Matthes Seeling

Duration of fluid fasting and choice of analgesic are modifiable factors for early postoperative delirium.

Background and objective Most therapeutic options for postoperative delirium are only symptom oriented; therefore, the best approach remains prevention. The aim of this study was to identify predisposing and precipitating factors for early postoperative delirium. Methods A total of 1002 patients were screened for delirium in an observational, cohort study. Nine hundred and ten patients were observed in the recovery room and 862 patients on the first postoperative day in the ward at the Charité – Universitaetsmedizin, Berlin. Delirium was measured with the nursing delirium screening scale. Risk factors were analysed in a multivariate analysis. Results Delirium was seen in 11.0% of the patients in the recovery room and in 4.2% of the patients on the ward. Delirium in the recovery room was associated with delirium on the ward (McNemars test P = <0.001). Apart from age and site of surgery, we found the duration of preoperative fluid fasting to be a modifiable precipitating factor for delirium in the recovery room (odds ratio 2.69, 95% confidence interval 1.4–5.2) and on the ward (odds ratio 10.57, 95% confidence interval 1.4–78.6) and the choice of intraoperative opioid for delirium on the ward (odds ratio 2.27, 95% confidence interval 1.0–5.1). Conclusion Duration of preoperative fluid fasting and the choice of intraoperative analgesic are risk factors for postoperative delirium, and their modification provides a promising approach to reduce the incidence of postoperative delirium.

Independent risk factors for postoperative pain in need of intervention early after awakening from general anaesthesia

Despite advances in postoperative pain management, the proportion of patients with moderate to severe postoperative pain is still ranging 20–80%. In this retrospective study, we investigated 1736 patients to determine the incidence of postoperative pain in need of intervention (PPINI)defined as numeric rating scale >4 at rest in the post anaesthesia care unit early after awakening from general anaesthesia, and to identify possible risk factors. The proportion of patients with PPINI was 28.5%. On multivariate analysis, younger age (OR = 1.300 [1.007–1.678], p = 0.044), female gender (OR = 1.494 [1.138–1.962], p = 0.004), obesity (OR = 1.683 [1.226–2.310], p = 0.001), use of nitrous oxide (OR = 1.621 [1.110–2.366], p = 0.012), longer duration of surgery (OR = 1.165 [1.050–1.292], p = 0.004), location of surgery (musculoskeletal OR = 2.026 [1.326–3.095], p = 0.001; intraabdominal OR = 1.869 [1.148–3.043], p = 0.012), and ASA‐PS I–II (OR = 1.519 [1.131–2.039], P = 0.005) were identified as independent risk factors for PPINI. Patients with PPINI experienced significantly more PONV (10.3% vs. 6.2%, p = 0.003), more psychomotor agitation (5.5% vs. 2.7%, p = 0.004), needed more application of opioid in PACU (62.8% vs. 24.2%, p < 0.001), stayed significantly longer in PACU (89.6 min [70–120] vs. 80 min [60–100], p < 0.001), had a longer median length of hospital stay (6.6 days [4.0–8.8] vs. 6.0 days [3.2–7.8]], p < 0.001), and longer postoperative stay (5.0 days [3.0–6.5] vs. 4.1 days [2.5–5.8], p < 0.001]). Patients with PPINI required more piritramid (8.0 mg [5.0–12.0] vs. 5.0 mg [3.0–7.8], p < 0.001) in PACU than patients without. The identification of patients at high risk for immediate postoperative pain in need of intervention would enable the formation of effective postoperative pain management programs.

A Comparison of Three Scores to Screen for Delirium on the Surgical Ward

BackgroundPostoperative delirium is associated with adverse outcome. The aim of this study was to find a valid and easy-to-use tool to screen for postoperative delirium on the surgical ward.MethodsData were collected from 88 patients who underwent elective surgery. Delirium screening was performed daily until the sixth postoperative day using the Confusion Assessment Method (CAM), the Nursing Delirium Screening Scale (Nu-DESC), and the Delirium Detection Score (DDS), and the DSM-IV criteria as the gold standard.ResultsSeventeen of 88 patients (19%) developed delirium on at least one of the postoperative days according to the gold standard. The DDS scored positive for 40 (45%) patients, the CAM for 15 (17%), and the Nu-DESC for 28 (32%) patients. Sensitivity and specificity were 0.71 and 0.87 for the DDS, 0.75 and 1.00 for the CAM, and 0.98 and 0.92 for the Nu-DESC. The interrater reliability was 0.83 for the Nu-DESC, 0.77 for the DDS, and 1.00 for the CAM.ConclusionsAll scores showed high specificity but differed in their sensitivity. The Nu-DESC proved to be the most sensitive test for screening for a postoperative delirium on the surgical ward followed by the CAM and DDS when compared to the gold standard.

[The Intensive Care Delirium Screening Checklist (ICDSC)--translation and validation of intensive care delirium checklist in accordance with guidelines].

BACKGROUND Although Delirium is the most common psychiatric disease in ICU settings, it is recognized late or not at all in up to 84 % of all cases. METHODS Translation of the ICDSC, in accordance with ISPOR guidelines and validation by conducting a screening of 68 ICU patients. RESULTS The translation process was authorized by the original author. The final German translation of the ICDSC showed a sensitivity and specificity of 89 % and 57 % respectively. CONCLUSION The ICDSC is suitable for delirium screening by nurses even on ventilated patients. Besides a high sensitivity another advantage is the possibility to screen for a subsyndromal delirium.

Die Nursing Delirium Screening Scale (Nu–DESC) – Richtlinienkonforme Übersetzung für den deutschsprachigen Raum

BACKGROUND Both in the recovery room as well as in the intensive care unit post-operative delirium is the most common psychiatric disease. The post-operative delirium is stated in literature to occur in 15 % to 50 % of patients, whereby up to 80 % of patients requiring intensive care with artificial respiration develop a delirium. The delirium correlates with the length of hospital stay and leads to a tripple rate of the six-month-mortality. Nu-DESC, developed by Gaudreau et al. is a measuring instrument for the clinical diagnostics of deliriums which is quickly operable, care-based and which can thus be easily integrated in everyday routine. The aim of this study was the translation of Nu-DESC from English as basis for the use in clinical research and routine. MATERIALS AND METHODS The translation process was conducted in accordance with the internationally acknowledged guidelines of Translation and Cultural Adaptation of Patient Reported Outcomes Measures - Principles of Good Practice (PGP). An interim German version was developed from 3 independently devised translations, a back-translation of which was then conducted by a registered state-approved translator. The back-translation was then presented to the author of the original for evaluation. RESULTS The back-translation of the German translation was authorised by the author of the original. On the basis of the cognitive debriefing results which were consistently very good to good, the translation process could be finalised and the final German version of Nu-DESC could be passed by the expert team. An evaluation of the German Nu-DESC regarding its practicability showed significant differences between doctors and nursing staff. CONCLUSION The German version of Nu-DESC provides an instrument for evaluating the delirium in the area of clinical routine and research.

Effects of intensivist coverage in a post-anaesthesia care unit on surgical patients' case mix and characteristics of the intensive care unit

IntroductionThere is an increasing demand for intensive care in hospitals, which can lead to capacity limitations in the intensive care unit (ICU). Due to postponement of elective surgery or delayed admission of emergency patients, outcome may be negatively influenced. To optimize the admission process to intensive care, the post-anaesthesia care unit (PACU) was staffed with intensivist coverage around the clock. The aim of this study is to demonstrate the impact of the PACU on the structure of ICU-patients and the contribution to overall hospital profit in terms of changes in the case mix index for all surgical patients.MethodsThe administrative data of all surgical patients (n = 51,040) 20 months prior and 20 months after the introduction of a round-the-clock intensivist staffing of the PACU were evaluated and compared.ResultsThe relative number of patients with longer length of stay (LOS) (more than seven days) in the ICU increased after the introduction of the PACU. The average monthly number of treatment days of patients staying less than 24 hours in the ICU decreased by about 50% (138.95 vs. 68.19 treatment days, P <0.005). The mean LOS in the PACU was 0.45 (± 0.41) days, compared to 0.27 (± 0.2) days prior to the implementation. The preoperative times in the hospital decreased significantly for all patients. The case mix index (CMI) per hospital day for all surgical patients was significantly higher after the introduction of a PACU: 0.286 (± 0.234) vs. 0.309 (± 0.272) P <0.001 CMI/hospital day.ConclusionsThe introduction of a PACU and the staffing with intensive care staff might shorten the hospital LOS for surgical patients. The revenues for the hospital, as determined by the case mix index of the patients per hospital day, increased after the implementation of a PACU and more patients can be treated in the same time, due to a better use of resources.

Robust Allocation of Operating Rooms: a Cutting Plane Approach to handle Lognormal Case Durations

The problem of allocating operating rooms (OR) to surgical cases is a challenging task, involving both combinatorial aspects and uncertainty handling. We formulate this problem as a parallel machines scheduling problem, in which job durations follow a lognormal distribution, and a fixed assignment of jobs to machines must be computed. We propose a cutting-plane approach to solve the robust counterpart of this optimization problem. To this end, we develop an algorithm based on fixed-point iterations that identifies worst-case scenarios and generates cut inequalities. The main result of this article uses Hilberts projective geometry to prove the convergence of this procedure under mild conditions. We also propose two exact solution methods for a similar problem, but with a polyhedral uncertainty set, for which only approximation approaches were known. Our model can be extended to balance the load over several planning periods in a rolling horizon. We present extensive numerical experiments for instances based on real data from a major hospital in Berlin. In particular, we find that: (i) our approach performs well compared to a previous model that ignored the distribution of case durations; (ii) compared to an alternative stochastic programming approach, robust optimization yields solutions that are more robust against uncertainty, at a small price in terms of average cost; (iii) the \emph{longest expected processing time first} (LEPT) heuristic performs well and efficiently protects against extreme scenarios, but only if a good prediction model for the durations is available. Finally, we draw a number of managerial implications from these observations.