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Abdullah Al-Shimemeri

Publications and source records attributed to Abdullah Al-Shimemeri.

7 recordsLinked to original sources
PubMed2006

Effect of corticosteroids on adult varicella pneumonia: cohort study and literature review.

BACKGROUND: Varicella pneumonia (VP) is a serious entity associated with morbidity and mortality. There have been sporadic reports using corticosteroids in life-threatening VP. We report a case series of VP to examine the outcome and the effect of corticosteroid use. METHODS: A retrospective chart review was conducted on all adult patients admitted to a tertiary care hospital with VP during a 14-year period. We documented oxygenation (SpO2, PaO2/FIO2) on admission and after 48 h, whether the patients were admitted to an intensive care unit (ICU), the use of mechanical ventilation, ICU and hospital length of stay (LOS) and patient outcome. We compared those patients who received corticosteroids with those who did not. RESULTS: We identified 19 patients with VP. Ten received corticosteroids, in addition to antiviral and supportive treatment. Patients who received corticosteroids were significantly more hypoxaemic on admission and all were admitted to ICU with seven of them intubated. Only two of the nine in non-steroid group were intubated. Despite their greater severity, the corticosteroid group showed a much more rapid improvement in oxygenation and a trend towards shorter duration of mechanical ventilation. The duration of ICU and hospital LOS were not significantly different. All patients survived. CONCLUSIONS: Corticosteroids in severe VP accelerate the physiological recovery and may shorten the duration of mechanical ventilation.

Adrenal Cortex Hormones↗
PubMed2004

Outcome predictors of cirrhosis patients admitted to the intensive care unit.

OBJECTIVE: To evaluate outcome predictors of patients with cirrhosis admitted to an intensive care unit (ICU). METHODS: One hundred and twenty-nine consecutive patients with cirrhosis admitted to the ICU at a tertiary care transplant centre in Saudi Arabia between March 1999 and December 2000 were entered prospectively in an ICU database. Liver transplantation patients and readmissions to the ICU were excluded. The following data were documented: demographic features, severity of illness measures, parameters of organ failure, presence of gastrointestinal bleeding, and sepsis. The need for mechanical ventilation, renal replacement therapy and pulmonary artery catheter placement was recorded. The primary endpoint was hospital outcome. RESULTS: Cirrhotic patients admitted to the ICU had high hospital mortality (73.6%). However, the actual mortality was not significantly different from the predicted mortality using prediction systems. There was an association between the number of organs failing and mortality. Coma and acute renal failure emerged as independent predictors of mortality. All patients who were monitored with pulmonary artery catheterisation in this study died. Patients requiring mechanical ventilation and renal replacement therapy had very high mortalities (84% and 89%, respectively). All 13 cirrhotic patients admitted to ICU immediately post-cardiac arrest in this study died. CONCLUSIONS: Cirrhotic patients admitted to ICU have a poor prognosis, especially when admitted with coma, acute renal failure or post-cardiac arrest. The consistently poor prognosis associated with certain ICU interventions should raise new awareness regarding limitations of medical therapy. These mortality statistics compel a critical re-examination of uniformly aggressive life support for the critically ill cirrhotic patient, a percentage of whom will not benefit from invasive measures.

Catheterization, Swan-Ganz↗
PubMed2003

Assessment of six mortality prediction models in patients admitted with severe sepsis and septic shock to the intensive care unit: a prospective cohort study.

INTRODUCTION: We conducted the present study to assess the validity of mortality prediction systems in patients admitted to the intensive care unit (ICU) with severe sepsis and septic shock. We included Acute Physiology and Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, Mortality Probability Model (MPM) II0 and MPM II24 in our evaluation. In addition, SAPS II and MPM II24 were customized for septic patients in a previous study, and the customized versions were included in this evaluation. MATERIALS AND METHOD: This cohort, prospective, observational study was conducted in a tertiary care medical/surgical ICU. Consecutive patients meeting the diagnostic criteria for severe sepsis and septic shock during the first 24 hours of ICU admission between March 1999 and August 2001 were included. The data necessary for mortality prediction were collected prospectively as part of the ongoing ICU database. Predicted and actual mortality rates, and standardized mortality ratio were calculated. Calibration was assessed using Lemeshow-Hosmer goodness of fit C-statistic. Discrimination was assessed using receiver operating characteristic curves. RESULTS: The overall mortality prediction was adequate for all six systems because none of the standardized mortality ratios differed significantly from 1. Calibration was inadequate for APACHE II, SAPS II, MPM II0 and MPM II24. However, the customized version of SAPS II exhibited significantly improved calibration (C-statistic for SAPS II 23.6 [P = 0.003] and for customized SAPS II 11.5 [P = 0.18]). Discrimination was best for customized MPM II24 (area under the receiver operating characteristic curve 0.826), followed by MPM II24 and customized SAPS II. CONCLUSION: Although general ICU mortality system models had accurate overall mortality prediction, they had poor calibration. Customization of SAPS II and, to a lesser extent, MPM II24 improved calibration. The customized model may be a useful tool when evaluating outcomes in patients with sepsis.

APACHE↗
PubMed2003

Improving resource utilization in the intensive care units. A challenge for Saudi Hospitals.

In the face of increasing demand of intensive care services in the Kingdom of Saudi Arabia, as well as the high cost of delivering such services, systematic steps must be undertaken in order to ensure optional utilization and fair allocation of resources. Strategies start prior to intensive care units (ICU) admission by the proper selection of patients who are likely to benefit from ICU. Less resource-demanding alternatives, such as intermediate care units, should be used for low-risk patients. Do-not-resuscitate status in patients with no meaningful chance of recovery will prevent futile admissions to ICUs. Measures known to improve the efficiency of care in the ICU must be implemented, including hiring full-time qualified intensivists, switching open units to closed ones and the introduction of certain evidence-base driven management protocols. On discharge, the intermediate care units again play a role as less expensive alternative transitional area for patients who are not stable enough to go to general ward. Measures to reduce re-admissions to ICU must also be implemented. Improving ICU resource utilization requires teamwork not only the intensivists but also the administrators and other health care providers.

Health Services Needs and Demand↗
PubMed2002

Assessment of performance of four mortality prediction systems in a Saudi Arabian intensive care unit.

INTRODUCTION: The purpose of this study is to assess the performance of Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, Mortality Probability Model MPM II0 and MPM II24 systems in a major tertiary care hospital in Riyadh, Saudi Arabia. METHODS: The following data were collected prospectively on all consecutive patients admitted to the Intensive Care Unit between 1 March 1999 and 31 December 2000: demographics, APACHE II and SAPS II scores, MPM variables, ICU and hospital outcome. Predicted mortality was calculated using original regression formulas. Standardized mortality ratio (SMR) was computed with 95% confidence intervals (CI). Calibration was assessed by calculating Lemeshow-Hosmer goodness-of-fit C statistics. Discrimination was evaluated by calculating the Area Under the Receiver Operating Characteristic Curves (ROC AUC). RESULTS: Predicted mortality by all systems was not significantly different from actual mortality [SMR for MPM II0: 1.00 (0.91-1.10), APACHE II: 1.00 (0.8-1.11), SAPS II: 1.09 (0.97-1.21), MPM II24 0.92 (0.82-1.03)]. Calibration was best for MPM II24 (C-statistic: 14.71, P = 0.06). Discrimination was best for MPM II0 (ROC AUC:0.85) followed by MPM II24 (0.84), APACHE II (0.83) then SAPS II (0.79). CONCLUSIONS: In our ICU population: 1) Overall mortality prediction, estimated by standardized mortality ratio, was accurate, especially for MPM II0 and APACHE II. 2) MPM II24 has the best calibration. 3) SAPS II has the lowest calibration and discrimination. The local performance of MPM II24 in addition to its ease-to-use makes it an attractive model for mortality prediction in Saudi Arabia.

APACHE↗
PubMed2002

Can we predict prognosis using mortality probability model IIo?

OBJECTIVE: To evaluate Mortality Probability Model (MPM) IIo as a tool to predict very poor prognosis after intensive care unit admission. METHODS: The study was conducted as a prospective observational study in a medical-surgical intensive care unit in a tertiary care teaching hospital, Riyadh, Kingdom of Saudi Arabia. Data necessary to calculate MPM IIo predicted mortality was collected from March 1999 through to February 2000 on all intensive care unit admissions. The hospital outcome was documented. We calculated the sensitivity, specificity, positive predictive value and negative predictive value of MPM IIo using cutoff points of 90% and 95%. RESULTS: Data was complete on 557/569 patients (98%). Thirty-one patients had predicted mortality of >95% and all died yielding a specificity of 100% and positive predictive value of 100%. However, sensitivity was only 18% and negative predictive value 73%. Forty-four patients had predicted mortality of >90% of whom only one survived yielding a specificity of 99.7% and a positive predictive value of 97.7%. Sensitivity was only 25% and negative predictive value of 75%. CONCLUSIONS: Using a decision-cutoff of 95% predicted mortality using MPMI IIo had a very high specificity in predicting death after intensive care unit admission, although with a low sensitivity. This information can be used to support clinical judgment regarding the very ill patients who are unlikely to benefit from intensive care unit admission.

Adult↗