Risk Models and Scoring Systems for Predicting the Prognosis in Critically Ill Cirrhotic Patients with Acute Kidney Injury: A Prospective Validation Study

Background

Cirrhotic patients with acute kidney injury (AKI) admitted to intensive care units (ICUs) show extremely high mortality rates. We have proposed the MBRS scoring system, which can be used for assessing patients on the day of admission to the ICU; this new system involves determination of mean arterial pressure (MAP) and bilirubin level and assessment of respiratory failure and sepsis. We had used this scoring system to analyze the prognosis of ICU cirrhotic patients with AKI in 2008, and the current study was an external validation of this scoring system.

Methods

A total of 190 cirrhotic patients with AKI were admitted to the ICU between March 2008 and February 2011. We prospectively analyzed and recorded the data for 31 demographic parameters and some clinical characteristic variables on day 1 of admission to the ICU; these variables were considered as predictors of mortality.

Results

The overall in-hospital mortality rate was 73.2% (139/190), and the 6-month mortality rate was 83.2% (158/190). Hepatitis B viral infection (43%) was observed to be the cause of liver disease in most of the patients. Multiple logistic regression analysis indicated that the MBRS and Acute Physiology and Chronic Health Evaluation III (ACPACHE III) scores determined on the first day of admission to the ICU were independent predictors of in-hospital mortality in patients. In the analysis of the area under the receiver operating characteristic (AUROC) curves, the MBRS scores showed good discrimination (AUROC: 0.863±0.032, p<0.001) in predicting in-hospital mortality.

Conclusion

On the basis of the results of this external validation, we conclude that the MBRS scoring system is a reproducible, simple, easy-to-apply evaluation tool that can increase the prediction accuracy of short-term prognosis in critically ill cirrhotic patients with AKI.     

Adjusted Age-Adjusted Charlson Comorbidity Index Score as a Risk Measure of Perioperative Mortality before Cancer Surgery

BackgroundIdentification of patients at risk of death from cancer surgery should aid in preoperative preparation. The purpose of this study is to assess and adjust the age-adjusted Charlson comorbidity index (ACCI) to identify cancer patients with increased risk of perioperative mortality.MethodsWe identified 156,151 patients undergoing surgery for one of the ten common cancers between 2007 and 2011 in the Taiwan National Health Insurance Research Database. Half of the patients were randomly selected, and a multivariate logistic regression analysis was used to develop an adjusted-ACCI score for estimating the risk of 90-day mortality by variables from the original ACCI. The score was validated. The association between the score and perioperative mortality was analyzed.ResultsThe adjusted-ACCI score yield a better discrimination on mortality after cancer surgery than the original ACCI score, with c-statics of 0.75 versus 0.71. Over 80 years of age, 70–80 years, and renal disease had the strongest impact on mortality, hazard ratios 8.40, 3.63, and 3.09 (P < 0.001), respectively. The overall 90-day mortality rates in the entire cohort varied from 0.9%, 2.9%, 7.0%, and 13.2% in four risk groups stratifying by the adjusted-ACCI score; the adjusted hazard ratio for score 4–7, 8–11, and ≥ 12 was 2.84, 6.07, and 11.17 (P < 0.001), respectively, in 90-day mortality compared to score 0–3.ConclusionsThe adjusted-ACCI score helps to identify patients with a higher risk of 90-day mortality after cancer surgery. It might be particularly helpful for preoperative evaluation of patients over 80 years of age.     

A Clinical Predictor Score for 30-Day Mortality among HIV-Infected Adults Hospitalized with Pneumonia in Uganda

BackgroundPneumonia is a major cause of mortality among HIV-infected patients. Pneumonia severity scores are promising tools to assist clinicians in predicting patients’ 30-day mortality, but existing scores were developed in populations infected with neither HIV nor tuberculosis (TB) and include laboratory data that may not be available in resource-limited settings. The objective of this study was to develop a score to predict mortality in HIV-infected adults with pneumonia in TB-endemic, resource-limited settings.MethodsWe conducted a secondary analysis of data from a prospective study enrolling HIV-infected adults with cough ≥2 weeks and <6 months and clinically suspected pneumonia admitted to Mulago Hospital in Kampala, Uganda from September 2008 to March 2011. Patients provided two sputum specimens for mycobacteria, and those with Ziehl-Neelsen sputum smears that were negative for mycobacteria underwent bronchoscopy with inspection for Kaposi sarcoma and testing for mycobacteria and fungi, including Pneumocystis jirovecii. A multivariable best subsets regression model was developed, and one point was assigned to each variable in the model to develop a clinical predictor score for 30-day mortality.ResultsOverall, 835 patients were studied (mean age 34 years, 53.4% female, 30-day mortality 18.2%). A four-point clinical predictor score was identified and included heart rate >120 beats/minute, respiratory rate >30 breaths/minute, oxygen saturation <90%, and CD4 cell count <50 cells/mm³. Patients’ 30-day mortality, stratified by score, was: score 0 or 1, 12.6%, score 2 or 3, 23.4%, score 4, 53.9%. For each 1 point change in clinical predictor score, the odds of 30-day mortality increased by 65% (OR 1.65, 95% CI 1.39-1.96, p <0.001).ConclusionsA simple, four-point scoring system can stratify patients by levels of risk for mortality. Rapid identification of higher risk patients combined with provision of timely and appropriate treatment may improve clinical outcomes. This predictor score should be validated in other resource-limited settings.     

Establishment and Validation of GV-SAPS II Scoring System for Non-Diabetic Critically Ill Patients

MethodsTraining and validation cohorts were exacted from the Multiparameter Intelligent Monitoring in Intensive Care database III version 1.3 (MIMIC-III v1.3). The GV-SAPS II score was constructed by Cox proportional hazard regression analysis and compared with the original SAPS II, Sepsis-related Organ Failure Assessment Score (SOFA) and Elixhauser scoring systems using area under the curve of the receiver operator characteristic (auROC) curve.Results4,895 and 5,048 eligible individuals were included in the training and validation cohorts, respectively. The GV-SAPS II score was established with four independent risk factors, including hyperglycemia, hypoglycemia, standard deviation of blood glucose levels (Glu_SD), and SAPS II score. In the validation cohort, the auROC values of the new scoring system were 0.824 (95% CI: 0.813–0.834, P< 0.001) and 0.738 (95% CI: 0.725–0.750, P< 0.001), respectively for 30 days and 9 months, which were significantly higher than other models used in our study (all P < 0.001). Moreover, Kaplan-Meier plots demonstrated significantly worse outcomes in higher GV-SAPS II score groups both for 30-day and 9-month mortality endpoints (all P< 0.001).ConclusionsWe established and validated a modified prognostic scoring system that integrated glucose variability for non-diabetic critically ill patients, named GV-SAPS II. It demonstrated a superior prognostic capability and may be an optimal scoring system for prognostic evaluation in this patient group.     

Development and Validation of a Risk Score for Predicting Death after Pneumonectomy

Pneumonectomy is associated with significant postoperative mortality. This study was undertaken to develop and validate a risk model of mortality following pneumonectomy. We reviewed our prospective database and identified 774 pneumonectomies from a total of 7792 consecutive anatomical lung resections in the years 2003 to 2010 (rate of pneumonectomy: 9.9%). Based on data from 542 pneumonectomies between 2003 and 2007 (i.e., the "discovery set"), a penalized multivariable logistic regression analysis was performed to identify preoperative risk factors. A risk model was developed and validated in an independent data set of 232 pneumonectomies that were performed between 2008 and 2010 (i.e., the "validation set"). Of the 542 patients in the discovery set (DS), 35 patients (6.5%) died after pneumonectomy during the same admission. We developed a risk prediction model for in-hospital mortality following pneumonectomy; that model included age, current alcohol use, coronary artery disease, preoperative leukocyte count and palliative indication as possible risk factors. The risk model was subsequently successfully validated in an independent data set (n = 232) in which 18 patients (7.8%) died following pneumonectomy. For the validation set, the sensitivity of the model was 53.3% (DS: 54.3%), the specificity was 88.0% (DS: 87.4%), the positive predictive value was 26.7% (DS: 22.9%) and the negative predictive value was 95.8% (DS: 96.5%). The Brier score was 0.062 (DS: 0.054). The prediction model is statistically valid and clinically relevant.     

Rapid Diagnosis of Lung Tumors,a Feasability Study Using Maldi-Tof Mass Spectrometry

ObjectiveDespite recent advances in imaging and core or endoscopic biopsies, a percentage of patients have a major lung resection without diagnosis. We aimed to assess the feasibility of a rapid tissue preparation/analysis to discriminate cancerous from non-cancerous lung tissue.MethodsFresh sample preparations were analyzed with the Microflex LT^TM MALDI-TOF analyzer. Each main reference spectra (MSP) was consecutively included in a database. After definitive pathological diagnosis, each MSP was labeled as either cancerous or non-cancerous (normal, inflammatory, infectious nodules). A strategy was constructed based on the number of concordant responses of a mass spectrometry scoring algorithm. A 3-step evaluation included an internal and blind validation of a preliminary database (n = 182 reference spectra from the 100 first patients), followed by validation on a whole cohort database (n = 300 reference spectra from 159 patients). Diagnostic performance indicators were calculated.Results127 cancerous and 173 non-cancerous samples (144 peripheral biopsies and 29 inflammatory or infectious lesions) were processed within 30 minutes after biopsy sampling. At the most discriminatory level, the samples were correctly classified with a sensitivity, specificity and global accuracy of 92.1%, 97.1% and 95%, respectively.ConclusionsThe feasibility of rapid MALDI-TOF analysis, coupled with a very simple lung preparation procedure, appears promising and should be tested in several surgical settings where rapid on-site evaluation of abnormal tissue is required. In the operating room, it appears promising in case of tumors with an uncertain preoperative diagnosis and should be tested as a complementary approach to frozen-biopsy analysis.     

Design and Performance of a New Severity Score for Intermediate Care

Background

Application of illness-severity scores in Intermediate Care Units (ImCU) shows conflicting results. The aim of the study is to design a severity-of-illness score for patients admitted to an ImCU.

Methods

We performed a retrospective observational study in a single academic medical centre in Pamplona, Spain. Demographics, past medical history, reasons for admission, physiological parameters at admission and during the first 24 hours of ImCU stay, laboratory variables and survival to hospital discharge were recorded. Logistic regression analysis was performed to identify variables for mortality prediction.

Results

A total of 743 patients were included. The final multivariable model (derivation cohort = 554 patients) contained only 9 variables obtained at admission to the ImCU: previous length of stay 7 days (6 points), health-care related infection (11), metastatic cancer (9), immunosuppressive therapy (6), Glasgow comma scale 12 (10), need of non-invasive ventilation (14), platelets 50000/mcL (9), urea 0.6 g/L (10) and bilirubin 4 mg/dL (9). The ImCU severity score (ImCUSS) is generated by summing the individual point values, and the formula for determining the expected in-hospital mortality risk is: e^{ImCUSS points*0.099 – 4,111} / (1 + e^{ImCUSS points*0.099 – 4,11}1). The model showed adequate calibration and discrimination. Performance of ImCUSS (validation cohort = 189 patients) was comparable to that of SAPS II and 3. Hosmer-Lemeshow goodness-of-fit C test was χ² 8.078 (p=0.326) and the area under receiver operating curve 0.802.

Conclusions

ImCUSS, specially designed for intermediate care, is based on easy to obtain variables at admission to ImCU. Additionally, it shows a notable performance in terms of calibration and mortality discrimination.     

Angiographic Lesion Complexity Score and In-Hospital Outcomes after Percutaneous Coronary Intervention

Objective

We devised a percutaneous coronary intervention (PCI) scoring system based on angiographic lesion complexity and assessed its association with in-hospital complications.

Background

Although PCI is finding increasing application in patients with coronary artery disease, lesion complexity can lead to in-hospital complications.

Methods

Data from 3692 PCI patients were scored based on lesion complexity, defined by bifurcation, chronic total occlusion, type C, and left main lesion, along with acute thrombus in the presence of ST-segment elevation myocardial infarction (1 point assigned for each variable).

Results

The patients’ mean age was 67.5 +/- 10.8 years; 79.8% were male. About half of the patients (50.3%) presented with an acute coronary syndrome, and 2218 (60.1%) underwent PCI for at least one complex lesion. The patients in the higher-risk score groups were older (p < 0.001) and had present or previous heart failure (p = 0.02 and p = 0.01, respectively). Higher-risk score groups had significantly higher in-hospital event rates for death, heart failure, and cardiogenic shock (from 0 to 4 risk score; 1.7%, 4.5%, 6.3%, 7.1%, 40%, p < 0.001); bleeding with a hemoglobin decrease of >3.0 g/dL (3.1%, 11.0%, 13.1%, 10.3%, 28.6%, p < 0.001); and postoperative myocardial infarction (1.5%, 3.1%, 3.8%, 3.8%, 10%, p = 0.004), respectively. The association with adverse outcomes persisted after adjustment for known clinical predictors (odds ratio 1.72, p < 0.001).

Conclusion

The complexity score was cumulatively associated with in-hospital mortality and complication rate and could be used for event prediction in PCI patients.     

ISAR Score (Identification of Seniors At Risk) predice la mortalidad en mayores de 75 años ingresados en Cuidados Intensivos

Background and objectivesCurrently, the patient's baseline situation is a more important prognostic factor than age. The purpose of this study is to estimate the prognostic value of the ISAR score (Identification of Senior at Risk) in patients ≥75 years admitted to intensive care (ICU).Patients and methodsProspective multicenter study including patients ≥75 years admitted to the ICU > 24 hours. On admission, 28 days and 6 months after discharge from the ICU, mortality and baseline were evaluated using the ISAR score, the Lawton and Brody scale (LB) and the Barthel index (BI), the Frail fragility scale. scale (FS), the Charlson comorbidity index (ICC), Dementia rating score (DRC).Results38 of 94 patients (40%) were high risk (ISAR ≥ 3) and were characterized by BI 90 (65-100), LB 4 (3-5), and CDR 1 (0-2), ICC 7.5 (6-10). 58% had FS ≥ 3. In the long term, they were in a situation of dependency [BI 50 (2.5-77.5), LB 3 (0-4), CDR 1 (0-1.5)]. The ICU mortality at 28 days and 6 months was 18.4%, 25.7% and 35.3%, respectively, being statistically significant. The area under the ISAR score ROC curve was 0.749 to 0.797, in all the mortality periods studied, although the difference with other predictive variables was not significant, but the p value was the lowest.ConclusionsThe ISAR score predicts mortality in critically elderly patients with a discriminative capacity comparable to other predictive variables.     

Machine learning-based in-hospital mortality prediction of HIV/AIDS patients with Talaromyces marneffei infection in Guangxi,China

ObjectiveTalaromycosis is a serious regional disease endemic in Southeast Asia. In China, Talaromyces marneffei (T. marneffei) infections is mainly concentrated in the southern region, especially in Guangxi, and cause considerable in-hospital mortality in HIV-infected individuals. Currently, the factors that influence in-hospital death of HIV/AIDS patients with T. marneffei infection are not completely clear. Existing machine learning techniques can be used to develop a predictive model to identify relevant prognostic factors to predict death and appears to be essential to reducing in-hospital mortality.MethodsWe prospectively enrolled HIV/AIDS patients with talaromycosis in the Fourth People’s Hospital of Nanning, Guangxi, from January 2012 to June 2019. Clinical features were selected and used to train four different machine learning models (logistic regression, XGBoost, KNN, and SVM) to predict the treatment outcome of hospitalized patients, and 30% internal validation was used to evaluate the performance of models. Machine learning model performance was assessed according to a range of learning metrics, including area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) tool was used to explain the model.ResultsA total of 1927 HIV/AIDS patients with T. marneffei infection were included. The average in-hospital mortality rate was 13.3% (256/1927) from 2012 to 2019. The most common complications/coinfections were pneumonia (68.9%), followed by oral candida (47.5%), and tuberculosis (40.6%). Deceased patients showed higher CD4/CD8 ratios, aspartate aminotransferase (AST) levels, creatinine levels, urea levels, uric acid (UA) levels, lactate dehydrogenase (LDH) levels, total bilirubin levels, creatine kinase levels, white blood-cell counts (WBC) counts, neutrophil counts, procaicltonin levels and C-reactive protein (CRP) levels and lower CD3⁺ T-cell count, CD8⁺ T-cell count, and lymphocyte counts, platelet (PLT), high-density lipoprotein cholesterol (HDL), hemoglobin (Hb) levels than those of surviving patients. The predictive XGBoost model exhibited 0.71 sensitivity, 0.99 specificity, and 0.97 AUC in the training dataset, and our outcome prediction model provided robust discrimination in the testing dataset, showing an AUC of 0.90 with 0.69 sensitivity and 0.96 specificity. The other three models were ruled out due to poor performance. Septic shock and respiratory failure were the most important predictive features, followed by uric acid, urea, platelets, and the AST/ALT ratios.ConclusionThe XGBoost machine learning model is a good predictor in the hospitalization outcome of HIV/AIDS patients with T. marneffei infection. The model may have potential application in mortality prediction and high-risk factor identification in the talaromycosis population.     

Testing the Prognostic Accuracy of the Updated Pediatric Sepsis Biomarker Risk Model

Background

We previously derived and validated a risk model to estimate mortality probability in children with septic shock (PERSEVERE; PEdiatRic SEpsis biomarkEr Risk modEl). PERSEVERE uses five biomarkers and age to estimate mortality probability. After the initial derivation and validation of PERSEVERE, we combined the derivation and validation cohorts (n = 355) and updated PERSEVERE. An important step in the development of updated risk models is to test their accuracy using an independent test cohort.

Objective

To test the prognostic accuracy of the updated version PERSEVERE in an independent test cohort.

Methods

Study subjects were recruited from multiple pediatric intensive care units in the United States. Biomarkers were measured in 182 pediatric subjects with septic shock using serum samples obtained during the first 24 hours of presentation. The accuracy of PERSEVERE 28-day mortality risk estimate was tested using diagnostic test statistics, and the net reclassification improvement (NRI) was used to test whether PERSEVERE adds information to a physiology-based scoring system.

Results

Mortality in the test cohort was 13.2%. Using a risk cut-off of 2.5%, the sensitivity of PERSEVERE for mortality was 83% (95% CI 62–95), specificity was 75% (68–82), positive predictive value was 34% (22–47), and negative predictive value was 97% (91–99). The area under the receiver operating characteristic curve was 0.81 (0.70–0.92). The false positive subjects had a greater degree of organ failure burden and longer intensive care unit length of stay, compared to the true negative subjects. When adding PERSEVERE to a physiology-based scoring system, the net reclassification improvement was 0.91 (0.47–1.35; p<0.001).

Conclusions

The updated version of PERSEVERE estimates mortality probability reliably in a heterogeneous test cohort of children with septic shock and provides information over and above a physiology-based scoring system.     

A Prognostic Score for Patients with Intermediate-Stage Hepatocellular Carcinoma Treated with Transarterial Chemoembolization

Background

Intermediate-stage hepatocellular carcinoma (HCC), defined according to the Barcelona Clinic Liver Cancer (BCLC) staging system, is a heterogeneous condition with variable clinical benefits from transarterial chemoembolization (TACE). This study aimed to develop a simple validated prognostic score based on the predictive factors for survival in patients with intermediate-stage HCC treated with TACE.

Methods

Three-hundred and fifty patients with intermediate-stage HCC undergoing initial TACE at Chiba University Hospital (training cohort; n = 187) and two affiliated hospitals (validation cohort; n = 163) were included. Following variables were entered into univariate and multivariate Cox regression models to develop a points-based clinical scoring system: gender, age, etiology, pretreatment, Child–Pugh score, aspartate aminotransferase, creatinine, C-reactive protein, alfa-fetoprotein, size of the largest lesion, and number and location of lesions.

Results

The number of lesions and the Child–Pugh score were identified as independent prognostic factors in the training cohort. The development of a 0–7-point prognostic score, named the Chiba HCC in intermediate-stage prognostic (CHIP) score, was based on the sum of three subscale scores (Child–Pugh score = 0, 1, 2, or 3, respectively, number of lesions = 0, 2, or 3, respectively, HCV-RNA positivity = 0 or 1, respectively). The generated scores were then differentiated into five groups (0–2 points, 3 points, 4 points, 5 points, and 6–7 points) by the median survival time (65.2, 29.2, 24.3, 13.1, and 8.4 months, respectively; p < 0.0001). These results were confirmed in the external validation cohort (p < 0.0001).

Conclusions

The CHIP score is easy-to-use and may assist in finding an appropriate treatment strategy for intermediate-stage HCC.     

A Risk Score for Predicting Multiple Sclerosis

ObjectiveMultiple sclerosis (MS) develops as a result of environmental influences on the genetically susceptible. Siblings of people with MS have an increased risk of both MS and demonstrating asymptomatic changes in keeping with MS. We set out to develop an MS risk score integrating both genetic and environmental risk factors. We used this score to identify siblings at extremes of MS risk and attempted to validate the score using brain MRI.Methods78 probands with MS, 121 of their unaffected siblings and 103 healthy controls were studied. Personal history was taken, and serological and genetic analysis using the illumina immunochip was performed. Odds ratios for MS associated with each risk factor were derived from existing literature, and the log values of the odds ratios from each of the risk factors were combined in an additive model to provide an overall score. Scores were initially calculated using log odds ratio from the HLA-DRB1*1501 allele only, secondly using data from all MS-associated SNPs identified in the 2011 GWAS. Subjects with extreme risk scores underwent validation studies. MRI was performed on selected individuals.ResultsThere was a significant difference in the both risk scores between people with MS, their unaffected siblings and healthy controls (p<0.0005). Unaffected siblings had a risk score intermediate to people with MS and controls (p<0.0005). The best performing risk score generated an AUC of 0.82 (95%CI 0.75–0.88).InterpretationsThe risk score demonstrates an AUC on the threshold for clinical utility. Our score enables the identification of a high-risk sibling group to inform pre-symptomatic longitudinal studies.     

A simple mortality risk prediction score for viper envenoming in India (VENOMS): A model development and validation study

BackgroundSnakebite is a neglected problem with a high mortality in India. There are no simple clinical prognostic tools which can predict mortality in viper envenomings. We aimed to develop and validate a mortality-risk prediction score for patients of viper envenoming from Southern India.MethodsWe used clinical predictors from a prospective cohort of 248 patients with syndromic diagnosis of viper envenoming and had a positive 20-minute whole blood clotting test (WBCT 20) from a tertiary-care hospital in Puducherry, India. We applied multivariable logistic regression with backward elimination approach. External validation of this score was done among 140 patients from the same centre and its performance was assessed with concordance statistic and calibration plots.FindingsThe final model termed VENOMS from the term “Viper ENvenOming Mortality Score included 7 admission clinical parameters (recorded in the first 48 hours after bite): presence of overt bleeding manifestations, presence of capillary leak syndrome, haemoglobin <10 g/dL, bite to antivenom administration time > 6.5 h, systolic blood pressure < 100 mm Hg, urine output <20 mL/h in 24 h and female gender. The lowest possible VENOMS score of 0 predicted an in-hospital mortality risk of 0.06% while highest score of 12 predicted a mortality of 99.1%. The model had a concordance statistic of 0·86 (95% CI 0·79–0·94) in the validation cohort. Calibration plots indicated good agreement of predicted and observed outcomes.ConclusionsThe VENOMS score is a good predictor of the mortality in viper envenoming in southern India where Russell’s viper envenoming burden is high. The score may have potential applications in triaging patients and guiding management after further validation.     

不同年龄女性急性ST段抬高型心肌梗死患者冠状动脉病变特点、PPCI治疗临床疗效的差异及院内死亡的危险因素分析

摘要 目的：分析不同年龄女性急性ST段抬高型心肌梗死（STEMI）患者冠状动脉病变特点、经急诊经皮冠状动脉介入（PPCI）治疗后的临床疗效差异及院内死亡的危险因素。方法：选取2018年1月~2022年3月期间在我院接受PPCI治疗的女性STEMI患者408例,根据患者不同的发病年龄将其分为A组（年龄≤65岁,n=161）与B组（年龄>65岁,n=247）。对比不同的发病年龄PPCI冠状动脉病变特点、治疗后的临床疗效差异及院内不良事件发生情况。单因素和多因素Logistic回归分析女性STEMI患者院内死亡的危险因素。结果：A组、B组的病变血管数量、钙化病变组间对比有统计学差异（P<0.05）。A组、B组的病变血管部位、术前TIMI血流分级、分叉病变组间对比无统计学差异（P>0.05）。两组主动脉内囊反搏术比例组间对比未见明显差异（P>0.05）,B组症状发生到血管开通时间（S-to-D）、门-球囊扩张时间（D-to-B）时间长于A组（P<0.05）。两组术中死亡、支架内血栓、BARC3~5级出血比例组间对比无统计学差异（P>0.05）。B组术后死亡的发生率低于A组（P<0.05）。根据患者不同的预后结局分为存活组（n=369）和死亡组（n=39）。单因素分析结果显示女性STEMI患者院内死亡与年龄、糖尿病、体质量指数（BMI）、Killip心功能分级、术前TIMI血流分级、术后TIMI血流分级、住院天数、S-to-D时间、D-to-B时间、收缩压（SBP）、舒张压（DBP）、白细胞计数（WBC）、中性粒细胞、血小板体积分布宽度（PDW）、左心室射血分数（LVEF）、肌酸激酶同工酶（CK-MB）有关（P<0.05）。多因素Logistic回归分析,结果显示年龄偏大、LVEF偏低、CK-MB偏高、术后TIMI血流分级0~I级、S-to-D时间偏长是女性STEMI患者院内死亡的危险因素（P<0.05）。结论：不同年龄女性STEMI患者冠状动脉病变特点、且PPCI 的治疗效果存在一定的差异。此外,年龄偏大、LVEF偏低、CK-MB偏高、术后TIMI血流分级0~I级、S-to-D时间偏长是女性STEMI患者院内死亡的危险因素。     

Using a Diabetes Risk Score to Identify Patients Without Diabetes at Risk for New Hyperglycemia in the Hospital

ObjectiveTo assess the value of a validated diabetes risk test, the Cambridge Risk Score (CRS), to identify patients admitted to hospital without diabetes at risk for new hyperglycemia (NH).MethodsThis retrospective cross-sectional study included adults admitted to a hospital over a 4-year period. Patients with no diabetes diagnosis and not on antidiabetics were included. The CRS was calculated for each patient, and those with available glycated hemoglobin (HbA1C) results were investigated in a second analysis. Multivariate regression analyses were performed to assess the association among CRS, HbA1C, and the risk for NH.ResultsA total of 19,830 subjects comprised the sample, of which 38% were found to have developed NH, defined as a blood glucose level ≥140 mg/dL. After accounting for covariates, the CRS was significantly associated with NH (odds ratio [OR], 1.19 [1.16, 1.22]; P < .001). Only 17% of patients had their HbA1C values checked within 6 months of admission. Compared with patients without diabetes, patients with prediabetes based on their HbA1C level (OR, 1.59 [1.37, 1.86]; P < .001) and patients with undiagnosed diabetes (OR, 5.95 [3.50, 10.65]; P < .001) were also significantly more likely to have NH.ConclusionResults of this study show that the CRS and HbA1C levels were significantly associated with the risk of developing NH in inpatient adults without diabetes. Given that an HbA1C level was missing in most medical records of hospitalized patients without diabetes, the CRS could be a useful tool for early identification and management of NH, possibly leading to better outcomes.     

Trends in the Use of Guideline-Recommended Medications and In-Hospital Mortality of Patients with Acute Myocardial Infarction in a Chinese Population

ObjectiveCurrent practice guidelines recommend the routine use of several cardiac medications early in the course of acute myocardial infarction (AMI). Our objective was to analyze temporal trends in medication use and in-hospital mortality of AMI patients in a Chinese population.MethodsThis is a retrospective observational study using electronic medical records from the hospital information system (HIS) of 14 Chinese hospitals. We identified 5599 patients with AMI between 2005 and 2011. Factors associated with medication use and in-hospital mortality were explored by using hierarchical logistic regression.ResultsThe use of several guideline-recommended medications all increased during the study period: statins (57.7%–90.1%), clopidogrel (61.8%–92.3%), β-Blockers (45.4%–65.1%), ACEI/ARB (46.7%–58.7%), aspirin (81.9%–92.9%), and the combinations thereof increased from 24.9% to 42.8% (P<0.001 for all). Multivariate analyses showed statistically significant increases in all these medications. The in-hospital mortality decreased from 15.9% to 5.7% from 2005 to 2011 (P<0.001). After multivariate adjustment, admission year was still a significant factor (OR = 0.87, 95% CI 0.79–0.96, P = 0.007), the use of aspirin (OR = 0.64, 95% CI 0.46–0.87), clopidogrel (OR = 0.44, 95% CI 0.31–0.61), ACEI/ARB (OR = 0.73, 95% CI 0.56–0.94) and statins (OR = 0.54, 95% CI 0.40–0.73) were associated with a decrease in in-hospital mortality. Patients with older age, cancer and renal insufficiency had higher in-hospital mortality, while they were generally less likely to receive all these medications.ConclusionUse of guideline-recommended medications early in the course of AMI increased between 2005 and 2011 in a Chinese population. During this same time, there was a decrease in in-hospital mortality.     

Desarrollo y validación de un instrumento observacional para la evaluación del bienestar en personas con demencia desde la perspectiva de la atención centrada en la persona: Listado de Indicadores de Bienestar

IntroductionWithin the context of Person Centred Care, the present paper shows the creation and validation process of an observational tool for the assessment of the wellbeing of people with dementia, from a perspective that seeks to highlight the effects that the physical and social environment have on the person, and how these are reflected in the well-being.MethodsThe List of Wellbeing Indicators (LIBE) was created following an inductive iterative process with professionals from different disciplines, until the validated version was reached. It was then validated in two successive studies with a sample of 79 people with dementia. Discrimination capacity of the scale indicators, internal consistency, inter-rater reliability, and convergent and divergent validity were determined.ResultsAn internal consistency of Cronbach́s alpha 0.81 was obtained. The inter-rater reliability, analysing intraclass correlation coefficient (ICC) within the 3 raters, was significant for all the indicators in the tool, with scores between 0.59-1.00. Convergent validity was studied comparing scores in each LIBE indicator with scores in each QUALID indicator, and some significant associations were found between response categories in both tools. For the discriminant validity, the scores obtained in each LIBE indicator were compared with the scores in each PAINAD-Sp item, and no significant associations were found.ConclusionLIBE offers an observational measure of behaviours that can be considered well-being indicators in people with dementia living in residential care. LIBE is a valid and reliable tool that offers a different perspective of measuring a construct that has been infrequently explored in dementia population. Is also an easy to apply tool, with different uses (clinical, intervention, research), and applicable for professionals of several disciplines.     

Racial and socio-economic disparities in breast cancer hospitalization outcomes by insurance status

BackgroundBreast cancer remains a major cause of morbidity and mortality among women in the US, and despite numerous studies documenting racial disparities in outcomes, the survival difference between Black and White women diagnosed with breast cancer continues to widen. Few studies have assessed whether observed racial disparities in outcomes vary by insurance type e.g. Medicare/Medicaid versus private insurance. Differences in coverage, availability of networked physicians, or cost-sharing policies may influence choice of treatment and treatment outcomes, even after patients have been hospitalized, effects of which may be differential by race.PurposeThe aim of this analysis was to examine hospitalization outcomes among patients with a primary diagnosis of breast cancer and assess whether differences in outcome exist by insurance status after adjusting for age, race/ethnicity and socio-economic status.MethodsWe obtained data on over 67,000 breast cancer patients with a primary diagnosis of breast cancer for this cross-sectional study from the 2007–2011 Healthcare Cost and Utilization project Nationwide Inpatient Sample (HCUP-NIS), and examined breast cancer surgery type (mastectomy vs. breast conserving surgery or BCS), post-surgical complications and in-hospital mortality. Multivariable regression models were used to compute estimates, odds ratios and 95% confidence intervals.ResultsBlack patients were less likely to receive mastectomies compared with White women (OR: 0.80, 95% CI: 0.71–0.90), regardless of whether they had Medicare/Medicaid or Private insurance. Black patients were also more likely to experience post-surgical complications (OR: 1.41, 95% CI: 1.12–1.78) and higher in-hospital mortality (OR: 1.57, 95%: 1.21–2.03) compared with White patients, associations that were strongest among women with Private insurance. Women residing outside of large metropolitan areas were significantly more likely to receive mastectomies (OR: 1.89, 95% CI: 1.54–2.31) and experience higher in-hospital mortality (OR: 1.74, 95% CI: 1.40–2.16) compared with those in metropolitan areas, regardless of insurance type.ConclusionAmong hospitalized patients with breast cancer, racial differences in hospitalization outcomes existed and worse outcomes were observed among Black women with private insurance. Future studies are needed to determine factors associated with poor outcomes in this group of women, as well as to examine contributors to low BCS adoption in non-metropolitan areas.     

Dengue in Java,Indonesia: Relevance of Mosquito Indices as Risk Predictors

BackgroundNo vaccine is currently available for dengue virus (DENV), therefore control programmes usually focus on managing mosquito vector populations. Entomological surveys provide the most common means of characterising vector populations and predicting the risk of local dengue virus transmission. Despite Indonesia being a country strongly affected by DENV, only limited information is available on the local factors affecting DENV transmission and the suitability of available survey methods for assessing risk.Conclusions/significanceOur data suggested that the utility of traditional larvae indices, which continue to be used in many dengue endemic countries, should be re-evaluated locally. The results highlight the need for validation of risk indicators and control strategies across DENV affected areas here and perhaps elsewhere in SE Asia.