Contribution of Low CD4 Cell Counts and High Human Immunodeficiency Virus (HIV) Viral Load to the Efficacy of Preferred First-Line Antiretroviral Regimens for Treating HIV Infection: A Systematic Review and Meta-Analysis.

We assessed whether low CD4 count and high viral load (VL) affect the response to currently preferred ART. We performed a systematic review of randomized, controlled clinical trials that analyzed preferred first-line ART and a subgroup analysis by CD4 count (≤ or >200 CD4/µL) or VL (≤ or >100 000 copies/mL). We computed the odds ratio (OR) of treatment failure (TF) for each subgroup and individual treatment arm. Patients with ≤200 CD4 cells or VL ≥100 000 copies/mL showed an increased likelihood of TF at 48 weeks: OR, 1.94; 95% confidence interval (CI): 1.45-2.61 and OR, 1.75; 95% CI: 1.30-2.35, respectively. A similar increase in the risk of TF was observed at 96 weeks. There was no significant heterogeneity regarding integrase strand transfer inhibitor or nucleoside reverse transcriptase inhibitor backbone. Our results show that CD4 <200 cells/µL and VL ≥100,000 copies/mL impair ART efficacy in all preferred regimens.

Performance and validation of the Healthy Heart Score model for predicting 12-year cardiovascular mortality in a nationwide Mediterranean population.

INTRODUCTION AND OBJECTIVES: The Healthy Heart Score (HHS) is a lifestyle-based equation for predicting cardiovascular disease (CVD) risk and may serve as a tool in primordial prevention. However, its performance outside North American populations is unknown. This study assessed the performance of the HHS for estimating CVD mortality in the adult population of Spain. METHODS: We analyzed data from the ENRICA cohort, comprising 10 228 participants free of chronic disease and representative of the Spanish population aged ≥ 18-years, who were recruited from 2008 to 2010 and were followed up to 2020. The HHS includes body mass index, alcohol, physical activity, smoking, and a 5-component dietary score. The HHS was calculated at baseline using the sex-specific beta coefficients from the original development cohorts. Model discrimination was assessed using the Harrell c-statistic and Gonen-Heller c-statistic for survival data, and calibration was evaluated through calibration plots. RESULTS: After a median follow-up of 11.8 years, 110 CVD deaths were ascertained. The discrimination of the HHS was similar for women (Harrell c, 0.91; 95%CI, 0.87-0.95; Gonen-Heller-c, 0.85; 95%CI, 0.83-0.88) and men (Harrell c, 0.91; 95%CI, 0.88-0.94; Gonen-Heller c: 0.85; 95%CI, 0.83-0.88). After recalibration by the sex-specific baseline survival function, the calibration became optimal for: a) all deciles of predicted CVD risk except the highest decile, where HHS underestimated the risk, and b) all age groups except 70 years and older, where there was an underestimation. CONCLUSIONS: In this Spanish cohort, the HHS showed good discrimination and calibration for predicting CVD death. The performance of HHS in other European populations and its implementation in the clinical setting warrants further investigation.

Prediction of significant coronary artery disease in acute chest pain without infarction in emergency department: MAPAC Cardio-PreTest model.

Acute nontraumatic chest pain is a frequent reaso n for consultation in emergency departments and represents a diagnostic challenge. The objective is to estimate the risk of significant coronary artery disease (CAD) in patients with cardiogenic acute chest pain for whom the diagnosis of infarction was ruled out in the emergency department with a nondiagnostic ECG and negative high-sensitivity troponins. We prospectively recruited 1625 patients from emergency departments of seven Spanish hospitals. The outcome was presence of significant CAD determined by presence of ischaemia in functional tests or more than 70% stenosis in imaging tests. In this study, we developed a predictive model and evaluated its performance and clinical utility. The prevalence of significant CAD was 14% [227/1625; 95% confidence interval (CI), 12-16]. MAPAC Cardio-PreTest model included seven predictors: age, sex, smoking, history of hypertension, family history of CAD, history of hyperuricaemia, and type of chest pain. The optimism-adjusted model discrimination was C-statistic 0.654 (95% CI, 0.618-0.693). Calibration plot showed good agreement between the predicted and observed risks, and calibration slope was 0.880 (95% CI, 0.731-1.108) and calibration-in-the-large -0.001 (95% CI, -0.141 to 0.132). The model increased net benefit and improved risk classification over the recommended approach by the European Society of Cardiology [Net Reclassification Index (NRI) of events = 5.3%, NRI of nonevents = 7.0%]. MAPAC Cardio-PreTest model is an online prediction tool to estimate the individualised probability of significant CAD in patients with acute chest pain without a diagnosis of infarction in emergency department. The model was more useful than the current alternatives in helping patients and clinicians make individually tailored choices about the intensity of monitoring or additional coronary tests.

Predicting major complications in patients undergoing laparoscopic and open hysterectomy for benign indications.

BACKGROUND: Hysterectomy, the most common gynecological operation, requires surgeons to counsel women about their operative risks. We aimed to develop and validate multivariable logistic regression models to predict major complications of laparoscopic or abdominal hysterectomy for benign conditions. METHODS: We obtained routinely collected health administrative data from the English National Health Service (NHS) from 2011 to 2018. We defined major complications based on core outcomes for postoperative complications including ureteric, gastrointestinal and vascular injury, and wound complications. We specified 11 predictors a priori. We used internal-external cross-validation to evaluate discrimination and calibration across 7 NHS regions in the development cohort. We validated the final models using data from an additional NHS region. RESULTS: We found that major complications occurred in 4.4% (3037/68 599) of laparoscopic and 4.9% (6201/125 971) of abdominal hysterectomies. Our models showed consistent discrimination in the development cohort (laparoscopic, C-statistic 0.61, 95% confidence interval [CI] 0.60 to 0.62; abdominal, C-statistic 0.67, 95% CI 0.64 to 0.70) and similar or better discrimination in the validation cohort (laparoscopic, C-statistic 0.67, 95% CI 0.65 to 0.69; abdominal, C-statistic 0.67, 95% CI 0.65 to 0.69). Adhesions were most predictive of complications in both models (laparoscopic, odds ratio [OR] 1.92, 95% CI 1.73 to 2.13; abdominal, OR 2.46, 95% CI 2.27 to 2.66). Other factors predictive of complications included adenomyosis in the laparoscopic model, and Asian ethnicity and diabetes in the abdominal model. Protective factors included age and diagnoses of menstrual disorders or benign adnexal mass in both models and diagnosis of fibroids in the abdominal model. INTERPRETATION: Personalized risk estimates from these models, which showed moderate discrimination, can inform clinical decision-making for people with benign conditions who may require hysterectomy.

Personalising the risk of conversion from laparoscopic to open hysterectomy in benign conditions: Development and external validation of risk prediction models.

OBJECTIVE: To develop and validate novel prediction models to personalise the risk of conversion from laparoscopic to open hysterectomy in benign conditions. DESIGN: Retrospective cohort study. SETTINGS: English NHS Hospitals between 2011 and 2018. POPULATION: 68 752 women undergoing laparoscopic hysterectomy for benign conditions. METHODS: We developed two multivariable logistic models using readily available clinical information, one for the pre-operative setting and another for operative decision-making using additional surgical information, using 2011-2016 data in five regions (24 806 women). We validated them (a) temporally in the same regions using 2017-2018 data (12 438 women); (b) geographically in the same time-period using data from three different regions (22 024 women); and (c) temporally and geographically using 2017-2018 data in three different regions (9484 women). MAIN OUTCOME MEASURES: Conversion from laparoscopic to open hysterectomy. RESULTS: Conversions occurred in 6.8% (1687/24 806) of hysterectomies in the development group, and in 5.5% (681/12 438) in the temporal, 5.9% (1297/22 204) in the geographical and 5.2% (488/9484) in the temporal and geographical validation groups. In the development cohort, the area under the receiver operating characteristic curve values for the pre-operative and operative models were 0.65 and 0.67, respectively. In the validation cohorts the corresponding values were 0.65 and 0.66 (temporal), 0.66 and 0.68 (geographical) and 0.65 and 0.68 (temporal and geographical), respectively. Factors predictive of conversion included age, Asian ethnicity, obesity, fibroids, adenomyosis, endometriosis and adhesions. Adhesions were the most predictive (odds ratio 2.54, 95% confidence interval 2.22-2.90). CONCLUSION: The models for predicting conversions showed acceptable performance and transferability. TWEETABLE ABSTRACT: Novel tool to personalise the risk of conversion from laparoscopic to open hysterectomy in benign conditions.

Prognostic models for mortality after cardiac surgery in patients with infective endocarditis: a systematic review and aggregation of prediction models.

BACKGROUND: There are several prognostic models to estimate the risk of mortality after surgery for active infective endocarditis (IE). However, these models incorporate different predictors and their performance is uncertain. OBJECTIVE: We systematically reviewed and critically appraised all available prediction models of postoperative mortality in patients undergoing surgery for IE, and aggregated them into a meta-model. DATA SOURCES: We searched Medline and EMBASE databases from inception to June 2020. STUDY ELIGIBILITY CRITERIA: We included studies that developed or updated a prognostic model of postoperative mortality in patient with IE. METHODS: We assessed the risk of bias of the models using PROBAST (Prediction model Risk Of Bias ASsessment Tool) and we aggregated them into an aggregate meta-model based on stacked regressions and optimized it for a nationwide registry of IE patients. The meta-model performance was assessed using bootstrap validation methods and adjusted for optimism. RESULTS: We identified 11 prognostic models for postoperative mortality. Eight models had a high risk of bias. The meta-model included weighted predictors from the remaining three models (EndoSCORE, specific ES-I and specific ES-II), which were not rated as high risk of bias and provided full model equations. Additionally, two variables (age and infectious agent) that had been modelled differently across studies, were estimated based on the nationwide registry. The performance of the meta-model was better than the original three models, with the corresponding performance measures: C-statistics 0.79 (95% CI 0.76-0.82), calibration slope 0.98 (95% CI 0.86-1.13) and calibration-in-the-large -0.05 (95% CI -0.20 to 0.11). CONCLUSIONS: The meta-model outperformed published models and showed a robust predictive capacity for predicting the individualized risk of postoperative mortality in patients with IE. PROTOCOL REGISTRATION: PROSPERO (registration number CRD42020192602).

Physician-Related Variability in the Outcomes of an Invasive Treatment for Neck and Back Pain: A Multi-Level Analysis of Data Gathered in Routine Clinical Practice.

Neuro-reflexotherapy (NRT) is a proven effective, invasive treatment for neck and back pain. To assess physician-related variability in results, data from post-implementation surveillance of 9023 patients treated within the Spanish National Health Service by 12 physicians were analyzed. Separate multi-level logistic regression models were developed for spinal pain (SP), referred pain (RP), and disability. The models included all patient-related variables predicting response to NRT and physician-related variables. The Intraclass Correlation Coefficient (ICC) and the Median Odds Ratio (MOR) were calculated. Adjusted MOR (95% CI) was 1.70 (1.47; 2.09) for SP, 1.60 (1.38; 1.99) for RP, and 1.65 (1.42; 2.03) for disability. Adjusted ICC (95%CI) values were 0.08 (0.05; 0.15) for SP, 0.07 (0.03; 0.14) for RP, and 0.08 (0.04; 0.14) for disability. In the sensitivity analysis, in which the 6920 patients treated during the physicians' training period were excluded, adjusted MOR was 1.38 (1.17; 1.98) for SP, 1.37 (1.12; 2.31) for RP, and 1.25 (1.09; 1.79) for disability, while ICCs were 0.03 (0.01; 0.14) for SP, 0.03 (0.00; 0.19) for RP, and 0.02 (0.00; 0.10) for disability. In conclusion, the variability in results obtained by different NRT-certified specialists is reasonable. This suggests that current training standards are appropriate.

Prognostic assessment of valvular surgery in active infective endocarditis: multicentric nationwide validation of a new score developed from a meta-analysis.

OBJECTIVES: Several risk prediction models have been developed to estimate the risk of mortality after valve surgery for active infective endocarditis (IE), but few external validations have been conducted to assess their accuracy. We previously developed a systematic review and meta-analysis of the impact of IE-specific factors for the in-hospital mortality rate after IE valve surgery, whose obtained pooled estimations were the basis for the development of a new score (APORTEI). The aim of the present study was to assess its prognostic accuracy in a nationwide cohort. METHODS: We analysed the prognostic utility of the APORTEI score using patient-level data from a multicentric national cohort. Patients who underwent surgery for active IE between 2008 and 2018 were included. Discrimination was evaluated using the area under the receiver operating characteristic curve, and the calibration was assessed using the calibration slope and the Hosmer-Lemeshow test. Agreement between the APORTEI and the EuroSCORE I was also analysed by Lin's concordance correlation coefficient (CCC), the Bland-Altman agreement analysis and a scatterplot graph. RESULTS: The 11 variables that comprised the APORTEI score were analysed in the sample. The APORTEI score was calculated in 1338 patients. The overall observed surgical mortality rate was 25.56%. The score demonstrated adequate discrimination (area under the receiver operating characteristic curve = 0.75; 95% confidence interval 0.72-0.77) and calibration (calibration slope = 1.03; Hosmer-Lemeshow test P = 0.389). We found a lack of agreement between the APORTEI and EuroSCORE I (concordance correlation coefficient = 0.55). CONCLUSIONS: The APORTEI score, developed from a systematic review and meta-analysis, showed an adequate estimation of the risk of mortality after IE valve surgery in a nationwide cohort.

Increased HIV infection in patients with stroke in Spain. A 16-year population-based study.

INTRODUCTION: An increased incidence of stroke in HIV-infected patients has already been reported, suggesting that HIV infection may be a cerebrovascular risk factor. The objective of this study was to assess temporal trends in the proportion of HIV infection among patients with stroke in Spain. METHODS: Data were obtained from the minimum basic dataset (MBDS) of all patients hospitalized in Spain between 1997 and 2012 with a primary or secondary diagnosis of stroke. The annual proportion of HIV infection and time trends (stratifying by type of stroke and HIV stage) were calculated, and predictors of HIV infection and the social and economic impact of HIV-infected (HIV+) and non-infected (HIV-) patients were analyzed. RESULTS: Of 857,371 patients hospitalized with an incident stroke, 2134 (0.25%) had HIV infection. A 2.5% year-on-year increase (OR 1.025, 95% CI 1.015-1.036, p<0.0001) of the proportion of HIV-infected patients was observed due to an increase in the asymptomatic stage of the infection (per year OR 1.077, 95% CI 1.057-1.097, p<0.0001), as the proportion of patients with AIDS remained stable. Factors independently associated with HIV infection and stroke were active smoking, stimulating drugs and hepatitis C virus (HCV) infection. A higher mortality rate, longer hospital stay and a higher cost per hospitalized patient was observed among HIV+ patients. CONCLUSIONS: From 1997 to 2012, there was an increase in the proportion of HIV infection among patients hospitalized with stroke irrespective of the classical vascular risk factors, reinforcing the role of HIV infection as a cerebrovascular risk factor.

Predicting the evolution of neck pain episodes in routine clinical practice.

BACKGROUND: The objective of this study was to develop models for predicting the evolution of a neck pain (NP) episode. METHODS: Three thousand two hundred twenty-five acute and chronic patients seeking care for NP, were recruited consecutively in 47 health care centers. Data on 37 variables were gathered, including gender, age, employment status, duration of pain, intensity of NP and pain referred down to the arm (AP), disability, history of neck surgery, diagnostic procedures undertaken, imaging findings, clinical diagnosis, and treatments used. Three separate multivariable logistic regression models were developed for predicting a clinically relevant improvement in NP, AP and disability at 3 months. RESULTS: Three thousand one (93.5%%) patients attended follow-up. For all the models calibration was good. The area under the ROC curve was ≥0.717 for pain and 0.664 for disability. Factors associated with a better prognosis were: a) For all the outcomes: pain being acute (vs. chronic) and having received neuro-reflexotherapy. b) For NP: nonspecific pain (vs. pain caused by disc herniation or spinal stenosis), no signs of disc degeneration on imaging, staying at work, and being female. c) For AP: nonspecific NP and no signs of disc degeneration on imaging. d) For disability: staying at work and no signs of facet joint degeneration on imaging. CONCLUSIONS: A prospective registry can be used for developing valid predictive models to quantify the odds that a given patient with NP will experience a clinically relevant improvement.