Beds

IntroductionWhen the number of patients who require intensive care is greater than the number of beds available, intensive care unit (ICU) entry flow is obstructed. This phenomenon has been associated with higher mortality rates in patients that are not admitted despite their need, and in patients that are admitted but are waiting for a bed. The purpose of this study is to evaluate if a delay in ICU admission affects mortality for critically ill patients.MethodsA prospective cohort of adult patients admitted to the ICU of our institution between January and December 2005 were analyzed. Patients for whom a bed was available were immediately admitted; when no bed was available, patients waited for ICU admission. ICU admission was classified as either delayed or immediate. Confounding variables examined were: age, sex, originating hospital ward, ICU diagnosis, co-morbidity, Acute Physiology and Chronic Health Evaluation (APACHE) II score, therapeutic intervention, and Sequential Organ Failure Assessment (SOFA) score. All patients were followed until hospital discharge.ResultsA total of 401 patients were evaluated; 125 (31.2%) patients were immediately admitted and 276 (68.8%) patients had delayed admission. There was a significant increase in ICU mortality rates with a delay in ICU admission (P = 0.002). The fraction of mortality risk attributable to ICU delay was 30% (95% confidence interval (CI): 11.2% to 44.8%). Each hour of waiting was independently associated with a 1.5% increased risk of ICU death (hazard ratio (HR): 1.015; 95% CI 1.006 to 1.023; P = 0.001).ConclusionsThere is a significant association between time to admission and survival rates. Early admission to the ICU is more likely to produce positive outcomes.

ObjectiveThe risk of sudden infant death syndrome (SIDS) among infants who co-sleep in the absence of hazardous circumstances is unclear and needs to be quantified.DesignCombined individual-analysis of two population-based case-control studies of SIDS infants and controls comparable for age and time of last sleep.SettingParents of 400 SIDS infants and 1386 controls provided information from five English health regions between 1993-6 (population: 17.7 million) and one of these regions between 2003-6 (population:4.9 million).ResultsOver a third of SIDS infants (36%) were found co-sleeping with an adult at the time of death compared to 15% of control infants after the reference sleep (multivariate OR = 3.9 [95% CI: 2.7-5.6]). The multivariable risk associated with co-sleeping on a sofa (OR = 18.3 [95% CI: 7.1-47.4]) or next to a parent who drank more than two units of alcohol (OR = 18.3 [95% CI: 7.7-43.5]) was very high and significant for infants of all ages. The risk associated with co-sleeping next to someone who smoked was significant for infants under 3 months old (OR = 8.9 [95% CI: 5.3-15.1]) but not for older infants (OR = 1.4 [95% CI: 0.7-2.8]). The multivariable risk associated with bed-sharing in the absence of these hazards was not significant overall (OR = 1.1 [95% CI: 0.6-2.0]), for infants less than 3 months old (OR = 1.6 [95% CI: 0.96-2.7]), and was in the direction of protection for older infants (OR = 0.1 [95% CI: 0.01-0.5]). Dummy use was associated with a lower risk of SIDS only among co-sleepers and prone sleeping was a higher risk only among infants sleeping alone.ConclusionThese findings support a public health strategy that underlines specific hazardous co-sleeping environments parents should avoid. Sofa-sharing is not a safe alternative to bed-sharing and bed-sharing should be avoided if parents consume alcohol, smoke or take drugs or if the infant is pre-term.

BackgroundPressure ulcers are a prevalent and global issue and support surfaces are widely used for preventing ulceration. However, the diversity of available support surfaces and the lack of direct comparisons in RCTs make decision-making difficult.ObjectivesTo determine, using network meta-analysis, the relative effects of different support surfaces in reducing pressure ulcer incidence and comfort and to rank these support surfaces in order of their effectiveness.MethodsWe conducted a systematic review, using a literature search up to November 2016, to identify randomised trials comparing support surfaces for pressure ulcer prevention. Two reviewers independently performed study selection, risk of bias assessment and data extraction. We grouped the support surfaces according to their characteristics and formed evidence networks using these groups. We used network meta-analysis to estimate the relative effects and effectiveness ranking of the groups for the outcomes of pressure ulcer incidence and participant comfort. GRADE was used to assess the certainty of evidence.Main resultsWe included 65 studies in the review. The network for assessing pressure ulcer incidence comprised evidence of low or very low certainty for most network contrasts. There was moderate-certainty evidence that powered active air surfaces and powered hybrid air surfaces probably reduce pressure ulcer incidence compared with standard hospital surfaces (risk ratios (RR) 0.42, 95% confidence intervals (CI) 0.29 to 0.63; 0.22, 0.07 to 0.66, respectively). The network for comfort suggested that powered active air-surfaces are probably slightly less comfortable than standard hospital mattresses (RR 0.80, 95% CI 0.69 to 0.94; moderate-certainty evidence).ConclusionsThis is the first network meta-analysis of the effects of support surfaces for pressure ulcer prevention. Powered active air-surfaces probably reduce pressure ulcer incidence, but are probably less comfortable than standard hospital surfaces. Most prevention evidence was of low or very low certainty, and more research is required to reduce these uncertainties.

ObjectiveThis study aimed to explore the conditional dependency structure of contributing factors related to bed falls and to identify stable dependency configurations within reported bed falls incident reports using Bayesian network analysis.MethodsA retrospective analysis was conducted using 102 inpatient bed-fall incident reports collected from a tertiary hospital between 2014 and 2024. Twenty-two previously identified contributing factors were encoded as binary variables. Bayesian network structure learning was performed using a hill-climbing algorithm with the Bayesian Information Criterion, without imposing prior structural constraints. Structural stability was assessed through non-parametric bootstrap resampling. Conditional inference and posterior probability analyses were used to examine probability changes and co-occurrence patterns under specific clinical conditions.ResultsBootstrap analysis identified several structurally stable directed edges in the Bayesian network. Sudden changes in patient consciousness were repeatedly connected to medication-related hypotension and safety measure-related nodes, forming a central structural component of the network. A stable directed relationship was also observed between nighttime sedative use with toileting and unassisted bed exit. In addition, delayed patient assistance was more frequently linked to delayed responses by on-site caregivers than to complete caregiver absence. Together, these results indicate that reported bed falls are associated with a limited number of recurrent and structurally consistent contributing-factor configurations.ConclusionReported bed falls appear to arise from interactions among a small number of contributing factors under specific clinical contexts rather than from isolated causes. Bayesian network analysis offers a useful approach for identifying contributing-factor configurations and informing scenario-based fall prevention strategies in clinical nursing practice.