Steven A. Frost

Development of prognostic nomograms for individualizing 5-year and 10-year fracture risks

SummaryWe have developed clinical nomograms for predicting 5-year and 10-year fracture risks for any elderly man or woman. The nomograms used age and information concerning fracture history, fall history, and BMD T-score or body weight.IntroductionAlthough many fracture risk factors have been identified, the translation of these risk factors into a prognostic model that can be used in primary care setting has not been well realized. The present study sought to develop a nomogram that incorporates non-invasive risk factors to predict 5-year and 10-year absolute fracture risks for an individual man and woman.MethodsThe Dubbo Osteoporosis Epidemiology Study was designed as a community-based prospective study, with 1358 women and 858 men aged 60+ years as at 1989. Baseline measurements included femoral neck bone mineral density (FNBMD), prior fracture, a history of falls and body weight. Between 1989 and 2004, 426 women and 149 men had sustained a low-trauma fracture (not including morphometric vertebral fractures). Two prognostic models based on the Cox’s proportional hazards analysis were considered: model I included age, BMD, prior fracture and falls; and model II included age, weight, prior fracture and fall.ResultsAnalysis of the area under the receiver operating characteristic curve (AUC) suggested that model I (AUC = 0.75 for both sexes) performed better than model II (AUC = 0.72 for women and 0.74 for men). Using the models’ estimates, we constructred various nomograms for individualizing the risk of fracture for men and women. If the 5-year risk of 10% or greater is considered “high risk”, then virtually all 80-year-old men with BMD T-scores <-1.0 or 80-year-old women with T-scores <-2.0 were predicted to be in the high risk group. A 60-year-old woman’s risk was considered high risk only if her BMD T-scores ≤-2.5 and with a prior fracture; however, no 60-year-old men would be in the high risk regardless of their BMD and risk profile.ConclusionThese data suggest that the assessment of fracture risk for an individual cannot be based on BMD alone, since there are clearly various combinations of factors that could substantially elevate an individual’s risk of fracture. The nomograms presented here can be useful for individualizing the short- and intermediate-term risk of fracture and identifying high-risk individuals for intervention to reduce the burden of fracture in the general population.

Risk factors for in-hospital post-hip fracture mortality

INTRODUCTION Approximately 10% of hip fracture patients die during hospitalization; however, it is not clear what risk factors contribute to the excess mortality. This study sought to examine risk factors of, and to develop prognostic model for, predicting in-hospital mortality among hip fracture patients. METHODS We studied outcomes among 410 men and 1094 women with a hip fracture who were admitted to a major-teaching-hospital in Sydney (Australia) between 1997 and 2007. Clinical data, including concomitant illnesses, were obtained from inpatient data. The primary outcome of the study was in-hospital mortality regardless of length of stay. A Log-binomial regression model was used to identify risk factors for in-hospital mortality. Using the identified risk factors, prognostic nomograms were developed for predicting short term risk of mortality for an individual. RESULTS The median duration of hospitalization was 9 days. During hospitalization, the risk of mortality was higher in men (9%) than in women (4%). After adjusting for multiple risk factors, increased risk of in-hospital mortality was associated with advancing age (rate ratio [RR] for each 10-year increase in age: 1.91 95% confidence interval [CI]: 1.47 to 2.49), in men (RR 2.13; 95% CI 1.41 to 3.22), and the presence of comorbid conditions on admission (RR for one or more comorbid conditions vs. none: 2.30; 95% CI 1.52 to 3.48). Specifically, the risk of mortality was increased in patients with a pre-existing congestive heart failure (RR 3.02; 95% CI: 1.65 to 5.54), and liver disease (RR 4.75; 95% CI: 1.87 to 12.1). These factors collectively accounted for 69% of the risk for in-hospital mortality. A nomogram was developed from these risk factors to individualize the risk of in-hospital death following a hip fracture. The area under the receiver operating characteristic curve of the final model containing age, sex and comorbid conditions was 0.76. CONCLUSION These data suggest that among hip fracture patients, advancing age, gender (men), and pre-existing concomitant diseases such as congestive heart failure and liver disease were the main risk factors for in-hospital mortality. The nomogram developed from this study can be used to convey useful prognostic information to help guide treatment decisions.

Severity of illness and risk of readmission to intensive care: A meta-analysis

BACKGROUND Almost one in every 10 patients who survive intensive care will be readmitted to the intensive care unit (ICU) during the same hospitalisation. The association between increasing severity of illness (widely calculated in ICU patients) with risk of readmission to ICU has not been systematically summarized. OBJECTIVE The meta-analysis was designed to combine information from published studies to assess the relationship between severity of illness in ICU patients and the risk of readmission to ICU during the same hospitalisation. DATA SOURCES Studies were identified by searching MEDLINE (1966 to August 2008), EMBASE (1980-2008), and CINAHL (1982 to August 2008). REVIEW METHODS Studies included only adult populations, readmissions to ICU during the same hospitalisation and reports of valid severity of illness index. RESULTS Eleven studies (totaling 220000 patients) were included in the meta-analysis. Severity of illness (APACHE II, APACHE III, SAPS and SAPS II) measured at the time of ICU admission or discharge, was higher in patients readmitted to the ICU during the same hospitalisation compared to patients not-readmitted (both p-values<0.001). The risk of readmission to ICU increased by 43% with each standard deviation increase in severity of illness score (regardless if measured on admission to, or discharge from the ICU) (odds ratio (OR)=1.43, 95% confidence interval (CI)=1.3-1.6). CONCLUSIONS A relationship between increasing intensive care severity of illness and risk of readmission to ICU was found. The effect was the same regardless of the time of measurement of severity of illness (at admission to ICU or the time of discharge from ICU). However, further research is required to develop more comprehensive tools to identify patients at risk of readmission to ICU to allow the targeted interventions, such as ICU-outreach to follow-up these patients to minimize adverse events.

Unplanned admission to intensive care after emergency hospitalisation: Risk factors and development of a nomogram for individualising risk

BACKGROUND AND AIMS Unplanned admission to an intensive care unit (ICU) is associated with high mortality, having the highest incidence among patients who are emergency admissions to the hospital. This study was designed to identify factors associated with unplanned ICU admission in emergency admissions to hospital and develop an absolute risk tool to individualise the risk of an event during a hospital stay. METHODS Emergency department (ED) and in-patient hospital data from a large teaching hospital of consecutive admissions from 1 January 1997 to 31 December 2007 aged over 14 years was included in this study. Patient data extracted from 126826 emergency presentations admitted as in-patients consisted of demographic and clinical variables. RESULTS During an 11-year period 1582 incident unplanned ICU admissions occurred. Predictors of unplanned ICU admission included older age, being male, having a higher acuity triage category and a history of co-morbid conditions. Emergency department diagnostic groups associated with higher incidence of unplanned ICU admission included: sepsis, acute renal failure, lymphatic-hematopoietic tissue neoplasms, pneumonia, chronic-airways disease and bowel obstruction. The final model used to develop the nomogram had an ROC curve AUC of 0.7. CONCLUSION This study identified factors associated with unplanned ICU admission and developed a nomogram to individualise risk prior to a patient being transferred from the ED. This nomogram provides clinicians the opportunity prior to transfer from the ED, to either (1) review the appropriateness of the ward level of planned transfer or (2) flag patients for follow-up on the general ward to assess for deterioration.

Excess mortality attributable to hip-fracture: A relative survival analysis

INTRODUCTION Individuals with hip fracture are at substantially increased risk of mortality. The aim of this study was to estimate the excess mortality attributable to hip fracture in elderly men and women. METHODS The Dubbo Osteoporosis Epidemiology Study was designed as a prospective epidemiologic investigation, in which more than 2000 men and women aged 60+ as of 1989 had been followed for 21 years. During the follow-up period, the incidence of atraumatic hip fractures was ascertained by X-ray reports, and mortality was ascertained by the New South Wales Birth, Death and Marriage Registry. Relative survival ratios were estimated by taking into account the age-and-sex specific expected survival in the general Australian population from 1989 to 2010. RESULTS During the follow-up period 151 women and 55 men sustained a hip fracture. Death occurred in 86 (57%) women and 36 (66%) men. In women, the cumulative relative survival post hip-fracture at 1, 5 and 10 years was 0.83 (95% confidence interval (CI) 0.76-0.89), 0.59 (95% CI 0.48-0.68), and 0.31 (95% CI 0.20-0.43), respectively; in men, the corresponding estimates of relative survival were: 0.63 (95% CI 0.48-0.75), 0.48 (95% CI 0.32-0.63), and 0.36 (95% CI 0.18-0.56). On average post hip-fracture women died 4 years earlier (median: 4.1, inter-quartile range (IQR) 1.7-7.8) and men died 5 years earlier (median = 4.8, IQR 2.4-7.0) than expected. For every six women and for every three men with hip fracture one extra death occurred above that expected in the background population. CONCLUSION Hip fracture is associated with reduced life expectancy, with men having a greater reduction than women, even after accounting for time-related changes in background mortality in the population. These data underscore that hip fracture is an independent clinical risk factor for mortality.

What are the factors in risk prediction models for rehospitalisation for adults with chronic heart failure

BACKGROUND Risk prediction models can assist in identifying individuals at risk of adverse events and also the judicious allocation of scare resources. Our objective was to describe risk prediction models for the rehospitalisation of individuals with chronic heart failure (CHF) and identify the elements contributing to these models. METHODS The electronic data bases MEDLINE, PsychINFO, Ovid Evidence-Based Medicine Reviews and Scopus (1950-2010), were searched for studies that describe models to predict all-cause hospital readmission for individuals with CHF. Search terms included: patient readmission; risk; chronic heart failure, congestive heart failure and heart failure. We excluded non-English studies, pediatric studies, and publications without original data. RESULTS Only 1 additional model was identified since the review undertaken by Ross and colleagues in 2008. All models were derived from data sets collected in the United States and patients were followed from 60 days to 18 months. The only common predictors of re-hospitalisation in the models identified by Ross and colleagues were a history of diabetes mellitus and a history of prior hospitalisation. The additional model extends its scope to include the non clinical factors of social instability and socioeconomic status as predictors of rehospitalisation. CONCLUSIONS In spite of the burden of hospitalisation in CHF, there are limited tools to assist clinicians in assessing risk. Developing risk prediction models, based on patient, provider and system characteristics may assist in identifying individuals in the community at greatest risk and in need of targeted interventions to improve outcomes.

Central venous catheter placement by advanced practice nurses demonstrates low procedural complication and infection rates : a report from 13 years of service

Objectives:To report procedural characteristics and outcomes from a central venous catheter placement service operated by advanced practice nurses. Design:Single-center observational study. Setting:A tertiary care university hospital in Sydney, Australia. Patients:Adult patients from the general wards and from critical care areas receiving a central venous catheter, peripherally inserted central catheter, high-flow dialysis catheter, or midline catheter for parenteral therapy between November 1996 and December 2009. Interventions:None. Measurements and Main Results:Prevalence rates by indication, site, and catheter type were assessed. Nonparametric tests were used to calculate differences in outcomes for categorical data. Catheter infection rates were determined per 1,000 catheter days after derivation of the denominator. A total of 4,560 catheters were placed in 3,447 patients. The most common catheters inserted were single-lumen peripherally inserted central catheters (n = 1,653; 36.3%) and single-lumen central venous catheters (n = 1,233; 27.0%). A small proportion of high-flow dialysis catheters were also inserted over the reporting period (n = 150; 3.5%). Sixty-one percent of all catheters placed were for antibiotic administration. The median device dwell time (in d) differed across cannulation sites (p < 0.001). Subclavian catheter placement had the longest dwell time with a median of 16 days (interquartile range, 8–26 d). Overall catheter dwell was reported at a cumulative 63,071 catheter days. The overall catheter-related bloodstream infection rate was 0.2 per 1,000 catheter days. The prevalence rate of pneumothorax recorded was 0.4%, and accidental arterial puncture (simple puncture—with no dilation or cannulation) was 1.3% using the subclavian vein. Conclusions:This report has demonstrated low complication rates for a hospital-wide service delivered by advance practice nurses. The results suggest that a centrally based service with specifically trained operators can be beneficial by potentially improving patient safety and promoting organizational efficiencies.

Timing of Repeat BMD Measurements: Development of an Absolute Risk-Based Prognostic Model†

This study attempted to address the following questions: for an individual who is at present nonosteoporotic, given their current age and BMD level, what is the individuals risk of fracture and when is the ideal time to repeat a BMD measurement? Nonosteoporotic women (n = 1008) and men (n = 750) over the age of 60 in 1989 from the Dubbo Osteoporosis Epidemiology Study were monitored until one of the following outcomes occurred: (1) BMD reached “osteoporosis” level (i.e., T‐scores ≤ −2.5) or (2) an incident fragility fracture. During the follow‐up period (average, 7 yr), 346 women (34%) and 160 men (21%) developed osteoporosis or sustained a low‐trauma fracture. The risk of osteoporosis or fracture increased with advancing age (women: RR/10 yr, 1.3; 95% CI, 1.1–1.6; men: RR/10 yr, 2.3; 95% CI, 1.7–2.9) and lower BMD levels (women: RR per −0.12 g/cm2, 3.2; 95% CI, 2.6–4.1; RR per −0.12 g/cm2, 2.6; 95% CI, 2.0–3.3). Using the predicted risk (of osteoporosis or fracture) of 10% as a cut‐off level for repeating BMD measurement, the estimated time to reach the cut‐off level varied from 1.5 (for an 80‐yr‐old woman with a T‐score of −2.2) to 10.6 yr (for a 60‐yr‐old man with a T‐score of 0). These results suggest that, based on an individuals current age and BMD T‐score, it is possible to estimate the optimal time to repeat BMD testing for the individual. The prognostic model and approach presented in this study may help improve the individualization and management of osteoporosis.

Long term trends in medical emergency team activations and outcomes

AIM OF STUDY . To analyze long-term medical emergency team (MET) operational trends including number of MET calls, trigger criteria for activation and clinical outcomes at a tertiary level, university hospital with a mature MET system. MATERIALS AND METHODS The characteristics of 19,030 MET calls between 2000 and 2012 were analyzed in a single-centre, retrospective observational study. Rates indexed per 1000 hospital admissions for MET calls, cardiac arrests, unplanned admissions to the intensive care unit (ICU) and hospital mortality were used as performance measures of the MET. Descriptive statistics (mean±standard deviation) were applied and trends analyzed by one-way ANOVA with year 2000 set as the baseline using Dunns correction for multiple comparisons, p<0.05. RESULTS Activations of the MET increased between 2000 and 2012 (19±3-30±4) and there were changes in reasons for activations over time. Clinical concern (worried) was the most common (22%) trigger criterion in 2000 followed by hypotension (21%) and decreased level of consciousness (17%). In 2012, hypotension was the most common trigger (32%), followed by decreased level of consciousness (19%) and clinical concern (15%). Rates of cardiorespiratory arrest (1.4±0.7-1.1±0.4) and unplanned ICU admission (5.0±1.2-5.9±1.0) did not change between 2000 and 2012. Hospital mortality decreased from 2005 onwards (15±3.4-12±2.2). CONCLUSIONS MET activity progressively increased during the study period and there was a change in pattern of specific triggering criteria. The sustained decrease in hospital mortality independent of cardiac arrest and unplanned ICU admissions rates suggests patient benefit from the MET system.

Subglottic secretion drainage for preventing ventilator associated pneumonia: A meta-analysis

BACKGROUND Ventilator associated pneumonia (VAP) in the intensive care unit (ICU) has been shown to be associated with significant morbidity and mortality.(1-3) It has been reported to affect between 9 and 27% of intubated patients receiving mechanical ventilation.(4-6) OBJECTIVE: A meta-analysis was undertaken to combine information from published studies of the effect of subglottic drainage of secretions on the incidence of ventilated associated pneumonia in adult ICU patients. DATA SOURCES Studies were identified by searching MEDLINE (1966 to January 2011), EMBASE (1980-2011), and CINAHL (1982 to January 2011). REVIEW METHODS Randomized trials of subglottic drainage of secretions compared to usual care in adult mechanically ventilated ICU patients were included in the meta-analysis. RESULTS Subglottic drainage of secretions was estimated to reduced the risk of VAP by 48% (fixed-effect relative risk (RR)=0.52, 95% confidence interval (CI), 0.42-0.65). When comparing subglottic drainage and control groups, the summary relative risk for ICU mortality was 1.05 (95% CI, 0.86-1.28) and for hospital mortality was 0.96 (95% CI, 0.81-1.12). Overall subglottic drainage effect on days of mechanical ventilation was -1.04 days (95% CI, -2.79-0.71). CONCLUSION This meta-analysis of published randomized control trials shows that almost one-half of cases of VAP may be prevented with the use of specialized endotracheal tubes designed to drain subglottic secretions. Time on mechanical ventilation may be reduced and time to development of VAP may be increased, but no reduction in ICU or hospital mortality has been observed in published trials.