Comparative performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data

INTRODUCTION

Benchmarking intensive care units for audit and feedback is frequently based on comparing actual mortality versus predicted mortality. Traditionally, mortality prediction models rely on a limited number of input variables and significant manual data entry and curation. Using automatically extracted electronic health record data may be a promising alternative. However, adequate data on comparative performance between these approaches is currently lacking.

METHODS

The AmsterdamUMCdb intensive care database was used to construct a baseline APACHE IV in-hospital mortality model based on data typically available through manual data curation. Subsequently, new in-hospital mortality models were systematically developed and evaluated. New models differed with respect to the extent of automatic variable extraction, classification method, recalibration usage and the size of collection window.

RESULTS

A total of 13 models were developed based on data from 5,077 admissions divided into a train (80%) and test (20%) cohort. Adding variables or extending collection windows only marginally improved discrimination and calibration. An XGBoost model using only automatically extracted variables, and therefore no acute or chronic diagnoses, was the best performing automated model with an AUC of 0.89 and a Brier score of 0.10.

DISCUSSION

Performance of intensive care mortality prediction models based on manually curated versus automatically extracted electronic health record data is similar. Importantly, our results suggest that variables typically requiring manual curation, such as diagnosis at admission and comorbidities, may not be necessary for accurate mortality prediction. These proof-of-concept results require replication using multi-centre data.

Development and evaluation of regression tree models for predicting in-hospital mortality of a national registry of COVID-19 patients over six pandemic surges

BACKGROUND

Objective prognostic information is essential for good clinical decision making. In case of unknown diseases, scarcity of evidence and limited tacit knowledge prevent obtaining this information. Prediction models can be useful, but need to be not only evaluated on how well they predict, but also how stable these models are under fast changing circumstances with respect to development of the disease and the corresponding clinical response. This study aims to provide interpretable and actionable insights, particularly for clinicians. We developed and evaluated two regression tree predictive models for in-hospital mortality of COVID-19 patient at admission and 24 hours (24 h) after admission, using a national registry. We performed a retrospective analysis of observational routinely collected data.

METHODS

Two regression tree models were developed for admission and 24 h after admission. The complexity of the trees was managed via cross validation to prevent overfitting. The predictive ability of the model was assessed via bootstrapping using the Area under the Receiver-Operating-Characteristic curve, Brier score and calibration curves. The tree models were assessed on the stability of their probabilities and predictive ability, on the selected variables, and compared to a full-fledged logistic regression model that uses variable selection and variable transformations using splines. Participants included COVID-19 patients from all ICUs participating in the Dutch National Intensive Care Evaluation (NICE) registry, who were admitted at the ICU between February 27, 2020, and November 23, 2021. From the NICE registry, we included concerned demographic data, minimum and maximum values of physiological data in the first 24 h of ICU admission and diagnoses (reason for admission as well as comorbidities) for model development. The main outcome measure was in-hospital mortality. We additionally analysed the Length-of-Stay (LoS) per patient subgroup per survival status.

RESULTS

A total of 13,369 confirmed COVID-19 patients from 70 ICUs were included (with mortality rate of 28%). The optimism-corrected AUROC of the admission tree (with seven paths) was 0.72 (95% CI: 0.71-0.74) and of the 24 h tree (with 11 paths) was 0.74 (0.74-0.77). Both regression trees yielded good calibration and variable selection for both trees was stable. Patient subgroups comprising the tree paths had comparable survival probabilities as the full-fledged logistic regression model, survival probabilities were stable over six COVID-19 surges, and subgroups were shown to have added predictive value over the individual patient variables.

CONCLUSIONS

We developed and evaluated regression trees, which operate at par with a carefully crafted logistic regression model. The trees consist of homogenous subgroups of patients that are described by simple interpretable constraints on patient characteristics thereby facilitating shared decision-making.

Prognostic models of in-hospital mortality of intensive care patients using neural representation of unstructured text: A systematic review and critical appraisal

OBJECTIVE

To review and critically appraise published and preprint reports of prognostic models of in-hospital mortality of patients in the intensive-care unit (ICU) based on neural representations (embeddings) of clinical notes.

METHODS

PubMed and arXiv were searched up to August 1, 2022. At least two reviewers independently selected the studies that developed a prognostic model of in-hospital mortality of intensive-care patients using free-text represented as embeddings and extracted data using the CHARMS checklist. Risk of bias was assessed using PROBAST. Reporting on the model was assessed with the TRIPOD guideline. To assess the machine learning components that were used in the models, we present a new descriptive framework based on different techniques to represent text and provide predictions from text. The study protocol was registered in the PROSPERO database (CRD42022354602).

RESULTS

Eighteen studies out of 2,825 were included. All studies used the publicly-available MIMIC dataset. Context-independent word embeddings are widely used. Model discrimination was provided by all studies (AUROC 0.75-0.96), but measures of calibration were scarce. Seven studies used both structural clinical variables and notes. Model discrimination improved when adding clinical notes to variables. None of the models was externally validated and often a simple train/test split was used for internal validation. Our critical appraisal demonstrated a high risk of bias in all studies and concerns regarding their applicability in clinical practice.

CONCLUSION

All studies used a neural architecture for prediction and were based on one publicly available dataset. Clinical notes were reported to improve predictive performance when used in addition to only clinical variables. Most studies had methodological, reporting, and applicability issues. We recommend reporting both model discrimination and calibration, using additional data sources, and using more robust evaluation strategies, including prospective and external validation. Finally, sharing data and code is encouraged to improve study reproducibility.

Automated identification of patient subgroups: A case-study on mortality of COVID-19 patients admitted to the ICU

BACKGROUND

- Subgroup discovery (SGD) is the automated splitting of the data into complex subgroups. Various SGD methods have been applied to the medical domain, but none have been extensively evaluated. We assess the numerical and clinical quality of SGD methods.

METHOD

- We applied the improved Subgroup Set Discovery (SSD++), Patient Rule Induction Method (PRIM) and APRIORI - Subgroup Discovery (APRIORI-SD) algorithms to obtain patient subgroups on observational data of 14,548 COVID-19 patients admitted to 73 Dutch intensive care units. Hospital mortality was the clinical outcome. Numerical significance of the subgroups was assessed with information-theoretic measures. Clinical significance of the subgroups was assessed by comparing variable importance on population and subgroup levels and by expert evaluation.

RESULTS

- The tested algorithms varied widely in the total number of discovered subgroups (5-62), the number of selected variables, and the predictive value of the subgroups. Qualitative assessment showed that the found subgroups make clinical sense. SSD++ found most subgroups (n = 62), which added predictive value and generally showed high potential for clinical use. APRIORI-SD and PRIM found fewer subgroups (n = 5 and 6), which did not add predictive value and were clinically less relevant.

CONCLUSION

- Automated SGD methods find clinical subgroups that are relevant when assessed quantitatively (yield added predictive value) and qualitatively (intensivists consider the subgroups significant). Different methods yield different subgroups with varying degrees of predictive performance and clinical quality. External validation is needed to generalize the results to other populations and future research should explore which algorithm performs best in other settings.

The daily updated Dutch national database on COVID-19 epidemiology, vaccination and sewage surveillance

The Dutch national open database on COVID-19 has been incrementally expanded since its start on 30 April 2020 and now includes datasets on symptoms, tests performed, individual-level positive cases and deaths, cases and deaths among vulnerable populations, settings of transmission, hospital and ICU admissions, SARS-CoV-2 variants, viral loads in sewage, vaccinations and the effective reproduction number. This data is collected by municipal health services, laboratories, hospitals, sewage treatment plants, vaccination providers and citizens and is cleaned, analysed and published, mostly daily, by the National Institute for Public Health and the Environment (RIVM) in the Netherlands, using automated scripts. Because these datasets cover the key aspects of the pandemic and are available at detailed geographical level, they are essential to gain a thorough understanding of the past and current COVID-19 epidemiology in the Netherlands. Future purposes of these datasets include country-level comparative analysis on the effect of non-pharmaceutical interventions against COVID-19 in different contexts, such as different cultural values or levels of socio-economic disparity, and studies on COVID-19 and weather factors.

Association between early cumulative fluid balance and successful liberation from invasive ventilation in COVID-19 ARDS patients — insights from the PRoVENT-COVID study: a national, multicenter, observational cohort analysis

Background

Increasing evidence indicates the potential benefits of restricted fluid management in critically ill patients. Evidence lacks on the optimal fluid management strategy for invasively ventilated COVID-19 patients. We hypothesized that the cumulative fluid balance would affect the successful liberation of invasive ventilation in COVID-19 patients with acute respiratory distress syndrome (ARDS).

Methods

We analyzed data from the multicenter observational ‘PRactice of VENTilation in COVID-19 patients’ study. Patients with confirmed COVID-19 and ARDS who required invasive ventilation during the first 3 months of the international outbreak (March 1, 2020, to June 2020) across 22 hospitals in the Netherlands were included. The primary outcome was successful liberation of invasive ventilation, modeled as a function of day 3 cumulative fluid balance using Cox proportional hazards models, using the crude and the adjusted association. Sensitivity analyses without missing data and modeling ARDS severity were performed.

Results

Among 650 patients, three groups were identified. Patients in the higher, intermediate, and lower groups had a median cumulative fluid balance of 1.98 L (1.27–7.72 L), 0.78 L (0.26–1.27 L), and − 0.35 L (− 6.52–0.26 L), respectively. Higher day 3 cumulative fluid balance was significantly associated with a lower probability of successful ventilation liberation (adjusted hazard ratio 0.86, 95% CI 0.77–0.95, P = 0.0047). Sensitivity analyses showed similar results.

Conclusions

In a cohort of invasively ventilated patients with COVID-19 and ARDS, a higher cumulative fluid balance was associated with a longer ventilation duration, indicating that restricted fluid management in these patients may be beneficial.

Trial registration Clinicaltrials.gov (NCT04346342); Date of registration: April 15, 2020.

Graphical abstract

Comparison of outcome and characteristics between 6343 COVID-19 patients and 2256 other community-acquired viral pneumonia patients admitted to Dutch ICUs

Purpose

Describe the differences in characteristics and outcomes between COVID-19 and other viral pneumonia patients admitted to Dutch ICUs.

Materials and methods

Data from the National-Intensive-Care-Evaluation-registry of COVID-19 patients admitted between February 15th and January 1th 2021 and other viral pneumonia patients admitted between January 1st 2017 and January 1st 2020 were used. Patients' characteristics, the unadjusted, and adjusted in-hospital mortality were compared.

Results

6343 COVID-19 and 2256 other viral pneumonia patients from 79 ICUs were included. The COVID-19 patients included more male (71.3 vs 49.8%), had a higher Body-Mass-Index (28.1 vs 25.5), less comorbidities (42.2 vs 72.7%), and a prolonged hospital length of stay (19 vs 9 days). The COVID-19 patients had a significantly higher crude in-hospital mortality rate (Odds ratio (OR) = 1.80), after adjustment for patient characteristics and ICU occupancy rate the OR was respectively 3.62 and 3.58.

Conclusion

Higher mortality among COVID-19 patients could not be explained by patient characteristics and higher ICU occupancy rates, indicating that COVID-19 is more severe compared to other viral pneumonia. Our findings confirm earlier warnings of a high need of ICU capacity and high mortality rates among relatively healthy COVID-19 patients as this may lead to a higher mental workload for the staff.

Linking of global intensive care (LOGIC): An international benchmarking in critical care initiative

Benchmarking is a common and effective method for measuring and analyzing ICU performance. With the existence of national registries, objective information can now be obtained to allow benchmarking of ICU care within and between countries. The present manuscript briefly describes the current status of benchmarking in healthcare and critical care and presents the LOGIC project, an initiative to promote international benchmarking for intensive care units. Currently 13 registries have joined LOGIC. We showed large differences in the utilization of ICU as well as resources and in outcomes. Despite the need for careful interpretation of differences due to variation in definitions and limited risk adjustment, LOGIC is a growing worldwide initiative that allows access to insightful epidemiologic data from ICUs in multiple databases and registries.

The effect of ICU-tailored drug-drug interaction alerts on medication prescribing and monitoring: protocol for a cluster randomized stepped-wedge trial

Background

Drug-drug interactions (DDIs) can cause patient harm. Between 46 and 90% of patients admitted to the Intensive Care Unit (ICU) are exposed to potential DDIs (pDDIs). This rate is twice as high as patients on general wards. Clinical decision support systems (CDSSs) have shown their potential to prevent pDDIs. However, the literature shows that there is considerable room for improvement of CDSSs, in particular by increasing the clinical relevance of the pDDI alerts they generate and thereby reducing alert fatigue. However, consensus on which pDDIs are clinically relevant in the ICU setting is lacking. The primary aim of this study is to evaluate the effect of alerts based on only clinically relevant interactions for the ICU setting on the prevention of pDDIs among Dutch ICUs.

Methods

To define the clinically relevant pDDIs, we will follow a rigorous two-step Delphi procedure in which a national expert panel will assess which pDDIs are perceived clinically relevant for the Dutch ICU setting. The intervention is the CDSS that generates alerts based on the clinically relevant pDDIs. The intervention will be evaluated in a stepped-wedge trial. A total of 12 Dutch adult ICUs using the same patient data management system, in which the CDSS will operate, were invited to participate in the trial. Of the 12 ICUs, 9 agreed to participate and will be enrolled in the trial. Our primary outcome measure is the incidence of clinically relevant pDDIs per 1000 medication administrations.

Discussion

This study will identify pDDIs relevant for the ICU setting. It will also enhance our understanding of the effectiveness of alerts confined to clinically relevant pDDIs. Both of these contributions can facilitate the successful implementation of CDSSs in the ICU and in other domains as well.

Trial registration

Nederlands Trial register Identifier: NL6762. Registered November 26, 2018.

Trends in practice of blood glucose control in critically ill patients in the Netherlands

BACKGROUND

Publication of the Normoglycemia in Intensive Care Evaluation and Survival Using Glucose Algorithm Regulation (NICE-SUGAR) trial in 2009 and several observational studies caused a change in the recommendations for blood glucose control in intensive care patients. We evaluated local trends in blood glucose control in intensive care units in the Netherlands before and after the publication of the NICE-SUGAR trial and the revised Surviving Sepsis Campaign (SSC) guidelines in 2012.

METHODS

Survey focusing on the timing of changes in thresholds in local guidelines for blood glucose control and interrupted time-series analysis of patients admitted to seven intensive care units in the Netherlands from September 2008 through July 2014. Statistical process control was used to visualise and analyse trends in metrics for blood glucose control in association with the moment changes became effective.

RESULTS

Overall, the mean blood glucose level increased and the median percentage of blood glucose levels within the normoglycaemic range and in the hypoglycaemic range decreased, while the relative proportion of hyperglycaemic measurements increased. Changes in metrics were notable after publication of the NICE-SUGAR trial and the SSC guidelines but more frequent after changes in local guidelines; some changes seemed to appear independent of changes in local guidelines.

CONCLUSION

Local guidelines for blood glucose practice have changed in intensive care units in the Netherlands since the publication of the NICE-SUGAR trial and the revised SSC guidelines. Trends in the metrics for blood glucose control suggest new, higher target ranges for blood glucose control.

Recommendations for intensive care follow-up clinics; report from a survey and conference of Dutch intensive cares

BACKGROUND

With the increasing awareness of postintensive care syndrome and the unbridled development of post-ICU clinics in the Netherlands, guidelines for ICU after care are needed. The purpose of this study was to develop recommendations for the set-up of post-ICU clinics.

METHODS

Recommendations regarding the design of post-ICU clinics were formulated based on a survey among Dutch ICUs and the available literature. Subsequently, in a round table conference stakeholders discussed and voted on a final approval of the recommendations.

RESULTS

The response rate of our survey was 70% (57 of 82), 40% of the respondents provided ICU after care. Twenty-one people from 16 ICUs participated in the round table conference. Only two studies are available with information on organization and effectiveness of post-ICU clinics. It is recommended to invite patients who are mechanically ventilated for more than 2 days at a post-ICU clinic between 6 and 12 weeks after hospital discharge and screen for physical, psychological and cognitive impairments by using validated electronic patient-reported questionnaires. The set-up of a national registry for benchmarking and research purposes is suggested.

CONCLUSION

This study recommends how to organize post-ICU clinics based on literature and expert opinion. The implementation of the recommendations will facilitate the set-up of post-ICU clinics, research on effectiveness of post-ICU clinics and benchmarking of quality of ICU care.

Positive end-expiratory pressure following coronary artery bypass grafting

BACKGROUND

Cardiac surgery-related pulmonary complications include alterations in lung mechanics and anomalies in gas exchange. Higher levels of positive end-expiratory pressure (PEEP) have been suggested to benefit cardiac surgical patients. We compared respiratory compliance, arterial oxygenation and time till tracheal extubation in 2 cohorts of patients weaned from mechanical ventilation with different levels of PEEP after elective and uncomplicated coronary artery bypass grafting (CABG). We hypothesized that higher PEEP levels improve pulmonary compliance and gas exchange in the first hours of weaning from mechanical ventilation, but not to shorten time till tracheal extubation.

METHODS

Secondary retrospective analysis of 2 randomized controlled trials: in the first trial patients were weaned with PEEP levels of 10 cmH2O for the first 4 hours followed by PEEP levels of 5 cmH2O until tracheal extubation (high PEEP, HP); and the second trial patients were weaned with PEEP levels of 5 cmH2O during the entire weaning phase (low PEEP, LP). The primary endpoint was pulmonary compliance. Secondary endpoints included arterial oxygenation, duration of mechanical ventilation and postoperative pulmonary complications.

RESULTS

The analysis included 121 patients; 60 HP patients and 61 LP patients. Baseline characteristics were similar. Compared to LP patients, HP patients had a better pulmonary compliance, 47.2±14.1 versus 42.7±10.2 ml/cmH2O (P<0.05), and higher levels of PaO2, 18.5±6.6 (138.75±49.5) versus 16.7±5.4 (125.25±40.5) kPa (mmHg) (P<0.05). Patients in the HP group were less frequent in need of supplementary oxygen after ICU discharge. These differences remained present during the entire weaning phase, even after reduction of PEEP. However, HP patients had a longer time till tracheal extubation, 16.9±6.1 versus 10.5±5.0 hours (P<0.001). HP patients had longer durations of postoperative infusion of propofol, 4.9 (2.6-7.4) versus 3.5 (1.8-5.8) hours (P<0.05). There were no differences in use of inotropes. Cumulative fluid balances were slightly higher in HP patients.

CONCLUSION

Use of higher PEEP levels after elective uncomplicated CABG improves pulmonary compliance and oxygenation but seems to be associated with a delay in tracheal extubation.

Five years of therapeutic drug monitoring in the intensive care did not change vancomycin prescription behaviour: perceived needs for decision support

BACKGROUND

This study aims to assess clinicians' behaviour in prescribing vancomycin in the Intensive Care Unit (ICU) and their adherence to local guidelines for therapeutic drug monitoring (TDM).

METHODS

In this observational cohort study we included all consecutive patients admitted to a 28-bed multidisciplinary mixed adult ICU of a large university hospital in Amsterdam between January 2002 and September 2007 who were prescribed vancomycin for ≥ 3 days. We measured guideline adherence by checking for each given advice the corresponding action and monitored adherence over time using Statistical Process Control.

RESULTS

In 475 patients prescribed vancomycin, 1336 serum concentrations were measured, of which 598 in time and 738 with a median delay of 31 hours. Dose or dose frequency adjustments were often not done (54% in advice 2 [half dose frequency] and 86% in advice 4 [increase dose with 50%]) or not done concordantly (32% in advice 2 [half dose frequency] and 60% in advice 7 [half dose frequency if trough serum concentration]). Although adherence was stable over time, the average level was low (58.7%).

CONCLUSION

Five years of TDM did not achieve the desired prescription behaviour in the ICU and clinicians feel there is a need for computerized decision support. Local projects should measure adherence and implement appropriate solutions.

Early predictability of the need for tracheotomy after admission to ICU: an observational study

BACKGROUND

The goal of this study was to explore the ability of professional judgment to predict the need for tracheotomy early among intensive care unit (ICU) patients.

METHODS

Prospective study using daily questionnaires among ICU physicians in a mixed medical-surgical ICU. The prediction of tracheotomy was by a visual analogue scale (VAS, from 1 to 10, with 1 representing 'absolutely no need for tracheotomy' and 10 representing 'pertinent need for tracheotomy') during ICU stay until tracheal extubation or tracheotomy. For the purpose of this study, a VAS score ≥ 8 was considered a positive prediction for tracheotomy.

RESULTS

A total of 476 questionnaires were retrieved for 75 patients (6.4 ± 5.2 questionnaires per patient), of which 11 patients finally proceeded with a tracheostomy. At first assessment (mean of 2.4 ± 0.8 days after ICU admittance), ICU physicians predicted the need for tracheotomy 3.0 (2.0-6.0) higher VAS points for patients who were finally tracheotomized (P<0.01). Patients with a positive prediction had a 5.4 (1.2-24.1) higher chance of receiving tracheotomy (P=0.03). Considering the median VAS score over a maximum of 10 days before tracheotomy, ICU physicians scored tracheotomized patients significantly higher from day 8 onwards. When comparing ICU physicians, fellows and residents separately, only staff physicians scored a significant difference in the VAS score (P<0.05).

CONCLUSION

ICU physicians are able to differentiate between patients in need for tracheotomy from those who do not, within 2 days from admittance. The closer the time to the actual intervention, the better the physicians are able to predict this decision.

Tracheostomy: current practice on timing, correction of coagulation disorders and peri-operative management - a postal survey in the Netherlands

BACKGROUND

Several factors may delay tracheostomy. As many critically ill patients either suffer from coagulation abnormalities or are being treated with anticoagulants, fear of bleeding complications during the procedure may also delay tracheostomy. It is unknown whether such (usually mild) coagulation abnormalities are corrected first and to what extent. The purpose of this study was to ascertain current practice of tracheostomy in the Netherlands with regard to timing, pre-operative correction of coagulation disorders and peri-/intra-operative measures.

METHODS

In October 2005, a questionnaire was sent to the medical directors of all non-pediatric ICUs with >/=5 beds suitable for mechanical ventilation in the Netherlands.

RESULTS

A response was obtained from 44 (64%) out of 69 ICUs included in the survey. Seventy-five percent of patients receive tracheostomy within 2 days after the decision to proceed with a tracheostomy. Reasons indicated as frequent causes for delay were most often logistical factors. A heterogeneous attitude exists regarding values of coagulation parameters acceptable to perform tracheostomy. Fifty percent of the respondents have no guideline on correction of coagulation disorders or anticoagulant therapy before tracheostomy. Antimicrobial prophylaxis is almost never administered before tracheostomy. Forty-eight percent mentioned always using endoscopic guidance and 66% of ICUs only perform chest radiography on indication.

CONCLUSIONS

There is a high variation in peri- and intra-operative practice of tracheostomy in the Netherlands. Especially on the subject of coagulation and tracheostomy there are different opinions and protocols are often lacking.

Effects of prolonged intensive care unit stay on quality of life and long-term survival after transthoracic esophageal resection

OBJECTIVE

There are few prospective data on the effects of prolonged intensive care unit stay on the quality of life and long-term survival of a homogeneous patient population. Therefore, the aims of this prospective study were a) to describe the quality of life in patients after having a transthoracic esophageal resection; and b) to analyze the influences of a prolonged intensive care unit stay on quality of life and survival in patients after esophageal cancer resection who survived to hospital discharge.

DESIGN

Prospective study.

SETTING

Medical center.

PATIENTS

The study population consisted of 109 patients undergoing a transthoracic resection for adenocarcinoma of the middistal esophagus or gastric cardia between April 1994 and February 2000.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

A comparison was made between patients staying <or=5 days vs. >or=6 days in the intensive care unit and also <or=2 days vs. >or=14 days. Quality of life was assessed in all patients by mailed self-report questionnaires at baseline (preoperatively), at 5 wks, and at 3, 6, 9, 12, 18, 24, 30, and 36 months after surgery. Daily physical, emotional, and social functioning was assessed with the generic Medical Outcome Studies Short Form-20. Disease-specific quality of life was measured by an adapted Rotterdam Symptom Check List. Quality of life data were gathered between July 1994 and March 2003. Five of the 109 patients died in the hospital and were excluded from the analysis. All five of them were in the intensive care unit >or=6 days. Of the remaining 104 patients, 92 provided baseline scores. The data of the 92 patients were used for the quality of life analyses. For the clinicopathologic and survival analysis, the data of 104 hospital survivors were used. Patients spent a median of 5.5 days (range 0-71) in the intensive care unit. The Medical Outcome Studies Short Form-20 and the Rotterdam Symptom Check List measurements showed no clear differences in long-term quality of life between patients after a short vs. a prolonged postoperative intensive care unit period. The median overall survival in all patients was 2.0 yrs (range 0.1-8.0). Median overall survival in patients staying in the intensive care unit <or=5 days was 1.9 yrs (range 0.3-7.4 yrs) vs. 2.7 yrs (range 0.9-7.2 yrs) in patients staying >or=6 days (p = .9, log-rank test). Median overall survival in patients staying in the intensive care unit <or=2 days was 1.7 yrs (range 1.2-2.6 yrs) vs. 2.0 yrs (range 0.2-3.8 yrs) in patients staying >or=14 days (p = .74, log-rank test).

CONCLUSIONS

For patients who survived to hospital discharge after transthoracic esophagectomy, there was no difference in long-term quality of life or survival between those submitted to the intensive care unit for a short period vs. a long period.

[Percutaneous dilatating tracheostomy in intensive-care patients: technique, indications and complications]

Since tracheal cannulas are increasingly used to wean intensive-care patients from respiratory machines, more doctors and nurses will find themselves having to take care of patients with tracheostomas. Indications for tracheal cannula use include the likelihood of prolonged mechanical ventilation and/or difficult weaning. Percutaneous dilatational tracheotomy is a relatively simple procedure for inserting a tracheal cannula. It is performed using a modified Seldinger technique, carried out under general anaesthesia; use of a bronchoscope during the operation makes the procedure simpler and safer. When it is difficult to pinpoint the source of problems arising in patients fitted with a tracheal cannula, it must always be considered that the cannula might be the cause. Although rare, complications may arise several weeks or months after decanulation, such as stenosis of the trachea, changes in voice and fistula formation between the trachea and skin. A strict surveillance protocol is needed to recognize and treat late complication.

Inefficacy of high-dose transdermal fentanyl in a patient with neuropathic pain, a case report

Pain partially responsive to opioids can lead to rapid escalating dosages due to tolerance development. In this report the case of a 58-year-old female with neuropathic pain using increasing transdermal (TTS) fentanyl dosages to a maximum dose of 3400 microg/h resulting in fentanyl plasma levels of 173 ng/ml is described. For pain relief an epidural infusion at the level T1-2 with bupivacaine was started. Immediate pain relief was accompanied by short lasting respiratory depression and drowsiness.

The routine use of fresh frozen plasma in operations with cardiopulmonary bypass is not justified

BACKGROUND

The negative influence of cardiopulmonary bypass on hemostasis has been documented. Although abnormalities in platelet function are reported as the major cause of postoperative blood loss related to this hemostasis defect, fresh frozen plasma is often used in operations with cardiopulmonary bypass because it is thought to contribute to the reduction of postoperative bleeding complications. This study was designed to evaluate the effect of the administration of fresh frozen plasma after cardiopulmonary bypass on blood loss, transfusion requirements, and a number of coagulation parameters.

METHODS

In a prospective, randomized, double-blind clinical trial 50 patients (mean age 63 years; 35 men/15 women) undergoing elective operation with cardiopulmonary bypass were randomly assigned to one of two groups: group I (n = 24) received 3 units of fresh frozen plasma after operation and group II (n = 26) received an equal amount of Gelofusine plasma substitute. At seven points before, during, and after operation hemoglobin concentration, hematocrit level, thrombocyte count, and coagulation parameters were analyzed. Study endpoints were the volume of blood loss and the transfusion requirement.

RESULTS

There were no significant differences between the two study groups in blood loss, transfusion requirement, coagulation parameters, or thrombocyte counts.

CONCLUSION

The routine use of fresh frozen plasma in operations with cardiopulmonary bypass cannot be recommended.