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Biomedical subjects

D R Goldhill

Publications and source records attributed to D R Goldhill.

At least 19 recordsLinked to original sources
PubMed2006

Silent myocardial ischaemia and haemoglobin concentration: a randomized controlled trial of transfusion strategy in lower limb arthroplasty.

BACKGROUND AND OBJECTIVES: Red cell transfusion is commonly used in orthopaedic surgery. Evidence suggests that a restrictive transfusion strategy may be safe for most patients. However, concern has been raised over the risks of anaemia in those with ischaemic cardiac disease. Perioperative silent myocardial ischaemia (SMI) has a relatively high incidence in the elderly population undergoing elective surgery. This study used Holter monitoring to compare the effect of a restrictive and a liberal red cell transfusion strategy on the incidence of SMI in patients without signs or symptoms of ischaemic heart disease who were undergoing lower limb arthroplasty. MATERIALS AND METHODS: We performed a multicentre, controlled trial in which 260 patients undergoing elective hip and knee replacement surgery were enrolled and randomized to transfusion triggers that were either restrictive (8 g/dl) or liberal (10 g/dl). Participants were monitored with continuous ambulatory electrocardiogram (ECG) (Holter monitoring), preoperatively for 12 h and postoperatively for 72 h. The tapes were analysed for new ischaemia by technicians blinded to treatment. The total ischaemia time in minutes was divided by the recording time in hours and an ischaemic load in min/h was calculated. Haemoglobin levels were measured preoperatively, postoperatively in the recovery room, and on days one, three and five after surgery. RESULTS: The mean postoperative haemoglobin concentration was 9.87 g/dl in the restrictive group and 11.09 g/dl in the liberal group. In the restrictive group, 34% were transfused a total of 89 red cell units, and in the liberal group 43% were given a total of 119 red cell units. A postoperative episode of silent ischaemia was experienced by 21/109 (19%) patients in the restrictive group and by 26/109 (24%) patients in the liberal group [mean difference -4.6%; 95% confidence interval (CI): -15.5% to 6%, P = 0.41). There was no significant difference (P = 0.53) between the overall ischaemic load in the restrictive group (median 0 min/h, range 0-4.18) and the liberal group (median 0 min/h, range 0-19.48). In those patients who did experience postoperative SMI, the mean ischaemic load was 0.48 min/h in the restrictive group and 1.51 min/h in the liberal group (ratio 0.32, 95% CI: 0.14-0.76, P = 0.011). The median postoperative length of hospital stay in the restrictive group was 7.3 days [range 5-11; interquartile range (IQR) 6-8] compared with 7.5 days (range 5-13; IQR 7-8) in the liberal group. The numbers were not large enough to conclude equivalence. CONCLUSIONS: In patients without preoperative evidence of myocardial ischaemia undergoing elective hip and knee replacement surgery, a restrictive transfusion strategy seems unlikely to be associated with an increased incidence of SMI. A proportion of these patients experience moderate SMI, regardless of the transfusion trigger. Use of a restrictive transfusion strategy did not increase length of hospital stay, and use of this strategy would lead to a significant reduction in red cell transfusion in orthopaedic surgery. Our data did not indicate any potential for harm in employing such a strategy in patients with no prior evidence of cardiac ischaemia who were undergoing elective orthopaedic surgery.

Aged↗
PubMed2005

Quantification of mortality risk after abdominal aortic aneurysm repair.

BACKGROUND: The study was designed to evaluate the Acute Physiology And Chronic Health Evaluation (APACHE) II risk scoring system in abdominal aortic aneurysm (AAA) surgery. The aim was to create an APACHE-based risk stratification model for postoperative death. METHODS: Prospective postoperative APACHE II data were collected from patients undergoing AAA repair over a 9-year interval from 24 intensive care units (ICUs) in the Thames region. A multilevel logistic regression model (APACHE-AAA) for in-hospital mortality was developed to adjust for both case mix and the variation in outcome between ICUs. RESULTS: A total of 1896 patients were studied. The in-hospital mortality rate among the 1289 patients who had elective AAA repair was 9.6 (95 per cent confidence interval (c.i.) 8.0 to 11.2) per cent and that among the 605 patients who had an emergency repair was 46.9 (95 per cent c.i. 43.0 to 50.9) per cent. Four independent predictors of death were identified: age (odds ratio (OR) 1.05 (95 per cent c.i. 1.03 to 1.07) per year increase), Acute Physiology Score (OR 1.14 (95 per cent c.i. 1.12 to 1.17) per unit increase), emergency operation (OR 4.86 (95 per cent c.i. 3.64 to 6.52)) and chronic health dysfunction (OR 1.43 (95 per cent c.i. 1.04 to 1.97)). The APACHE-AAA model was internally valid, as shown by calibration (Hosmer-Lemeshow C statistic: chi(2) = 6.14, 8 d.f., P = 0.632), discrimination properties (area under receiver-operator characteristic curve 0.845) and subgroup analysis. There was no significant variation in outcome between hospitals. CONCLUSION: APACHE-AAA was shown to be an accurate risk-stratification model that could be used to quantify the risk of death after AAA surgery. It might also be used to determine the relative impact of ICU over high-dependency unit care.

APACHE↗
PubMed2005

A physiologically-based early warning score for ward patients: the association between score and outcome.

We analysed the physiological values and early warning score obtained from 1047 ward patients assessed by an intensive care outreach service. Patients were either referred directly from the wards (n = 245, 23.4%) or were routine critical care follow-ups. Decisions were made to admit 135 patients (12.9%) to a critical care area and limit treatment in another 78 (7.4%). An increasing number of physiological abnormalities was associated with higher hospital mortality (p < 0.0001) ranging from 4.0% with no abnormalities to 51.9% with five or more. An increasing early warning score was associated with more intervention (p < 0.0001) and higher hospital mortality (p < 0.0001). For patients with scores above one (n = 660), decisions to admit to a critical care area or limit treatment were taken in 200 (30.3%). Scores of all physiological variables except temperature contributed to the need for intervention and all variables except temperature and heart rate were associated with hospital mortality.

Adult↗
PubMed2004

Physiological abnormalities in early warning scores are related to mortality in adult inpatients.

BACKGROUND: Early warning scores using physiological measurements may help identify ward patients who are, or who may become, critically ill. We studied the value of abnormal physiology scores to identify high-risk hospital patients. METHODS: On a single day we recorded the following data from 433 adult non-obstetric inpatients: respiratory rate, heart rate, systolic pressure, temperature, oxygen saturation, level of consciousness, urine output for catheterized patients, age and inspired oxygen. We also noted the care required and given. RESULTS: Twenty-six patients (6%) died within 30 days. They were significantly older than survivors (P<0.001). Their median hospital stay was 26 days (interquartile range 16-39). Mortality increased with the number of physiological abnormalities (P<0.001), being 0.7% with no abnormalities, 4.4% with one, 9.2% with two and 21.3% with three or more. Patients receiving a lower level of care than desirable also had an increased mortality (P<0.01). Logistic regression modelling identified level of consciousness, heart rate, age, systolic pressure and respiratory rate as important variables in predicting outcome. CONCLUSIONS: Simple physiological observations identify high-risk hospital inpatients. Those who die are often inpatients for days or weeks before death, allowing time for clinicians to intervene and potentially change outcome. Access to critical care beds could decrease mortality.

Adult↗
PubMed2004

Simple bedside assessment of level of consciousness: comparison of two simple assessment scales with the Glasgow Coma scale.

Neurological assessment is an essential component of early warning scores used to identify seriously ill ward patients. We investigated how two simple scales (ACDU - Alert, Confused, Drowsy, Unresponsive; and AVPU - Alert, responds to Voice, responds to Pain, Unresponsive) compared to each other and also to the more complicated Glasgow Coma Scale (GCS). Neurosurgical nurses recorded patients' conscious level with each of the three scales. Over 7 months, 1020 analysable measurements were collected. Both simple scales identified distinct GCS ranges, although some overlap occurred (p < 0.001). Median GCS scores associated with AVPU were 15, 13, 8 and 6 and for ACDU were 15, 13, 10 and 6. The median values of ACDU were more evenly distributed than AVPU and may therefore be better at identifying early deteriorations in conscious level when they occur in critically ill ward patients.

Attitude of Health Personnel↗
PubMed2002

A survey of physicians' attitudes to transfusion practice in critically ill patients in the UK.

This study aimed to examine the attitudes of intensivists and haematologists to the use of blood and blood products using a scenario-based postal questionnaire. One hundred and sixty-two intensivists and 77 haematologists responded to the survey. In four scenarios, the baseline haemoglobin thresholds for red cell transfusion ranged from 6 to 12 g.dl(-1). There was significant variation between scenarios (p <0.005). Increasing age, high Acute Physiology and Chronic Health Status II score, surgery, acute respiratory distress syndrome, septic shock and lactic acidosis significantly (p <0.005) modified the transfusion threshold. There were greater variations in the baseline threshold for platelet transfusion. The majority of respondents (72.3%) selected a baseline haemoglobin threshold between 9 and 10 g.dl(-1). The thresholds for platelet transfusion were far less consistent.

Adult↗
PubMed2002

Blood component use in critically ill patients.

This prospective observational study was conducted to assess the current transfusion practice in critically ill patients. One thousand two hundred and forty-seven consecutive critically ill patients admitted between February 1999 and October 1999 were included in the study. Overall 666 (53%) patients were administered red cells. Transfused patients had significantly higher intensive care unit mortality but also had higher Acute Physiology and Chronic Health Evaluation II scores and longer durations of stay. The average pretransfusion haemoglobin concentration was < 9 g.dl(-1) in 75% of transfusion episodes. The common indications for transfusion were low haemoglobin (72%) and haemorrhage (25%). Overall, 202 (16%) and 281 (22%) of the patients were transfused platelets and fresh frozen plasma, respectively. The indications for transfusion were haemorrhage, low platelet counts, prolonged prothrombin time or to provide cover for invasive interventions. Most platelet transfusions were given at values in the order of 50-100 x 10(9).l(-1). The pretransfusion platelet count varied according to the indications for transfusion. This study showed that transfusion practice is consistent and that in general there does not seem to be an excessive use of blood components in critically ill patients.

APACHE↗
PubMed1999

Physiological values and procedures in the 24 h before ICU admission from the ward.

Physiological values and interventions in the 24 h before entry to intensive care were collected for admissions from hospital wards. In a 13-month period, there were 79 admissions in 76 patients who had been in hospital for at least 24 h and had not undergone surgery within 24 h of admission to intensive care. Thirty-four per cent of patients underwent cardiopulmonary resuscitation before intensive care admission. Using Acute Physiology and Chronic Health Evaluation II scoring to quantify abnormal physiology in the group as a whole, a significant deterioration in respiratory function before admission was found. During the 6-h period immediately before intensive care admission, 75% of patients received oxygen, 37% underwent arterial blood gas sampling, and oxygen saturation was measured in 61% of patients, 63% of whom had an oxygen saturation of less than 90%. Overall hospital mortality in the study group was 58%. Information collected on the wards identified seriously ill patients who may have benefited from earlier expert treatment.

APACHE↗
PubMed1999

The patient-at-risk team: identifying and managing seriously ill ward patients.

A 'patient-at-risk team', established to allow the early identification of seriously ill patients on hospital wards, made 69 assessments on 63 patients over 6 months. Predefined physiological criteria were not able to reliably predict which patients would be admitted to the intensive care unit. The incidence of cardiopulmonary resuscitation before intensive care admission was 3.6% for patients seen by the team and 30.4% for those not seen (p < 0.005). Of admissions seen by the team, 25% died on the intensive care unit compared with 45% of those not seen (not significant, p = 0.07). Among those not seen by the team, mortality was 40% for those who did not require resuscitation and 57% for those who did (not significant). Many critically ill ward patients had abnormal physiological values before intensive care unit admission. Identification of critically ill patients on the ward and early advice and active management are likely to prevent the need for cardiopulmonary resuscitation and to improve outcome.

APACHE↗
PubMed1998

APACHE II, data accuracy and outcome prediction.

From review of 122 intensive care charts, Acute Physiology and Chronic Health Evaluation (APACHE) II points were determined for eight physiological values. Using a strict interpretation of APACHE II criteria, an average of 20.6% of these points were higher and 6.7% lower than the points entered originally into an intensive care database. The resulting 1.73 points mean increase in APACHE II score increased predicted mortality from 24.8% to 27.8% and decreased the mortality ratio (observed hospital deaths devided by predicted deaths) from 1.52 (95% confidence interval: 1.11-2.03) to 1.35 (95% confidence interval: 0.99-1.81). There were few errors entering the data recorded on the audit form into the intensive care unit database with an optical mark reader and keyboard. Inaccuracy and inconsistency in data collection must be excluded before differences in mortality ratios are ascribed to intensive care unit performance.

APACHE↗
PubMed1998

Outcome of intensive care patients in a group of British intensive care units.

OBJECTIVE: To identify priorities for intensive care unit (ICU) intervention and research. DESIGN: Analysis of a large intensive care database. SETTING: Twenty-four ICUs in the North Thames region of the United Kingdom. PATIENTS: All patients admitted to an ICU between January 1, 1992, and April 31, 1996, on whom data had been entered into the database. Patients who were admitted after cardiac surgery, who had burns, or were <16 yrs of age were excluded from the study, as were data from patients with a previous ICU admission within 6 mos or where ICU or hospital outcome was unknown. Data were excluded from units that had entered <300 patients into the database. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 23,331 admissions with complete records were available. After exclusions, 12,762 admissions from 15 ICUs were selected for analysis. Hospital mortality was 32.5% with a mortality ratio of 1.14 (95% confidence interval 1.10 to 1.17). Nonsurvivors were older than survivors and had longer ICU stays. Patients admitted from wards had a higher mortality than patients from the operating room/recovery or the emergency department. Observed percentage mortality increased linearly with mortality predicted by Acute Physiology and Chronic Health Evaluation II, although the number of patients who died remained broadly constant across the range of predicted mortality. Twenty-seven percent of all deaths occurred after discharge from the ICU. Patients admitted after cardiopulmonary resuscitation constituted 30% of all deaths. Thirty-four percent of patients were in the ICU for >2 days, and they accounted for nearly 81% of bed days. CONCLUSIONS: Early identification of patients at risk, both before admission and after discharge from the ICU, may allow treatment to decrease mortality. Research and resources may be best directed at patients who die, despite a relatively low predicted mortality. Although these patients are a small percentage of the low-risk admissions, they constitute a large number of ICU deaths. Many patients die after discharge from ICU and this mortality may be decreased by minimizing inappropriate early discharge to the ward, by the provision of high-dependency and step-down units, and by continuing advice and follow-up by the ICU team after the patient has been discharged. Intervention before ICU admission and support of patients after discharge from the ICU should be part of the effort to decrease mortality for ICU patients. Inadequate provision of resources for critically ill patients may result in excess intensive care mortality that is not detected with ICU outcome prediction methods.

APACHE↗