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OBJECTIVES: To validate the Atema and APSI scoring systems in the diagnosis of complicated vs uncomplicated appendicitis. To compare these scoring systems with computed tomography (CT) imaging alone to establish which method provides most accurate prediction of complicated vs uncomplicated appendicitis. METHODS: This was a retrospective review of a sample of 160 patients that underwent appendicectomy and CT imaging for suspected appendicitis between 2018 and 2021 in a tertiary university teaching hospital. Each scoring system was applied to all patients and results analysed and compared with the effectiveness of CT imaging, RESULTS: 32.5% (n = 52) were found to have complicated appendicitis and 67.5% (n = 108) uncomplicated appendicitis. Application of the Atema score to our cohort of patients resulted in a sensitivity 76.9% [CI (64.2, 87.5), specificity 58.7% [CI (48.9, 68.1)], PPV 47.1% [CI (40.5, 53.8) and NPV 84.2% [CI (76.0, 89.9)]. By comparison, the APSI yielded a sensitivity 50.9% [CI (36.6, 65.4)], specificity 76.1% [CI (67.0, 87.8)], PPV 50% [CI (39.2, 60.6)] and NPV 76% [CI (71.1, 81.7)]. Radiology prediction of complicated vs uncomplicated appendicitis with CT imaging showed sensitivity 46% [CI (32.2, 60.5)], specificity 79%; [CI (69.8, 86)], PPV 51% [CI (39.6, 62.5)] and NPV 75% [CI (69.8, 79.9)]. CONCLUSION: By comparing the APSI and Atema et al. scoring systems with CT reporting in our hospital, it appears that the Atema may confer some benefit in stratifying patient risk of complicated versus uncomplicated appendicitis. Further larger scale prospective studies are required.
Assuntos
Apendicectomia , Apendicite , Tomografia Computadorizada por Raios X , Apendicite/diagnóstico por imagem , Apendicite/cirurgia , Humanos , Estudos Retrospectivos , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Apendicectomia/estatística & dados numéricos , Sensibilidade e Especificidade , Adulto Jovem , Valor Preditivo dos TestesRESUMO
OBJECTIVES: Studies evaluating telemedicine critical care (TCC) have shown mixed results. We prospectively evaluated the impact of TCC implementation on risk-adjusted mortality among patients stratified by pre-TCC performance. DESIGN: Prospective, observational, before and after study. SETTING: Three adult ICUs at an academic medical center. PATIENTS: A total of 2,429 patients in the pre-TCC (January to June 2016) and 12,479 patients in the post-TCC (January 2017 to June 2019) periods. INTERVENTIONS: TCC implementation which included an acuity-driven workflow targeting an identified "lower-performing" patient group, defined by ICU admission in an Acute Physiology and Chronic Health Evaluation diagnoses category with a pre-TCC standardized mortality ratio (SMR) of greater than 1.5. MEASUREMENTS AND MAIN RESULTS: The primary outcome was risk-adjusted hospital mortality. Risk-adjusted hospital length of stay (HLOS) was also studied. The SMR for the overall ICU population was 0.83 pre-TCC and 0.75 post-TCC, with risk-adjusted mortalities of 10.7% and 9.5% (p = 0.09). In the identified lower-performing patient group, which accounted for 12.6% (n = 307) of pre-TCC and 13.3% (n = 1671) of post-TCC ICU patients, SMR decreased from 1.61 (95% CI, 1.21-2.01) pre-TCC to 1.03 (95% CI, 0.91-1.15) post-TCC, and risk-adjusted mortality decreased from 26.4% to 16.9% (p < 0.001). In the remaining ("higher-performing") patient group, there was no change in pre- versus post-TCC SMR (0.70 [0.59-0.81] vs 0.69 [0.64-0.73]) or risk-adjusted mortality (8.5% vs 8.4%, p = 0.86). There were no pre- to post-TCC differences in standardized HLOS ratio or risk-adjusted HLOS in the overall cohort or either performance group. CONCLUSIONS: In well-staffed and overall higher-performing ICUs in an academic medical center, Acute Physiology and Chronic Health Evaluation granularity allowed identification of a historically lower-performing patient group that experienced a striking TCC-associated reduction in SMR and risk-adjusted mortality. This study provides additional evidence for the relationship between pre-TCC performance and post-TCC improvement.
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AIMS: The CREST tool was recently developed to stratify the risk of circulatory-aetiology death (CED) in out-of-hospital cardiac arrest (OHCA) patients without ST-elevation myocardial infarction (STEMI). We aimed to validate the CREST score using an external cohort and determine whether it could be improved by the addition of serum lactate on admission. METHODS: The study involved the retrospective analysis of consecutive patients admitted to a single tertiary centre with OHCA of presumed cardiac origin over a 51-month period. The CREST score was calculated by attributing points to the following variables: Coronary artery disease (CAD), non-shockable Rhythm, Ejection fraction <30%, cardiogenic Shock at presentation and ischaemic Time ≥25 minutes. The primary endpoint was CED vs neurological aetiology death (NED) or survival. RESULTS: Of 500 patients admitted with OHCA, 211 did not meet criteria for STEMI and were included. 115 patients died in hospital (71 NED, 44 CED). When analysed individually, CED was associated with all CREST variables other than a previous diagnosis of CAD. The CREST score accurately predicted CED with excellent discrimination (C-statistic 0.880, 95% CI 0.813-0.946) and calibration (Hosmer and Lemeshow P=0.948). Although an admission lactate ≥7 mmol/L also predicted CED, its addition to the CREST score (the C-AREST score) did not significantly improve the predictive ability (CS 0.885, 0.815-0.954, HS P=0.942, X2 difference in -2 log likelihood =0.326, P=0.850). CONCLUSION: Our study is the first to independently validate the CREST score for predicting CED in patients presenting with OHCA without STEMI. Addition of lactate on admission did not improve its predictive ability.
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OBJECTIVE: To compare the prognostic validity of the APACHE II-M and O-SOFA scales versus the APACHE II and SOFA to predict mortality in patients with severe maternal morbidity. DESIGN: A retrospective, longitudinal and analytical cohort study was carried out. SETTING: Medical-surgical intensive care unit (ICU) of a tertiary hospital. PATIENTS: Pregnant or puerperal patients of any age admitted to the ICU. INTERVENTIONS: Calculation of prognostic scores upon admission. VARIABLES OF INTEREST: APACHE II, SOFA, APACHE II-M and O-SOFA scores and maternal mortality. RESULTS: A total of 141 patients were included. The majority (70.2%) were puerperal. The most frequent diagnosis was gestational hypertensive disease (50 cases). The discrimination of each prognostic model was estimated with the area under the ROC curve (AUC-ROC). The calibration was estimated using the mortality ratio and the Hosmer-Lemeshow statistic. The four scales discriminated between survivors and non-survivors with areas under the curve >0.85. The APACHE II-M model was the predictive model with the highest discrimination and calibration. In the Hosmer-Lemeshow regression analysis, mortality as predicted by the APACHE II and O-SOFA was significantly different from the observed mortality. CONCLUSIONS: The APACHE II-M exhibited the greatest prognostic validity in predicting maternal mortality. This difference was given by its improvement in calibration.
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Acute Physiology and Chronic Health Evaluation is a well-validated method to risk-adjust ICU patient outcomes. However, predictions may be affected by inter-rater reliability for manually entered elements. We evaluated inter-rater reliability for Acute Physiology and Chronic Health Evaluation IV manually entered elements among clinician abstractors and assessed the impacts of disagreements on mortality predictions. DESIGN: Cross-sectional. SETTING: Academic medical center. SUBJECTS: Patients admitted to five adult ICUs. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Acute Physiology and Chronic Health Evaluation IV manually entered elements were abstracted from a selection of charts (n = 41) by two clinician "raters" trained in Acute Physiology and Chronic Health Evaluation IV methodology. Rater agreement (%) was determined for each manually entered element, including Acute Physiology and Chronic Health Evaluation diagnosis, Glasgow Coma Scale score, admission source, chronic conditions, elective/emergency surgery, and ventilator use. Cohen's kappa (K) or intraclass correlation coefficient was calculated for nominal and continuous manually entered elements, respectively. The impacts of manually entered element choices on Acute Physiology and Chronic Health Evaluation IV mortality predictions were computed using published Acute Physiology and Chronic Health Evaluation IV equations, and observed to expected hospital mortality ratios were compared between rater groups. The majority of manually entered element inconsistency was due to disagreement in choice of Glasgow Coma Scale (63.8% agreement, 0.83 intraclass correlation coefficient), Acute Physiology and Chronic Health Evaluation diagnosis (68.3% agreement, 0.67 kappa), and admission source (90.2% agreement, 0.85 kappa). The difference in predicted mortality between raters related to Glasgow Coma Scale disagreements was significant (observed to expected mortality ratios for Rater 1 [1.009] vs Rater 2 [1.134]; p < 0.05). Differences related to Acute Physiology and Chronic Health Evaluation diagnosis or admission source disagreements were negligible. The new "unable to score" choice for Glasgow Coma Scale was used for 18% of Glasgow Coma Scale measurements but accounted for 63% of "major" Glasgow Coma Scale disagreements, and 50% of the overall difference in Acute Physiology and Chronic Health Evaluation-predicted mortality between raters. CONCLUSIONS: Inconsistent use among raters of the new "unable to score" choice for Glasgow Coma Scale introduced in Acute Physiology and Chronic Health Evaluation IV was responsible for important decreases in both Glasgow Coma Scale and Acute Physiology and Chronic Health Evaluation IV mortality prediction reliability in our study. A Glasgow Coma Scale algorithm we developed after the study to improve reliability related to use of this new "unable to score" choice is presented.
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OBJECTIVE: An evaluation is made of the hospital mortality predicting capacity of the main predictive scoring systems. DESIGN: A 2-year retrospective cohort study was carried out. SETTING: A third level ICU with surgical and medical patients. PATIENTS: All patients with multiorgan failure during the first day in the ICU. MAIN VARIABLES: APACHE II and IV, SAPS II and III, MPM II and hospital mortality. RESULTS: A total of 568 patients were included. Mortality rate: 39.8% (226 patients). Discrimination (area under the ROC curve; 95% CI): APACHE IV (0.805; 0.751-0.858), SAPS II (0.755; 0.697-0.814), MPM II (0.748; 0.688-0.809), SAPS III (0.737; 0.675-0.799) and APACHE II (0.699; 0.633-0.765). MPM II showed the best calibration, followed by SAPS III. APACHE II, SAPS II and APACHE IV showed very poor calibration. Standard mortality ratio (95% CI): APACHE IV 1.9 (1.78-2.02); APACHE II 1.1 (1.07-1.13); SAPS III 1.1 (1.06-1.14); SAPS II 1.03 (1.01-1.05); MPM 0.9 (0.86-0.94). CONCLUSIONS: APACHE IV showed the best discrimination, with poor calibration. MPM II showed good discrimination and the best calibration. SAPS II, in turn, showed the second best discrimination, with poor calibration. The APACHE II calibration and discrimination values currently disadvise its use. SAPS III showed good calibration with modest discrimination. Future studies at regional or national level and in certain critically ill populations are needed.