Although numerous risk factors for delirium in the ICU have been proposed, the strength of evidence supporting each risk factor remains unclear. This study systematically identifies risk factors for ...delirium in critically ill adults where current evidence is strongest.
CINAHL, EMBASE, MEDLINE, the Cochrane Central Register for Controlled Trials, and the Cochrane Database of Systematic Reviews.
Studies published from 2000 to February 2013 that evaluated critically ill adults, not undergoing cardiac surgery, for delirium, and used either multivariable analysis or randomization to evaluate variables as potential risk factors for delirium.
Data were abstracted in duplicate, and quality was scored using Scottish Intercollegiate Guidelines Network checklists (i.e., high, acceptable, and low). Using a best-evidence synthesis each variable was evaluated using 3 criteria: the number of studies investigating it, the quality of these studies, and whether the direction of association was consistent across the studies. Strengths of association were not summarized. Strength of evidence was defined as strong (consistent findings in ≥2 high quality studies), moderate (consistent findings in 1 high quality study and ≥1 acceptable quality studies), inconclusive (inconsistent findings or 1 high quality study or consistent findings in only acceptable quality/low quality studies) or no evidence available.
Among 33 studies included, 70% were high quality. There was strong evidence that age, dementia, hypertension, pre-ICU emergency surgery or trauma, Acute Physiology and Chronic Health Evaluation II score, mechanical ventilation, metabolic acidosis, delirium on the prior day, and coma are risk factors for delirium, that gender is not associated with delirium, and that use of dexmedetomidine is associated with a lower delirium prevalence. There is moderate evidence that multiple organ failure is a risk factor for delirium.
Only 11 putative risk factors for delirium are supported by either strong or moderate level of evidence. These factors should be considered when designing delirium prevention strategies or controlling for confounding in future etiologic studies.
Severe pain after surgery remains a major problem, occurring in 20-40% of patients. Despite numerous published studies, the degree of pain following many types of surgery in everyday clinical ...practice is unknown. To improve postoperative pain therapy and develop procedure-specific, optimized pain-treatment protocols, types of surgery that may result in severe postoperative pain in everyday practice must first be identified.
This study considered 115,775 patients from 578 surgical wards in 105 German hospitals. A total of 70,764 patients met the inclusion criteria. On the first postoperative day, patients were asked to rate their worst pain intensity since surgery (numeric rating scale, 0-10). All surgical procedures were assigned to 529 well-defined groups. When a group contained fewer than 20 patients, the data were excluded from analysis. Finally, 50,523 patients from 179 surgical groups were compared.
The 40 procedures with the highest pain scores (median numeric rating scale, 6-7) included 22 orthopedic/trauma procedures on the extremities. Patients reported high pain scores after many "minor" surgical procedures, including appendectomy, cholecystectomy, hemorrhoidectomy, and tonsillectomy, which ranked among the 25 procedures with highest pain intensities. A number of "major" abdominal surgeries resulted in comparatively low pain scores, often because of sufficient epidural analgesia.
Several common minor- to medium-level surgical procedures, including some with laparoscopic approaches, resulted in unexpectedly high levels of postoperative pain. To reduce the number of patients suffering from severe pain, patients undergoing so-called minor surgery should be monitored more closely, and postsurgical pain treatment needs to comply with existing procedure-specific pain-treatment recommendations.
Many studies have analyzed risk factors for the development of severe postoperative pain with contradictory results. To date, the association of risk factors with postoperative pain intensity among ...different surgical procedures has not been studied and compared.
The authors selected precisely defined surgical groups (at least 150 patients each) from prospectively collected perioperative data from 105 German hospitals (2004-2010). The association of age, sex, and preoperative chronic pain intensity with worst postoperative pain intensity was studied with multiple linear and logistic regression analyses. Pooled data of the selected surgeries were studied with random-effect analysis.
Thirty surgical procedures with a total number of 22,963 patients were compared. In each surgical procedure, preoperative chronic pain intensity and younger age were associated with higher postoperative pain intensity. A linear decline of postoperative pain with age was found. Females reported more severe pain in 21 of 23 surgeries. Analysis of pooled surgical groups indicated that postoperative pain decreased by 0.28 points (95% CI, 0.26 to 0.31) on the numeric rating scale (0 to 10) per decade age increase and postoperative pain increased by 0.14 points (95% CI, 0.13 to 0.15) for each higher score on the preoperative chronic pain scale. Females reported 0.29 points (95% CI, 0.22 to 0.37) higher pain intensity.
Independent of the type and extent of surgery, preoperative chronic pain and younger age were associated with higher postoperative pain. Females consistently reported slightly higher pain scores regardless of the type of surgery. The clinical significance of this small sex difference has to be analyzed in future studies.
Objective To provide an overview of prediction models for risk of cardiovascular disease (CVD) in the general population.Design Systematic review.Data sources Medline and Embase until June ...2013.Eligibility criteria for study selection Studies describing the development or external validation of a multivariable model for predicting CVD risk in the general population.Results 9965 references were screened, of which 212 articles were included in the review, describing the development of 363 prediction models and 473 external validations. Most models were developed in Europe (n=167, 46%), predicted risk of fatal or non-fatal coronary heart disease (n=118, 33%) over a 10 year period (n=209, 58%). The most common predictors were smoking (n=325, 90%) and age (n=321, 88%), and most models were sex specific (n=250, 69%). Substantial heterogeneity in predictor and outcome definitions was observed between models, and important clinical and methodological information were often missing. The prediction horizon was not specified for 49 models (13%), and for 92 (25%) crucial information was missing to enable the model to be used for individual risk prediction. Only 132 developed models (36%) were externally validated and only 70 (19%) by independent investigators. Model performance was heterogeneous and measures such as discrimination and calibration were reported for only 65% and 58% of the external validations, respectively.Conclusions There is an excess of models predicting incident CVD in the general population. The usefulness of most of the models remains unclear owing to methodological shortcomings, incomplete presentation, and lack of external validation and model impact studies. Rather than developing yet another similar CVD risk prediction model, in this era of large datasets, future research should focus on externally validating and comparing head-to-head promising CVD risk models that already exist, on tailoring or even combining these models to local settings, and investigating whether these models can be extended by addition of new predictors.
Postoperative stroke is a rare but major complication after surgery. The most often proposed mechanism is an embolus originating from the heart or great vessels. The role of intraoperative ...hypotension in the occurrence and evolution of postoperative stroke is largely unknown.
A case-control study was conducted among 48,241 patients who underwent noncardiac and nonneurosurgical procedures in the period from January 2002 to June 2009. A total of 42 stroke cases (0.09%) were matched on age and type of surgery to 252 control patients. Conditional logistic regression analysis was used to estimate the effect of the duration of intraoperative hypotension (defined according to a range of blood pressure thresholds) on the occurrence of an ischemic stroke within 10 days after surgery, adjusted for potential confounding factors.
After correction for potential confounders and multiple testing, the duration that the mean blood pressure was decreased more than 30% from baseline remained statistically significantly associated with the occurrence of a postoperative stroke.
Intraoperative hypotension might play a role in the development of postoperative ischemic stroke. Especially for mean blood pressure values decreasing more than 30% from baseline blood pressure, an association with postoperative ischemic stroke risks was observed.
Failure to recognize acute deterioration in hospitalized patients may contribute to cardiopulmonary arrest, unscheduled intensive care unit admission and increased mortality.
In this systematic ...review we aimed to determine whether continuous non-invasive respiratory monitoring improves early diagnosis of patient deterioration and reduces critical incidents on hospital wards.
Studies were retrieved from Medline, Embase, CINAHL, and the Cochrane library, searched from 1970 till October 25, 2014.
Electronic databases were searched using keywords and corresponding synonyms 'ward', 'continuous', 'monitoring' and 'respiration'. Pediatric, fetal and animal studies were excluded.
Since no validated tool is currently available for diagnostic or intervention studies with continuous monitoring, methodological quality was assessed with a modified tool based on modified STARD, CONSORT, and TREND statements.
Six intervention and five diagnostic studies were included, evaluating the use of eight different devices for continuous respiratory monitoring. Quantitative data synthesis was not possible because intervention, study design and outcomes differed considerably between studies. Outcomes estimates for the intervention studies ranged from RR 0.14 (0.03, 0.64) for cardiopulmonary resuscitation to RR 1.00 (0.41, 2.35) for unplanned ICU admission after introduction of continuous respiratory monitoring.
The methodological quality of most studies was moderate, e.g. 'before-after' designs, incomplete reporting of primary outcomes, and incomplete clinical implementation of the monitoring system.
Based on the findings of this systematic review, implementation of routine continuous non-invasive respiratory monitoring on general hospital wards cannot yet be advocated as results are inconclusive, and methodological quality of the studies needs improvement. Future research in this area should focus on technology explicitly suitable for low care settings and tailored alarm and treatment algorithms.
To identify patients at risk for postoperative myocardial injury and death, measuring cardiac troponin routinely after noncardiac surgery has been suggested. Such monitoring was implemented in our ...hospital. The aim of this study was to determine the predictive value of postoperative myocardial injury, as measured by troponin elevation, on 30-day mortality after noncardiac surgery.
This observational, single-center cohort study included 2232 consecutive intermediate- to high-risk noncardiac surgery patients aged ≥60 years who underwent surgery in 2011. Troponin was measured on the first 3 postoperative days. Log binomial regression analysis was used to estimate the association between postoperative myocardial injury (troponin I level >0.06 μg/L) and all-cause 30-day mortality. Myocardial injury was found in 315 of 1627 patients in whom troponin I was measured (19%). All-cause death occurred in 56 patients (3%). The relative risk of a minor increase in troponin (0.07-0.59 μg/L) was 2.4 (95% confidence interval, 1.3-4.2; P<0.01), and the relative risk of a 10- to 100-fold increase in troponin (≥0.60 μg/L) was 4.2 (95% confidence interval, 2.1-8.6; P<0.01). A myocardial infarction according to the universal definition was diagnosed in 10 patients (0.6%), of whom 1 (0.06%) had ST-segment elevation myocardial infarction.
Postoperative myocardial injury is an independent predictor of 30-day mortality after noncardiac surgery. Implementation of postoperative troponin monitoring as standard of care is feasible and may be helpful in improving the prognosis of patients undergoing noncardiac surgery.
Objective To identify existing prediction models for the risk of development of type 2 diabetes and to externally validate them in a large independent cohort.Data sources Systematic search of ...English, German, and Dutch literature in PubMed until February 2011 to identify prediction models for diabetes.Design Performance of the models was assessed in terms of discrimination (C statistic) and calibration (calibration plots and Hosmer-Lemeshow test).The validation study was a prospective cohort study, with a case cohort study in a random subcohort. Setting Models were applied to the Dutch cohort of the European Prospective Investigation into Cancer and Nutrition cohort study (EPIC-NL). Participants 38 379 people aged 20-70 with no diabetes at baseline, 2506 of whom made up the random subcohort.Outcome measure Incident type 2 diabetes. Results The review identified 16 studies containing 25 prediction models. We considered 12 models as basic because they were based on variables that can be assessed non-invasively and 13 models as extended because they additionally included conventional biomarkers such as glucose concentration. During a median follow-up of 10.2 years there were 924 cases in the full EPIC-NL cohort and 79 in the random subcohort. The C statistic for the basic models ranged from 0.74 (95% confidence interval 0.73 to 0.75) to 0.84 (0.82 to 0.85) for risk at 7.5 years. For prediction models including biomarkers the C statistic ranged from 0.81 (0.80 to 0.83) to 0.93 (0.92 to 0.94). Most prediction models overestimated the observed risk of diabetes, particularly at higher observed risks. After adjustment for differences in incidence of diabetes, calibration improved considerably.Conclusions Most basic prediction models can identify people at high risk of developing diabetes in a time frame of five to 10 years. Models including biomarkers classified cases slightly better than basic ones. Most models overestimated the actual risk of diabetes. Existing prediction models therefore perform well to identify those at high risk, but cannot sufficiently quantify actual risk of future diabetes.
Objectives
To evaluate to what extent delirium experts agree on the diagnosis of delirium when independently assessing exactly the same information and to evaluate the sensitivity of delirium ...screening tools in routine daily practice of clinical nurses.
Design
Prospective observational longitudinal study.
Setting
Three medical centers in the Netherlands.
Participants
Elderly postoperative adults (n = 167).
Measurements
A researcher examined participants daily (Postoperative Day 1–3) for delirium using a standardized cognitive assessment and interview including the Delirium Rating Scale Revised‐98 as global impression without any cut‐off values that was recorded on video. Two delirium experts independently evaluated the videos and clinical information from the last 24 hours in the participants’ record and classified each assessment as delirious, possibly delirious, or not delirious. Interrater agreement between the delirium experts was determined using weighted Cohen's kappa. When there was no consensus, a third expert was consulted. Final classification was based on median score and compared with the results of the Confusion Assessment Method for Intensive Care Unit and Delirium Observation Scale that clinical nurses administered.
Results
Four hundred twenty‐four postoperative assessments of 167 participants were included. The overall kappa was 0.61 (95% confidence interval = 0.53–0.68). There was no agreement between the experts for 89 (21.0%) assessments and a third delirium expert was needed for the final classification. Delirium screening that nurses performed detected 32% of the assessments that the experts diagnosed as (possibly) delirious.
Conclusion
There was considerable disagreement in classification of delirium by experts who independently assessed exactly the same information, showing the difficulty of delirium diagnosis. Furthermore, the sensitivity of daily delirium screening by clinical nurses was poor. Future research should focus on development of objective instruments to diagnose delirium.
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