindicerade, vilket kan komplicera handläggningen för den behandlande klinikern.

Background. This study was performed to develop and validate a cardiac surgical intensive care risk adjustment model for mixed cardiac surgery based on a few preoperative laboratory tests, extracorporeal circulation time, and measurements at arrival to the intensive care unit. Methods. This was a retrospective study of admissions to 5 cardiac surgical intensive care units in Sweden that submitted data to the Swedish Intensive Care Registry. Admissions from 2008 to 2014 (n = 21,450) were used for model development, whereas admissions from 2015 to 2016 (n = 6463) were used for validation. Models were built using logistic regression with transformation of raw values or categorization into groups. Results. The final model showed good performance, with an area under the receiver operating characteristics curve of 0.86 (95% confidence interval, 0.83-0.89), a Cox calibration intercept of -0.16 (95% confidence interval, -0.47 to 0.19), and a slope of 1.01 (95% confidence interval, 0.89-1.13) in the validation cohort. Conclusions. Eleven variables available on admission to the intensive care unit can be used to predict 30-day mortality after cardiac surgery. The model performance was better than those of general intensive care risk adjustment models used in cardiac surgical intensive care and also avoided the subjective assessment of the cause of admission. The standardized mortality ratio improves over time in Swedish cardiac surgical intensive care. (C) 2020 by The Society of Thoracic Surgeons