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ObjectiveTo provide an overview and critical appraisal of early warning scores for adult hospital patients.DesignSystematic review.Data sourcesMedline, CINAHL, PsycInfo, and Embase until June 2019.Eligibility criteria for study selectionStudies describing the development or external validation of an early warning score for adult hospital inpatients.Results13 171 references were screened and 95 articles were included in the review. 11 studies were development only, 23 were development and external validation, and 61 were external validation only. Most early warning scores were developed for use in the United States (n=13/34, 38%) and the United Kingdom (n=10/34, 29%). Death was the most frequent prediction outcome for development studies (n=10/23, 44%) and validation studies (n=66/84, 79%), with different time horizons (the most frequent was 24 hours). The most common predictors were respiratory rate (n=30/34, 88%), heart rate (n=28/34, 83%), oxygen saturation, temperature, and systolic blood pressure (all n=24/34, 71%). Age (n=13/34, 38%) and sex (n=3/34, 9%) were less frequently included. Key details of the analysis populations were often not reported in development studies (n=12/29, 41%) or validation studies (n=33/84, 39%). Small sample sizes and insufficient numbers of event patients were common in model development and external validation studies. Missing data were often discarded, with just one study using multiple imputation. Only nine of the early warning scores that were developed were presented in sufficient detail to allow individualised risk prediction. Internal validation was carried out in 19 studies, but recommended approaches such as bootstrapping or cross validation were rarely used (n=4/19, 22%). Model performance was frequently assessed using discrimination (development n=18/22, 82%; validation n=69/84, 82%), while calibration was seldom assessed (validation n=13/84, 15%). All included studies were rated at high risk of bias.ConclusionsEarly warning scores are widely used prediction models that are often mandated in daily clinical practice to identify early clinical deterioration in hospital patients. However, many early warning scores in clinical use were found to have methodological weaknesses. Early warning scores might not perform as well as expected and therefore they could have a detrimental effect on patient care. Future work should focus on following recommended approaches for developing and evaluating early warning scores, and investigating the impact and safety of using these scores in clinical practice.Systematic review registrationPROSPERO CRD42017053324.
ObjectiveTo provide an overview and critical appraisal of early warning scores for adult hospital patients.DesignSystematic review.Data sourcesMedline, CINAHL, PsycInfo, and Embase until June 2019.Eligibility criteria for study selectionStudies describing the development or external validation of an early warning score for adult hospital inpatients.Results13 171 references were screened and 95 articles were included in the review. 11 studies were development only, 23 were development and external validation, and 61 were external validation only. Most early warning scores were developed for use in the United States (n=13/34, 38%) and the United Kingdom (n=10/34, 29%). Death was the most frequent prediction outcome for development studies (n=10/23, 44%) and validation studies (n=66/84, 79%), with different time horizons (the most frequent was 24 hours). The most common predictors were respiratory rate (n=30/34, 88%), heart rate (n=28/34, 83%), oxygen saturation, temperature, and systolic blood pressure (all n=24/34, 71%). Age (n=13/34, 38%) and sex (n=3/34, 9%) were less frequently included. Key details of the analysis populations were often not reported in development studies (n=12/29, 41%) or validation studies (n=33/84, 39%). Small sample sizes and insufficient numbers of event patients were common in model development and external validation studies. Missing data were often discarded, with just one study using multiple imputation. Only nine of the early warning scores that were developed were presented in sufficient detail to allow individualised risk prediction. Internal validation was carried out in 19 studies, but recommended approaches such as bootstrapping or cross validation were rarely used (n=4/19, 22%). Model performance was frequently assessed using discrimination (development n=18/22, 82%; validation n=69/84, 82%), while calibration was seldom assessed (validation n=13/84, 15%). All included studies were rated at high risk of bias.ConclusionsEarly warning scores are widely used prediction models that are often mandated in daily clinical practice to identify early clinical deterioration in hospital patients. However, many early warning scores in clinical use were found to have methodological weaknesses. Early warning scores might not perform as well as expected and therefore they could have a detrimental effect on patient care. Future work should focus on following recommended approaches for developing and evaluating early warning scores, and investigating the impact and safety of using these scores in clinical practice.Systematic review registrationPROSPERO CRD42017053324.
Background : About 20% of cases of acute pancreatitis progress to a severe form, leading to high mortality rates. Several studies suggested methods to identify patients that will progress more severely. However, most studies present problems when used on daily practice. Objective : To assess the efficacy of the PANC 3 score to predict acute pancreatitis severity and its relation to clinical outcome. Methods : Acute pancreatitis patients were assessed as to sex, age, body mass index (BMI), etiology of pancreatitis, intensive care need, length of stay, length of stay in intensive care unit and mortality. The PANC 3 score was determined within the first 24 hours after diagnosis and compared to acute pancreatitis grade of the Revised Atlanta classification. Results : Out of 64 patients diagnosed with acute pancreatitis, 58 met the inclusion criteria. The PANC 3 score was positive in five cases (8.6%), pancreatitis progressed to a severe form in 10 cases (17.2%) and five patients (8.6%) died. Patients with a positive score and severe pancreatitis required intensive care more often, and stayed for a longer period in intensive care units. The PANC 3 score showed sensitivity of 50%, specificity of 100%, accuracy of 91.4%, positive predictive value of 100% and negative predictive value of 90.6% in prediction of severe acute pancreatitis. Conclusion : The PANC 3 score is useful to assess acute pancreatitis because it is easy and quick to use, has high specificity, high accuracy and high predictive value in prediction of severe acute pancreatitis.
Background: The modified early warning score (MEWS) was set up to supply prompt recognition of clinically deteriorating patients before they undergo a severe and life-threatening event. The study aimed to describe the probable usefulness of the MEWS in identifying deteriorating post-Whipple patients in hospital wards. Methods:We performed a study to analyze the relationship between the vital parameters and postoperative severe adverse events of patients after Whipple surgery in Guangdong Provincial People's Hospital from 2000 to 2017. In the retrospective study, a total of 13,651 sets of vital parameters in 236 Whipple postoperative patients were included. Subsequently, we applied a MEWS scoring system and explored the accuracy of the MEWS in evaluating the patients' final events versus advanced mathematical models. We then put the MEWS into the ward warning system and confirmed the accuracy of the MEWS based on the results of prospective studies again. Results:We assessed the ability of the MEWS to predict postoperative complications with an accuracy rate of 90.86-91.23%, a sensitivity of 83.04-90.88%, and a specificity of 90.85-95.73%. Conclusions:The MEWS model was applied to identify post-Whipple patients at risk of complication.Once the MEWS ≥2, interventions were needed to minimize the adverse events. Our data suggest that the MEWS is comparable to the advanced mathematical models, but MEWS is more accessible to perform and more generally applicable.
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