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1.
Ned Tijdschr Geneeskd ; 1642020 Apr 02.
Article in Dutch | MEDLINE | ID: mdl-32391997

ABSTRACT

Here we describe the characteristics of the first 100 laboratory confirmed COVID-19 patients admitted to the Elisabeth-Tweesteden Hospital (Tilburg, The Netherlands). The median age was 72 years, 67% was male, approximately 80% had co-morbidity, approximately 50% of which consisted of hypertension, cardiac and or pulmonary conditions and 25% diabetes. At admission 61% of patients had fever and about 50% presented at day 6 or more after onset of symptoms. At the time of writing 38 patients were discharged, 19 admitted to the intensive care unit (ICU) and 20 patients had died. The median age of ICU patients was 67 years and 63% had co-morbidity. The median time to discharge or to death was 6 and 5.5 days, respectively.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Hospital Mortality , Pneumonia, Viral/epidemiology , Aged , COVID-19 , Comorbidity , Coronavirus Infections/diagnosis , Critical Care , Female , Fever/diagnosis , Hospitalization/statistics & numerical data , Humans , Intensive Care Units , Male , Middle Aged , Netherlands/epidemiology , Pandemics , Patient Discharge/statistics & numerical data , Pneumonia, Viral/diagnosis , SARS-CoV-2
2.
Ned Tijdschr Geneeskd ; 155: A3257, 2011.
Article in Dutch | MEDLINE | ID: mdl-21586185

ABSTRACT

OBJECTIVE: Hospitalized patients are at risk for adverse events such as unexpected cardiac arrest or admission to an Intensive Care Unit (ICU). Prior to these adverse events these patients often have derangements in vital signs that are not recognized and treated adequately. To identify and treat those patients at risk, our hospital implemented a rapid response system in 2004. The purpose of this paper is to describe implementation and results of our rapid response system. DESIGN: Prospective cohort study. METHOD: The implementation of the rapid response system started by training all doctors and nurses to score vital signs using a dedicated score card. If a patient scores 3 or more points, the patients' treating physician has to see the patient and - if necessary - call the medical emergency team (MET), consisting of an ICU physician and an ICU nurse. We analyzed all consecutive MET calls in the period January 2005-December 2009. RESULTS: A total of 1058 MET calls for 981 patients were analyzed. In 606 patients (57.3%) it was decided to transfer the patient to a higher dependency unit, in most cases the ICU. In 353 patients (33.4%) treatment could be continued on the ward. In 88 patients (8.4%) it was decided that ICU treatment would not be beneficial and limits on treatment were put in place. Of the 981 patients, 255 (26.0%) died in hospital. CONCLUSION: In our hospital the rapid response system has developed into an important tool for the early identification and treatment of patients at risk. However, our data cannot prove the efficacy of the rapid response system in terms of reducing hospital mortality.


Subject(s)
Hospital Mortality , Hospital Rapid Response Team/statistics & numerical data , Hospitals, General/statistics & numerical data , Aged , Cohort Studies , Female , Hospital Rapid Response Team/standards , Humans , Male , Middle Aged , Netherlands , Prospective Studies
3.
Crit Care ; 13(3): R84, 2009.
Article in English | MEDLINE | ID: mdl-19500333

ABSTRACT

INTRODUCTION: Caring for the critically ill is a 24-hour-a-day responsibility, but not all resources and staff are available during off hours. We evaluated whether intensive care unit (ICU) admission during off hours affects hospital mortality. METHODS: This retrospective multicentre cohort study was carried out in three non-academic teaching hospitals in the Netherlands. All consecutive patients admitted to the three ICUs between 2004 and 2007 were included in the study, except for patients who did not fulfil APACHE II criteria (readmissions, burns, cardiac surgery, younger than 16 years, length of stay less than 8 hours). Data were collected prospectively in the ICU databases. Hospital mortality was the primary endpoint of the study. Off hours was defined as the interval between 10 pm and 8 am during weekdays and between 6 pm and 9 am during weekends. Intensivists, with no responsibilities outside the ICU, were present in the ICU during daytime and available for either consultation or assistance on site during off hours. Residents were available 24 hours a day 7 days a week in two and fellows in one of the ICUs. RESULTS: A total of 6725 patients were included in the study, 4553 (67.7%) admitted during daytime and 2172 (32.3%) admitted during off hours. Baseline characteristics of patients admitted during daytime were significantly different from those of patients admitted during off hours. Hospital mortality was 767 (16.8%) in patients admitted during daytime and 469 (21.6%) in patients admitted during off hours (P < 0.001, unadjusted odds ratio 1.36, 95%CI 1.20-1.55). Standardized mortality ratios were similar for patients admitted during off hours and patients admitted during daytime. In a logistic regression model APACHE II expected mortality, age and admission type were all significant confounders but off-hours admission was not significantly associated with a higher mortality (P = 0.121, adjusted odds ratio 1.125, 95%CI 0.969-1.306). CONCLUSIONS: The increased mortality after ICU admission during off hours is explained by a higher illness severity in patients admitted during off hours.


Subject(s)
After-Hours Care , Hospital Mortality , Intensive Care Units , Quality of Health Care , After-Hours Care/statistics & numerical data , Aged , Female , Hospitals, Teaching , Humans , Intensive Care Units/statistics & numerical data , Logistic Models , Male , Middle Aged , Netherlands/epidemiology , Personnel Staffing and Scheduling , Retrospective Studies
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