D. Reis Miranda

Nine equivalents of nursing manpower use score (NEMS)

Objectives: To develop a simplified Therapeutic Intervention Scoring System (TISS) based on the TISS-28 items and to validate the new score in an independent database. Design: Retrospective statistical analysis of a database and a prospective multicentre study. Setting: Development in the database of the Foundation for Research on Intensive Care in Europe with external validation in 64 intensive care units (ICUs) of 11 European countries. Measurements and results: Development of NEMS on a random sample of TISS-28 items, cross validation on another random sample of TISS-28, and external validation of NEMS in comparison with TISS-28 scored by two independent raters on the day of the visit to the ICUs participating in an international study. Multivariable regression techniques, Pearsons correlation, and paired sample t-tests were used (significance at p < 0.05 level). Intraclass correlation, rate of agreement, and kappa statistics were used for interrater reliability tests. The TISS-28 items were reduced to NEMS (9 items) in a random sample of 2000 records; the means of the two scores were no different: TISS-28 26.23 ± 10.38, NEMS 26.19 ± 9.12, NS. Cross-validation in a random sample of 996 records; mean TISS-28 26.13 ± 10.38, NEMS 26.17 ± 9.38, NS; R2 = 0.76. External validation on 369 pairs of TISS-28 and NEMS has shown that the means of the two scores were no different: TISS-28 27.56 ± 11.03, NEMS 27.02 ± 8.98, NS; R2 = 0.59. Reliability tests have shown an “almost perfect” interrater correlation. Similar to studies correlating TISS with Simplified Acute Physiology Score (SAPS)-I and/or Acute Physiology and Chronic Health Evaluation II scores, the value of NEMS scored on the first day accounts for 30.4 % of the variation of SAPS-II score. Conclusions: NEMS is a suitable therapeutic index to measure nursing workload at the ICU level. The use of NEMS is indicated for: (a) multicentre ICU studies; (b) management purposes in the general (macro) evaluation and comparison of workload at the ICU level; (c) the prediction of workload and planning of nursing staff allocation at the individual patient level.

Evaluation of the uniformity of fit of general outcome prediction models

Objective: To compare the performance of the New Simplified Acute Physiology Score (SAPS II) and the New Admission Mortality Probability Model (MPM II0) within relevant subgroups using formal statistical assessment (uniformity of fit). Design: Analysis of the database of a multi-centre, multi-national and prospective cohort study, involving 89 ICUs from 12 European Countries. Setting: Database of EURICUS-I. Patients: Data of 16,060 patients consecutively admitted to the ICUs were collected during a period of 4 months. Following the original SAPS II and MPM II0 criteria, the following patients were excluded from the analysis: younger than 18 years of age; readmissions; acute myocardial infarction; burn cases; patients in the post-operative period after coronary artery bypass surgery and patients with a length of stay in the ICU shorter than 8 h, resulting in a total of 10,027 cases. Interventions: Data necessary for the calculation of SAPS II and MPM II0, basic demographic statistics and vital status on hospital discharge were recorded. Formal evaluation of the performance of the models, comprising discrimination (area under ROC curve), calibration (Hosmer-Lemeshow goodness-of-fit H^ and C^ tests) and observed/expected mortality ratios within relevant subgroups. Main results: Better predictive accuracy was achieved in elective surgery patients admitted from the operative room/post-anaesthesia room with gastrointestinal, neurological or trauma diagnoses, and younger patients with non-operative neurological, septic or trauma diagnoses. All these characteristics appear to be linked to a lower severity of illness, with both models overestimating mortality in the more severely ill patients. Conclusions: Concerning the performance of the models, very large differences were apparent in relevant subgroups, varying from excellent to almost random predictive accuracy. These differences can explain some of the difficulties of the models to accurately predict mortality when applied to different populations with distinct patient baseline characteristics. This study stresses the importance of evaluating multiple diverse populations (to generate the design set) and of methods to improve the validation set before extrapolations can be made from the validation setting to new independent populations. It also underlines the necessity of a better definition of the patient baseline characteristics in the samples under analysis and the formal statistical evaluation of the application of the models to specific subgroups.

Quality of life after intensive care with the sickness impact profile

Objectivesa)to validate the structure of the Sickness Impact Profile scale (SIP) when applied to intensive care patients after discharge from the hospital.b)to explore the influence of age upon the various components of quality of life.DesignProspective study.SettingPatients admitted to 36 Dutch ICUs.Methods6247 patients out of 13000 consecutive admissions to the ICUs answered a SIP questionnaire 6 months after discharge from the hospital. The 3655 returned questionnaires were analyzed after aggregating the respondents into 6 age groups: from group 1: 17–29 up to group 4: >70 years of age.InterventionSelf-administration of SIP one year after discharge, measuring 5 independent categories (IC) and two dimensions: physical (PD) and psychosocial (PSD).ResultsThe total SIP-score oscillated between 5.8±8.2 (group I) and 10.5±9.5 (group 4). Group 3 had also a high score (9.4±11.2). Overall, the quality of life of patients was dominated by dysfunction on the categories composing the physical dimension, with exception of patients with ages between 30 and 50 years, in which dysfunction on the categories composing the psychosocial dimension was dominant. The structure of the SIP in the study was similar to that described to the original instrument.ConclusionsThe study validated the use of the SIP QOL-instrument on patients after intensive care. Age influenced consistently the various components of quality of life.

Evaluation of the antiviral response to zanamivir administered intravenously for treatment of critically ill patients with pandemic influenza A (H1N1) infection.

A retrospective nationwide study on the use of intravenous (IV) zanamivir in patients receiving intensive care who were pretreated with oseltamivir in the Netherlands was performed. In 6 of 13 patients with a sustained reduction of the viral load, the median time to start IV zanamivir was 9 days (range, 4–11 days) compared with 14 days (range, 6–21 days) in 7 patients without viral load reduction (P = .052). Viral load response did not influence mortality. We conclude that IV zanamivir as late add-on therapy has limited effectiveness. The effect of an immediate start with IV zanamivir monotherapy or in combination with other drugs need to be evaluated.

Effect of mechanical ventilation on right ventricular afterload

Mechanical ventilation has become a life-saving therapy in the treatment of patients with impaired pulmonary function. However, the dark side of mechanical ventilation has also emerged with the development of ventilator-induced lung injury [1], pneumonia, sepsis [2], and elevation of right ventricular (RV) afterload ultimately leading to a cor pulmonale [3], [4].

Isolated left ventricular failure is a predictor of poor outcome in patients receiving veno-arterial extracorporeal membrane oxygenation

We investigated survival according to the nature of heart failure (isolated left, vs isolated right, vs biventricular heart failure) in patients undergoing extracorporeal membrane oxygenation (ECMO) for refractory cardiogenic shock of different causes.

Predicting mortality while on veno-venous extracorporeal membrane oxygenation

Dear Editor, We read with great interest the paper of Pappalardo et al. [1]. In this paper, the authors constructed a very nice model predicting the mortality risk while on veno-venous extra-corporeal membrane oxygenation (vvECMO) in patients with acute respiratory distress syndrome (ARDS) due to H1N1 pneumonia. These patients were analyzed retrospectively from a large Italian vvECMO network [2]. Until publication of this paper, inclusion and exclusion criteria for vvECMO treatment were based on expert opinion [3]. The authors constructed the model from the retrospective data of 60 patients, of which 82 % had H1N1 pneumonia with a survival rate of 71 %. The remaining ARDS patients had a survival rate of 52 %. In another validation set containing 74 patients, the authors tested their model: the area under the curve (AUC) of the receiver operating characteristic (ROC) was 0.69 to predict mortality while on ECMO with a ECMOnet score [4.5 points, with a sensitivity of 51 % and a specificity of 76 %. In our center, we have treated 44 patients with vvECMO: 50 % for bacterial pneumonia, 20 % for viral pneumonia and 27 % for autoimmune pneumonitis disease. The overall survival rate while on vvECMO was 73 %. When applying the ECMOnet score to our patients, the optimal cut-off point (calculated with the Youden index) was an ECMOnet score of 6.5. The AUC with an ECMOnet score [6.5 was exactly 0.69 for predicting mortality while on ECMO with a sensitivity of 50 % and a specificity of 80 % (see Fig. 1). AUC of the oxygenation index and APACHEII was 0.52 and 0.54, respectively. Therefore, it seems that the ECMOnet score is a promising scoring system with a fair specificity in predicting mortality while on vvECMO, although with a higher cut-off point. At least, the ECMOnet score is much better than traditional scoring systems such as oxygenation index or APACHEII.

Fast confirmation of correct position of distal perfusion cannula during venoarterial extracorporeal membrane oxygenation

Lower extremity ischemia is a serious complication in patients treated with venoarterial extracorporeal membrane oxygenation (vaECMO). The Extracorporeal Life Support Organization (ELSO) database reports a 5% incidence of ischemic leg complications, leading to leg amputation in 1% of the vaECMO runs. Pacing a distal perfusion catheter (DPC) in the superficial femoral artery and confirming correct placement are essential. We present a patient with primary graft dysfunction after heart transplantation. vaECMO was instituted surgically in the right femoral artery and vein with an ipsilateral 6 Fr, 24 cm DPC (CL-07624, Arrow, Athlone, Ireland) in the common femoral artery. As a result of multiple percutaneous coronary interventions in the past, visual confirmation of the correct placement of the DPC was difficult during surgery. Postoperatively, no Doppler flow could be measured in the popliteal artery. We inserted a “J”-tipped guidewire (0.81 mm, 60 cm, CS-25855, Arrow, Athlone, Ireland) into the DPC and visualized the wire in the popliteal artery using ultrasound (Figs. 1, 2, video in the ESM), confirming the right position.