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S A Ridley

Publications and source records attributed to S A Ridley.

At least 19 recordsLinked to original sources
PubMed2005

Modelling the impact of an influenza pandemic on critical care services in England.

The UK Influenza Pandemic Contingency Plan does not consider the impact of a pandemic on critical care services. We modelled the demand for critical care beds in England with software developed by the Centers for Disease Control (Flusurge 1.0), using a range of attack rates and pandemic durations. Using inputs that have been employed in UK Department of Health scenarios (25% attack rate and 8-week pandemic duration) resulted in a demand for ventilatory support that exceeded 200% of present capacity. Demand remained unsustainably high even when more favourable scenarios were considered. Current critical care bed capacity in England would be unable to cope with the increased demand provided by an influenza pandemic. Appropriate contingency planning is essential.

Bed Occupancy↗
PubMed2004

Prescription errors in UK critical care units.

Drug prescription errors are a common cause of adverse incidents and may be largely preventable. The incidence of prescription errors in UK critical care units is unknown. The aim of this study was to collect data about prescription errors and so calculate the incidence and variation of errors nationally. Twenty-four critical care units took part in the study for a 4-week period. The total numbers of new and re-written prescriptions were recorded daily. Errors were classified according to the nature of the error. Over the 4-week period, 21,589 new prescriptions (or 15.3 new prescriptions per patient) were written. Eighty-five per cent (18,448 prescriptions) were error free, but 3141 (15%) prescriptions had one or more errors (2.2 erroneous prescriptions per patient, or 145.5 erroneous prescriptions per 1000 new prescriptions). The five most common incorrect prescriptions were for potassium chloride (10.2% errors), heparin (5.3%), magnesium sulphate (5.2%), paracetamol (3.2%) and propofol (3.1%). Most of the errors were minor or would have had no adverse effects but 618 (19.6%) errors were considered significant, serious or potentially life threatening. Four categories (not writing the order according to the British National Formulary recommendations, an ambiguous medication order, non-standard nomenclature and writing illegibly) accounted for 47.9% of all errors. Although prescription rates (and error rates) in critical care appear higher than elsewhere in hospital, the number of potentially serious errors is similar to other areas of high-risk practice.

Critical Care↗
PubMed2003

Mathematical modelling and simulation for planning critical care capacity.

Using average number of patients expected in a year, average length of stay and a target occupancy level to calculate the number of critical care beds needed is mathematically incorrect because of nonlinearity and variability in the factors that control length of stay. For a target occupancy in excess of 80%, this simple calculation will typically underestimate the number of beds required. More seriously, it provides no quantitative guidance information about other aspects of critical care demand such as the numbers of emergency patients transferred, deferral rates for elective patients and overall utilisation. The combination of appropriately analysing raw data and detailed mathematical modelling provides a much better method for estimating numbers of beds required. We describe this modelling approach together with evidence of its performance.

Bed Occupancy↗
PubMed2003

Long-term survival following intensive care: subgroup analysis and comparison with the general population.

This study aimed to compare the very long-term survival of critically ill patients with that of the general population, and examine the association among age, sex, admission diagnosis, APACHE II score and mortality. In a retrospective observational cohort study of prospectively gathered data, 2104 adult patients admitted to the intensive care unit (ICU) of a teaching hospital in Glasgow from 1985 to 1992, were followed until 1997. Vital status at five years was compared with that of an age- and sex-matched Scottish population. Five-year mortality for the ICU patients was 47.1%, 3.4 times higher than that of the general population. For those surviving intensive care the five-year mortality was 33.4%. Mortality was greater than that of the general population for four years following intensive care unit admission (95% confidence interval included 1.0 at four years). Multivariate analysis showed that risk factors for mortality in those admitted to ICU were age, APACHE II score on admission and diagnostic category. Mortality was higher for those admitted with haematological (87.5%) and neurological diseases (61.7%) and septic shock (62.9%). A risk score was produced: Risk Score = 10 (age hazard ratio + APACHE II hazard ratio + diagnosis hazard ratio). None of the patients with a risk score > 100 survived more than five years and for those who survived to five years the mean risk score was 57. Long-term survival following intensive care is not only related to age and severity of illness but also diagnostic category. The risk of mortality in survivors of critical illness matches that of the normal population after four years. Age, severity of illness and diagnosis can be combined to provide an estimate of five-year survival.

APACHE↗
PubMed2002

Uncertainty and scoring systems.

Estimating risks for individual patients facilitates communication with patients, relatives and colleagues, and determines whether further treatment is futile. The process of estimating risks involves mathematics (i.e. scoring systems) and human experience and expertise. Understanding how risks are estimated is important because prognostication is an integral part of any medical specialty. In the USA, such treatment limitation or withdrawal decisions were made on only 7% of all intensive care unit patients but this represented 47% of all deaths on such units. In the UK, data reported by the Intensive Care National Audit and Research Centre suggest that although treatment limitation decisions are made on only 11.8% of patients, this accounts for over 50% of deaths on intensive care. Scoring systems offer a useful adjunct in identifying futility but there are important inherent weaknesses that limit their performance. This review aims to discuss some of these limitations.

Critical Illness↗
PubMed2001

Variations in expenditure between adult general intensive care units in the UK.

This paper presents the findings from the second pilot study of the cost block method in 21 adult general intensive care units (ICUs). The aim of this study was to explore the possible reasons for the variation in cost identified in a previous pilot study of 11 ICUs. Data were collected for the six cost blocks for the financial year 1996/97. Multivariate analysis showed that 93% of the variation in expenditure on disposable equipment could be explained by the number of ICU beds, the number of admissions and the presence of a high-dependency unit (HDU). Ninety-two per cent of the variation in nursing staff expenditure was explained by the number of ICU beds and the presence of an HDU. Hospital type and the number of patient days explained 76% of the variation in expenditure on consultant staff. Sixty-four per cent of the variation in drug and fluid expenditure was explained by the number of patient days.

Adult↗
PubMed2001

Intermediate outcome of medical patients after intensive care.

Medical patients suffer a high mortality after critical illness; however, the causes of mortality after intensive care management are unclear. This study's aims were to (a) explore what factors affect outcome after intensive care and (b) identify medical patients at particularly high risk of mortality. During one year, all patients admitted with a medical cause to the Critical Care Complex were enrolled. Diagnosis on admission was recorded, and whether the reason for admission was a new clinical problem or an exacerbation of existing chronic illness. All patients were followed for a minimum of one year. A total of 186 medical patients were included in the study. Fifty-four medical patients died on intensive care (28.4% mortality), a further 16 died on the general ward after intensive care unit discharge (hospital mortality 36.8%) and six following discharge home (1 year's mortality 40.9%). Of the 16 patients who died on the general ward, 12 had been admitted to the intensive care unit with a new, previously unrecognised problem rather than exacerbation of a chronic pre-existing problem. However, on the general ward, 'Do Not Resuscitate' orders were placed on seven of these 12 patients. It would appear that some of the high post intensive care hospital mortality might be due to changes in resuscitation status in patients expected to survive following intensive care unit discharge.

APACHE↗
PubMed2000

Validation of outcome prediction in elderly patients.

We recently described an equation for predicting the 1-year survival of critically ill patients aged over 70 years. The aim of this study was to check the performance of this equation in a validation group of 555 patients. The required demographic details (age, diagnosis, acute physiology score) of all elderly patients admitted between 1/4/95 and 31/9/96 were recorded and patients were followed for 1 year. One hundred and six patients died on the intensive care unit (19% mortality) and a further 134 died within 1 year (43% total 1-year mortality). The performance of the predictive equation was modest; the goodness-of-fit p-value was 0.04 and the area under the receiver operating characteristic curve was 0.75. For both groups, the combined 1-year survival of all critically ill elderly patients was 55% but the outcome of patients aged over 85 years remains poor (37%).

Aged↗
PubMed1999

A comparison of hospital and critical-care activity.

When compared with changes in hospital activity, corresponding fluctuations in critical-care activity are not clear. Therefore, trends in hospital activity were compared with those of the critical-care services and simple patient demographic details. The results suggest that while the size of hospitals remained static, hospital admissions and outpatient attendances increased by 5% each year. During the same period, the number of critical-care beds increased by 21.4%. Despite this increase in capacity, the activity of the critical-care services continued to increase by a similar 5% per annum, indicating a huge surge in critical-care workload. The results indicate that the increase in the rate of activity in hospitals and critical-care services is similar but the workload of the critical-care services is increasing much faster. This suggests that the demand for critical care may be generated from within hospitals.

Age Factors↗
PubMed1999

Prevention of tracheal aspiration using the pressure-limited tracheal tube cuff.

A new design of tracheal tube cuff, the pressure-limited cuff, used with a constant-pressure inflation system, was compared with a high-volume low-pressure cuffed tracheal tube for leakage of dye placed in the subglottic space into the trachea. Patients requiring ventilation on the intensive care unit were randomly allocated into two groups, one for each type of cuff, and blue food dye was instilled daily via a fine catheter above the cuff into the subglottic space. There were eight patients in the high-volume low-pressure group and seven in the pressure-limited cuff group. Dye leaked into the trachea in seven (87%) of the high-volume low-pressure group compared with none (0%) of the pressure-limited cuff group (p < 0.01). This study demonstrates that the pressure-limited cuffed tracheal tube, in combination with a constant-pressure inflation device, prevents leakage of fluid into the lungs that occurs with high-volume low-pressure cuffs in the critically ill, intubated patient.

Air Pressure↗
PubMed1999

Prognostic indicators following emergency aortic aneurysm repair.

We performed a retrospective study of 135 patients presenting for emergency abdominal aneurysm repair to determine predictive factors for outcome. The outcome measures investigated were mortality in the operating theatre and intensive care, and at 28 and 100 days. Univariate analysis showed that the patient's age, hypotension on admission, aneurysmal rupture, pre-operative cardiopulmonary resuscitation, intra-operative blood loss and hypotension were risk factors for death either in the operating theatre or up to 100 days after surgery. Binary logistic regression identified the independent risk factors for survival. Operative survival was determined by acute factors such as pre-operative cardiopulmonary resuscitation, aneurysmal rupture and intra-operative hypotension. Longer term survival was determined by the patient's age, aneurysmal rupture, blood loss and blood pressure at admission. Using a binary logistic regression equation, from which a simplified risk score was derived, it is possible to predict the likelihood of survival of individual patients presenting for abdominal aortic aneurysm repair.

Aged↗
PubMed1999

Ventilator-associated pneumonia. Diagnosis, pathogenesis and prevention.

Ventilator-associated pneumonia is common, difficult to diagnose, affects the most vulnerable of patients and carries a high mortality. During prolonged mechanical ventilation the oropharynx, sinuses, dentition and stomach of critically ill patients become colonised with pathogenic bacteria. Colonised secretions pool in the oropharynx and subglottic space. These secretions repeatedly gain access to the lower airways by leakage past the tracheal tube cuff. If host defence mechanisms are overwhelmed, multiplication occurs in the lower respiratory tract producing an inflammatory response in the bronchioles and alveoli. The inflammatory response is characterised by capillary congestion, leucocyte and macrophage infiltration and fibrinous exudation into the alveolar spaces. If this inflammatory response occurs more than 48 h after intubation, it is called ventilator-associated pneumonia. Prevention depends on reducing upper airway and gastrointestinal reservoirs of bacteria, reducing or abolishing aspiration of these bacteria past the tracheal tube cuff and enhancing bacterial clearance from the lower airways.

Anti-Bacterial Agents↗
PubMed1998

Intermediate care, possibilities, requirements and solutions.

The inadequate supply of intensive care facilities has focused interest on intermediate care as a means of bridging the gulf between the level of support available in the intensive care unit and the general ward. However, few hospitals have developed intermediate care, in the form of high-dependency care units, and little information exists concerning the use or potential of such areas. Therefore, this review proposes to cover the definition of intermediate care and to discuss some of the possible reasons why intermediate care is now believed necessary. The capabilities of intermediate care for selected groups of patients and the treatment modalities offered are described. The present provision of high-dependency care in the United Kingdom is discussed and the methods for estimating the required size of a high-dependency unit are outlined. The impact of a high-dependency unit on the workload of the intensive care unit and the potential cost saving of managing such patients in an intermediate care area are illustrated.

Critical Care↗
PubMed1998

Evaluation of a new design of tracheal tube cuff to prevent leakage of fluid to the lungs.

A new design of tracheal tube cuff was compared with two types of high-volume, low-pressure (HVLP) cuffed tracheal tube for leakage of fluid from the subglottic space into the trachea. Spontaneous and positive-pressure ventilation were simulated using a mechanical lung, an intubated model trachea and a ventilator. Excised human tracheas were intubated and leakage past the cuff assessed. Distention of the tracheal wall was measured. HVLP cuffs leaked rapidly in the model during all modes of ventilation, and also in the excised human tracheas. This leakage occurred preferentially down longitudinal folds that occur in the HVLP cuff wall. The new design completely prevented leakage in the model during all modes of ventilation, during tracheal suctioning, and with tube movement. The new cuff also prevented leakage in the excised human tracheas. Tracheal wall distention and tracheal wall pressures were similar for all cuffs tested.

Equipment Design↗