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Introduction Prediction of fluid responsiveness in acutely ill patients might be influenced by a number of clinical and technical factors. We aim to identify variables potentially modifying the operative performance of fluid responsiveness predictors commonly used in clinical practice. Methods A sensitive strategy was conducted in the Medline and Embase databases to search for prospective studies assessing the operative performance of pulse pressure variation, stroke volume variation, passive leg raising (PLR), end-expiratory occlusion test (EEOT), mini-fluid challenge, and tidal volume challenge to predict fluid responsiveness in critically ill and acutely ill surgical patients published between January 1999 and February 2023. Adjusted diagnostic odds ratios (DORs) were calculated by subgroup analyses (inverse variance method) and meta-regression (test of moderators). Variables potentially modifying the operative performance of such predictor tests were classified as technical and clinical. Results A total of 149 studies were included in the analysis. The volume used during fluid loading, the method used to assess variations in macrovascular flow (cardiac output, stroke volume, aortic blood flow, volume‒time integral, etc.) in response to PLR/EEOT, and the apneic time selected during the EEOT were identified as technical variables modifying the operative performance of such fluid responsiveness predictor tests ( p  < 0.05 for all adjusted vs. unadjusted DORs). In addition, the operative performance of fluid responsiveness predictors was also influenced by clinical variables such as the positive end-expiratory pressure (in the case of EEOT) and the dose of norepinephrine used during the fluid responsiveness assessment for PLR and EEOT (for all adjusted vs. unadjusted DORs). Conclusion Prediction of fluid responsiveness in critically and acutely ill patients is strongly influenced by a number of technical and clinical aspects. Such factors should be considered for individual intervention decisions.

Introduction: Pulse pressure variation (PPV) has been shown to be useful to predict fluid responsiveness in patients ventilated at tidal volume (Vt) >8 mL kg−1. Nevertheless, most conditions in critical care force to use lower Vt. Thus, we sought to evaluate the operative performance of PPV when a Vt ⩽8 mL kg−1 is used during mechanical ventilation support. Methods: We searched PubMed and Embase databases for articles evaluating the operative performance of PPV as a predictor of fluid responsiveness in critical care and perioperative adult patients ventilated with tidal volume ⩽8 mL kg−1 without respiratory effort and arrhythmias, between January 1990 and January 2019. We included cohort and cross-sectional studies. Two authors performed an Independently selection using predefined terms of search. The fitted data of sensitivity, specificity, and area under the curve (AUC) were assessed by bivariate and hierarchical analyses. Results: We retrieved 19 trials with a total of 777 patients and a total of 935 fluid challenges. The fitted sensitivity of PPV to predict fluid responsiveness during mechanical ventilation at Vt ⩽8 mL kg−1 was 0.65 (95% confidence interval [CI]: 0.57-0.73), the specificity was 0.79 (95% CI: 0.73-0.84), and the AUC was 0.75. The diagnostic odds ratio was 5.5 (95% CI: 3.08-10.01, P < .001) by the random-effects model. Conclusions: Pulse pressure variation shows a fair operative performance as a predictor of fluid responsiveness in critical care and perioperative patients ventilated with a tidal volume ⩽8 mL kg−1 without respiratory effort and arrhythmias.

Introduction:Due to the clinical heterogeneity of COVID-19, biomarkers must be used to confirm the disease's diagnosis and determine its prognosis. Objective:To assess the performance of ferritin as a diagnostic biomarker in cases of suspected diagnosis of COVID-19 in inpatients and as a prognostic biomarker in those with a confirmed diagnosis. Materials and methods:Multicenter, prospective, observational study conducted in 711 adult patients hospitalized between April and November 2020 in three quaternary care hospitals in Bogotá D.C., Colombia, due to suspected COVID-19. Based on ferritin levels on hospital admission, ROC curves were created for three outcomes: diagnosis, admission to the intensive care unit (ICU), and death. The operating characteristics of this biomarker were calculated for each outcome, and a multivariate analysis was carried out using a linear regression model to evaluate the association between ferritin levels and each outcome. Results:COVID-19 diagnosis was confirmed in 592 patients, of whom 160 (27.02%) were admitted to the ICU and 107 (18.07%) died. The areas under the ROC curve (AUC) for diagnosis, ICU admission, and death were 0.67 (95%CI: 0.62-0.73), 0.58 (95%CI: 0.57-0.67), and 0.56 (95%CI: 0.50-0.63), respectively. In the bivariate analysis, ferritin levels were significantly associated with diagnosis (p=0.003) and admission to the ICU (p<0.001), but not with mortality (p=0.326). In the multivariate analysis, ferritin was only significantly associated with admission to the ICU (p=0.009). Conclusions:Ferritin showed poor and moderate performance as a prognostic and a diagnostic biomarker, respectively. Therefore, neither the diagnosis of patients with suspected COVID-19, nor the prognosis of those with a confirmed diagnosis can be determined based only on serum ferritin levels.

Several limitations regarding pulse pressure variation (PPV) use have been reported. Our aim was to describe changes in the PPV operative performance as a predictor of fluid responsiveness during the development of a swine endotoxin shock model and to assess hemodynamic variables associated with PPV changes. A swine porcine endotoxin shock model was established ( Escherichia Coli 055:B5 endotoxin) in 7 pigs, and 3 pigs were included in the control group. The endotoxin was infused until the mean arterial pressure (MAP) dropped below 50 mmHg (TH0); then, the model animal was reanimated with fluids and vasopressors. We performed fluid challenges every hour for 6 h. ROC curve analysis and a linear mixed model were performed. The area under the curve of PPV decreased from 0.95 (0.81–1.00) to 0.60 (0.17–1.00) at TH0. Its cutoff increased from 10.5 to 22.00% at TH0. PPV showed an inverse relationship with stroke volume, mean systemic filling pressure, MAP, and systemic vascular resistance (SVR) ( p  < 0.001, AIC = 111.85). The PPV operative performance as a predictor of fluid responsiveness decreased with the progression of shock. This could lead to an inverse association between PPV and the following variables: MAP and SVR.

Introduction: Heart failure is one of the most prevalent diseases worldwide. In Colombia, the state of research on the subject is unknown. Objective: To describe the original publications on heart failure in Colombia. Materials and methods: Systematic review. Digital search in Embase, PubMed, LILACS and Scielo, using the MeSH terms: “heart failure”, “Colombian”, “Colombia”, “Latin America”, “developing countries”. Manual search of 58 journals identified in Publindex. Original research that evaluated adult Colombians with heart failure and published between 1980 and 2015 were included. Results: 2 684 articles were identified, of which 35 met the inclusion criteria. 30 (85.7%) were published since 2009, 30 (85.7%) were conducted in Bogotá and Medellín, 11 (31.4%) had n>200, 19 (54.2%) were descriptive and 5 (14.2%) quasi-experimental. Moreover, 9 (25.7%) described general populations, 9 (25.7%) addressed the issue of self-care, 3 (8.8%) cardiac rehabilitation, 3 (8.8%) perception of the disease and 3 (8.8%) prognostic factors. Conclusions: The amount of published original research on heart failure is low, and most of them were carried out recently. Descriptive design was the most frequent, while the most frequently addressed topics were self-care and population descriptions.

The persistence of inflammatory processes in the myocardium in varying degrees of chronic Chagas heart disease has been poorly investigated. We hypothesized that edema could occur in patients with chronic chagasic cardiomyopathy and corresponds to the persistence of inflammatory processes in the myocardium. Eighty-two Chagas disease (CD) seropositive patients (64.6% females; age = 58.9 ± 9.9) without ischemic heart disease or conditions that cause myocardial fibrosis and dilation were considered. Late gadolinium enhancement (LGE) and T2-weighted magnetic resonance imaging of edema were obtained and represented using a 17-segment model. Patients were divided into three clinical groups according to the left ventricular (LV) ejection fraction (EF) as G1 (EF > 60%; n=37), G2 (35% > EF < 60%; n=33), and G3 (EF < 35%; n=12). Comparisons were performed by the Fisher or ANOVA tests. Bonferroni post hoc, Spearman correlation, and multiple correspondence analyses were also performed. Edema was observed in 8 (9.8%) patients; 2 (5.4%) of G1, 4 (12.1%) of G2, and 2 (16.7%) of G3. It was observed at the basal inferolateral segment in 7 (87.5%) cases. LGE was observed in 48 (58.5%) patients; 16 (43.2%) of G1, 21 (63.6%) of G2, and 11 (91.7%) of G3 (p<0.05). It was observed in the basal inferior/inferolateral/anterolateral segments in 35 (72.9%) patients and in the apical anterior/inferior/lateral and apex segments in 21 (43.7%), with midwall (85.4%; n=41), subendocardial (56.3%; n=27), subepicardial (54.2%; n=26), transmural (31.2%; n=15), and RV (1.2%; n=1) distribution. Subendocardial lesions were observed only in patients with LVEF < 35%. There was no involvement of the mid-inferolateral/anterolateral segments with an LVEF > 35% (p<0.05). Deteriorations of the LV and RV systolic functions were positively correlated (rs=0.69; p<0.05) without evidence of LGE in the RV. Edema can be found in patients with chagasic cardiomyopathy in the chronic stage. In later stages of cardiac dilation with low LVEF, the LGE pattern involves subendocardium and mid locations. Deteriorations of RV and LV are positively correlated without evidence of fibrosis in the RV.

Introduction: Metabolic acidosis is a frequent pathophysiological condition in critically ill patients. It can be assessed using different physiological variables, but their prognostic value has not yet been well established. Objective:To evaluate the association between the variables that allow assessing the metabolic component of acid-base balance (ABB) and 28-day mortality in patients admitted to an intensive care unit (ICU) in Bogotá, D.C., Colombia. Materials and methods: Prospective cohort study conducted in 122 patients admitted to an ICU between January and June 2013 and with a stay >24 hours. On admission to the ICU, blood samples were taken, and an arterial blood gas test was performed in order to calculate the following variables: anion gap (AG), corrected anion gap (AGc), standard base excess (BEst), metabolic H+, base excess-unmeasurable anions (BEua), arterial pH, arterial lactate, standard HCO3-st, and strong ion difference (SID). APACHE II and SOFA scores were also calculated. A bivariate analysis was performed in which ORs and their respective 95%CI were calculated, and then a multivariate analysis was conducted using a logistic regression model to identify the variables associated with 28-day mortality; a significance level of p<0.05 was considered. Results: Out of the 122 patients, 33 (27.05%) died at 28 days and 51 (48.80%) were women. Participants’ mean age was 46.5 years (±15.7). The following variables were significantly associated with 28-day mortality in the bivariate analysis: SID (OR=1.150; p=0.008), BEua (OR=0.897; p=0.023), AG (OR=1.231; p=0.002), AGc (OR=1.232; p=0.003), blood pH (OR=0.001; p=0.023), APACHE II (OR=1.180; p=0.001), HCO3-st (OR=0.841; p=0.015). In the multivariate analysis, only the APACHE II score variable was significantly associated with 28-day mortality (OR=1.188; p=0.008). Conclusion: The physiological variables that allow assessing the metabolic component of ABB, both from the Henderson model and the Stewart model, were not significantly associated with 28-day mortality.

Introduction. Detecting acute kidney injury (AKI) in the first days of hospitalization could prevent potentially fatal complications. However, epidemiological data are scarce, especially on nonsurgical patients. Objectives. To determine the incidence and risk factors associated with AKI within five days of hospitalization (EAKI). Methods. Prospective cohort of patients hospitalized in the Internal Medicine Department. Results. A total of 16% of 400 patients developed EAKI. The associated risk factors were prehospital treatment with nephrotoxic drugs (2.21 OR; 95% CI 1.12–4.36, p=0.022), chronic kidney disease (CKD) in stages 3 to 5 (3.56 OR; 95% CI 1.55–8.18, p<0.003), and venous thromboembolism (VTE) at admission (5.05 OR; 95% CI 1.59–16.0, p<0.006). The median length of hospital stay was higher among patients who developed EAKI (8 [IQR 5–14] versus 6 [IQR 4–10], p=0.008) and was associated with an increased requirement for dialysis (4.87 OR 95% CI 2.54 to 8.97, p<0.001) and in-hospital death (3.45 OR; 95% CI 2.18 to 5.48, p<0.001). Conclusions. The incidence of EAKI in nonsurgical patients is similar to the worldwide incidence of AKI. The risk factors included CKD from stage 3 onwards, prehospital treatment with nephrotoxic drugs, and VTE at admission. EAKI is associated with prolonged hospital stay, increased mortality rate, and dialysis requirement.

Introduction: The evaluation of metabolism and the diagnostic classification of acid-base disorders has generated great controversy. Acid-base balance (ABB) is approached by means of the physicochemical and Henderson’s models.Objective: To compare two diagnostic approaches to ABB in patients with severe sepsis.Materials and methods: Prospective, descriptive study conducted in patients with severe sepsis. ABB was analyzed within the first 24 hours. The diagnosis was compared according to each model and the causes of the disorders were compared according to the physicochemical model.Results: 38 patients were included in the study, of which 21 (55%) were women; the mean age was 49 years, the median APACHE II, 13.28, and the mortality at 28 days, 24.3%. The traditional approach identified 8 patients with normal ABB, 20 with metabolic acidosis, and 10 with other disorders. Based on the physicochemical model, all subjects had acidosis and metabolic alkalosis. Increased strong ion difference (SID) was the most frequently observed disorder.Conclusion: The physicochemical model was useful to diagnose more patients with acid-base disorders. According to these results, all cases presented with acidosis and metabolic alkalosis; the most frequent proposed mechanism of acidosis was elevated SID. The nature of these disorders and their clinical relevance is yet to be established.

To identify prognostic markers by applying machine learning strategies to the feature selection.An observational, retrospective, multi-center study that included hospitalized patients with a confirmed diagnosis of COVID-19 in three hospitals in Colombia. Eight strategies were applied to select prognostic-related characteristics. Eight logistic regression models were built from each set of variables and the predictive ability of the outcome was evaluated. The primary endpoint was transfer to intensive care or in-hospital death.The database consisted of 969 patients of which 486 had complete data. The main outcome occurred in 169 cases. The development database included 220 patients, 137 (62.3%) were men with a median age of 58.2, 39 (17.7%) were diabetic, 62 (28.2%) had high blood pressure, and 32 (14.5%) had chronic lung disease. Thirty-three variables were identified as prognostic markers, and those selected most frequently were: LDH, PaO2/FIO2 ratio, CRP, age, neutrophil and lymphocyte counts, respiratory rate, oxygen saturation, ferritin, and HCO3. The eight logistic regressions developed were validated on 266 patients in whom similar results were reached (accuracy: 65.8–72.9%).The combined use of strategies for selecting characteristics through machine learning techniques makes it possible to identify a broad set of prognostic markers in patients hospitalized for COVID-19 for death or hospitalization in intensive care.