A critical appraisal of the prognostic predictive models for patients with sepsis: Which model can be applied in clinical practice?

BACKGROUND: Sepsis is associated with high mortality and predictive models can help in clinical decision-making. The objective of this study was to carry out a systematic review of these models. METHODS: In 2019, we conducted a systematic review in MEDLINE and EMBASE (CDR42018111121:PROSPERO) of articles that developed predictive models for mortality in septic patients (inclusion criteria). We followed the CHARMS recommendations (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies), extracting the information from its 11 domains (Source of data, Participants, etc). We determined the risk of bias and applicability (participants, outcome, predictors and analysis) through PROBAST (Prediction model Risk Of Bias ASsessment Tool). RESULTS: A total of 14 studies were included. In the CHARMS extraction, the models found showed great variability in its 11 domains. Regarding the PROBAST checklist, only one article had an unclear risk of bias as it did not indicate how missing data were handled while the others all had a high risk of bias. This was mainly due to the statistical analysis (inadequate sample size, handling of continuous predictors, missing data and selection of predictors), since 13 studies had a high risk of bias. Applicability was satisfactory in six articles. Most of the models integrate predictors from routine clinical practice. Discrimination and calibration were assessed for almost all the models, with the area under the ROC curve ranging from 0.59 to 0.955 and no lack of calibration. Only three models were externally validated and their maximum discrimination values in the derivation were from 0.712 and 0.84. One of them (Osborn) had undergone multiple validation studies. DISCUSSION: Despite most of the studies showing a high risk of bias, we very cautiously recommend applying the Osborn model, as this has been externally validated various times.

Quality assessment of meta-analyses evaluating randomized clinical trials to improve the prognosis of septic shock: an overview of systematic reviews.

Objective: Clinical guidelines for the treatment of septic shock are based on the studies with the best scientific evidence, which are meta-analyses of clinical trials. However, these meta-analyses may have methodological limitations that prevent their conclusions from being extrapolated to routine clinical practice. Therefore, the objective of this study is to determine the quality of these meta-analyses through a systematic review.Methods: In this systematic review, we searched MEDLINE, Scopus and EMBASE from inception to May 2019. We selected meta-analyses from clinical trials that determined the effectiveness of an intervention in reducing the incidence of mortality in patients with septic shock. All items were extracted from the Overview Quality Assessment Questionnaire (OQAQ), which collects information from both systematic reviews and meta-analyses.Results: A total of 34 studies were included. Most elements of the OQAQ were conducted satisfactorily, although 35.3% of meta-analyses did not use a quality assessment of the studies included in other analyses. In 52.9% of meta-analyses, the quality of the studies was high or very high.Conclusions: The methods used to obtain the results should be taken into account when recommending an intervention to treat septic shock if the evidence comes from a meta-analysis of the analyzed characteristics.

A one-year risk score to predict all-cause mortality in hypertensive inpatients.

The aim of this study was to construct and internally validate a scoring system to estimate the probability of death in hypertensive inpatients. Existing predictive models do not meet all the indications for clinical application because they were constructed in patients enrolled in clinical trials and did not use the recommended statistical methodology. This cohort study comprised 302 hypertensive patients hospitalized between 2015 and 2017 in Spain. The main variable was time-to-death (all-cause mortality). Secondary variables (potential predictors of the model) were: age, gender, smoking, blood pressure, Charlson Comorbidity Index (CCI), physical activity, diet and quality of life. A Cox model was constructed and adapted to a points system to predict mortality one year from admission. The model was internally validated by bootstrapping, assessing both discrimination and calibration. The system was integrated into a mobile application for Android. During the study, 63 patients died (20.9%). The points system prognostic variables were: gender, CCI, personal care and daily activities. Internal validation showed good discrimination (mean C statistic of 0.76) and calibration (observed probabilities adjusted to predicted probabilities). In conclusion, a points system was developed to determine the one-year mortality risk for hypertensive inpatients. This system is very simple to use and has been internally validated. Clinically, we could monitor more closely those patients with a higher risk of mortality to improve their prognosis and quality of life. However, the system must be externally validated to be applied in other geographic areas.

A four-year cardiovascular risk score for type 2 diabetic inpatients.

As cardiovascular risk tables currently in use were constructed using data from the general population, the cardiovascular risk of patients admitted via the hospital emergency department may be underestimated. Accordingly, we constructed a predictive model for the appearance of cardiovascular diseases in patients with type 2 diabetes admitted via the emergency department. We undertook a four-year follow-up of a cohort of 112 adult patients with type 2 diabetes admitted via the emergency department for any cause except patients admitted with acute myocardial infarction, stroke, cancer, or a palliative status. The sample was selected randomly between 2010 and 2012. The primary outcome was time to cardiovascular disease. Other variables (at baseline) were gender, age, heart failure, renal failure, depression, asthma/chronic obstructive pulmonary disease, hypertension, dyslipidaemia, insulin, smoking, admission for cardiovascular causes, pills per day, walking habit, fasting blood glucose and creatinine. A cardiovascular risk table was constructed based on the score to estimate the likelihood of cardiovascular disease. Risk groups were established and the c-statistic was calculated. Over a mean follow-up of 2.31 years, 39 patients had cardiovascular disease (34.8%, 95% CI [26.0-43.6%]). Predictive factors were gender, age, hypertension, renal failure, insulin, admission due to cardiovascular reasons and walking habit. The c-statistic was 0.734 (standard error: 0.049). After validation, this study will provide a tool for the primary health care services to enable the short-term prediction of cardiovascular disease after hospital discharge in patients with type 2 diabetes admitted via the emergency department.

Valoración nutricional de pacientes con insuficiencia renal crónica terminal al iniciar terapéutica dialítica / Nutritional assessment of patients with end-stage chronic renal failure at the begining of dialysis therapy

Se utiliza un esquema de valoración nutricional en 9 pacientes con insuficiencia renal crónica terminal al iniciar tratamiento dialítico. Se tienen en cuenta aspectos dietéticos, antropométricos, bloquímicos e inmunológicos y se evidencia en los 9 enfermos cierto grado de desnutrición proteico-calórica; se destaca cómo el estado nutricional de un paciente interviene en la evolución posterior del mismo

Valoración nutricional de pacientes con insuficiencia renal crónica terminal al iniciar terapéutica dialítica / Nutritional assessent of patients with end-stage chronic renal failure at the begining of dialysis therapy

Se utiliza un esquema de valoración nutricional en 9 pacientes con insuficiencia renal crónica terminal al iniciar tratamiento dialítico. Se tienen en cuenta aspectos dietéticos, antropométricos, bloquímicos e inmunológicos y se evidencia en los 9 enfermos cierto grado de desnutrición proteico-calórica; se destaca cómo el estado nutricional de un paciente interviene en la evolución posterior del mismo (AU)