Natalia Fernanda Pascual Gómez

Background: Increased cardiovascular risk has been described in individuals with adrenal incidentalomas. The aim of the present study is to assess the effect of remnant cholesterol (RC) on the cardiovascular risk and mortality of patients with adrenal incidentalomas. Methods: A retrospective cohort study was conducted with patients with adrenal incidentalomas between 2001 and 2024. One hundred thirty-seven patients (mean age of 61.2 ± 11.5 years; 56.6% women) with non-functioning adrenal incidentalomas and with mild autonomous cortisol secretion (MACS) (cortisol post-dexamethasone suppression test ≥1.8 µg/mL) were included. The patients were divided into two groups using 30 mg/dL as the cut-off for RC. Logistic regression models were used to study the impact of RC on major adverse cardiovascular events and mortality (MACEs). Results: Patients with RC ≥ 30 mg/dL exhibited a higher prevalence of type 2 diabetes mellitus (T2D) (p < 0.001), lower HDL-C (p < 0.001) and LDL-C (p = 0.025) levels, a higher frequency of treatment with statins (p = 0.032), and a higher rate of non-fatal major cardiovascular events (p = 0.038) and MACEs (p = 0.038). Patients with MACS showed no differences in RC or complications during the follow-up. The relative risk of high RC was 2.65 (1.04–6.77) for cardiovascular events and 2.27 (1.05–4.92) for MACEs, with p < 0.05 in both cases. The only variables independently affecting MACEs were age ([odds ratio] OR = 1.13 [p = 0.004]), female sex (OR = 0.20; p = 0.016), LDL-C (OR = 1.02; p = 0.029), and RC (OR = 1.06; p = 0.014). T2D and HDL-C were not independently associated with MACEs. Conclusions: RC ≥30 mg/dL in patients with adrenal incidentalomas was associated with a higher prevalence of T2D, lower HDL-C levels, and a higher risk of MACEs. MACS was not associated with RC or MACEs during the follow-up.

The main objective of the study was to verify whether levels of procalcitonin (PCT) could guide us toward determining the type of bacteria causing the sepsis and to identify the discriminatory cut-off point in the first urgent laboratory test. This study is a single center retrospective analysis that includes 371 patients with a mean age of 71.7 ± 15.6 years who were diagnosed with sepsis or septic shock. The yield of blood cultures in demonstrating the causative microbiological agent was 24.3% (90), and it was 57, 1% (212) when evaluating all types of cultures. Statistically significant positive differences were observed in the mean value of the PCT between the group that obtained positive cultures and the group that did not (p < 0.0001). The AUC-ROC of PCT values as a guide to the causal bacteria type was 0.68 (95%CI: 0.57–0.78, p < 0.0021). The PCT value that showed the best diagnostic characteristics for identifying Gram-negative rods (GNR) as the causative agent in blood cultures was 2.1 ng/mL. The positive predictive value (PPV) was 78, 9% (66.3–88.1%). The AUC-ROC of the PCT values for sepsis diagnosis, with any positive culture that could be assessed, was 0.67 (95%CI: 0.63–0.73, p < 0.0001). The PCT value that showed the best diagnostic characteristic for predicting sepsis was 3.6 ng/mL.

Sepsis is a time-dependent disease whose prognosis is influenced by early diagnosis and therapeutic measures. Mortality from sepsis remains high, and for this reason, the guidelines of the Surviving Sepsis Campaign recommend establishing specific care programs aimed at patients with sepsis. We present the results of the application of a hospital model to improve performance in sepsis care, called Princess Sepsis Code, with the aim of reducing mortality. A retrospective study was conducted using clinical, epidemiological, and outcome variables in patients diagnosed with sepsis from 2015 to 2022. A total of 2676 patients were included, 32% of whom required admission to the intensive care unit, with the most frequent focus of the sepsis being abdominal. Mortality in 2015, at the beginning of the sepsis code program, was 24%, with a declining rate noted over the study period, with mortality reaching 17% in 2022. In the multivariate analysis, age > 70 years, respiratory rate > 22 rpm, deterioration in the level of consciousness, serum lactate > 2 mmol/L, creatinine > 1.6 mg/dL, and the focus of the sepsis were identified as variables independently related to mortality. The implementation of the Princess Sepsis Code care model reduces the mortality of patients exhibiting sepsis and septic shock.

The need for postoperative organic support is associated with patient outcomes. Biomarkers may be useful for detecting patients at risk. MR-ProADM is a novel biomarker with an interesting profile that can be used in this context. The main objective of this study was to verify whether there was an association between the preoperative serum levels of MR-ProADM and the need for organic support after elective abdominal cancer surgery, and to determine the preoperative MR-ProADM value that predicts the need for postoperative organic support. This was a multicenter prospective observational study conducted by four tertiary hospitals in Spain between 2017 and 2018. Plasma samples were collected for the quantification of MR-ProADM from adults who underwent major abdominal surgery during 2017–2018. The primary outcome was the need for organic support in the first seven postoperative days and its association with the preoperative levels of MR-ProADM, and the secondary outcome was the preoperative levels of MR-ProADM in the study population. This study included 370 patients with a mean age of 67.4 ± 12.9 years. Seventeen percent (63 patients) required some postoperative organic support measures in the first week. The mean preoperative value of MR-ProADM in patients who required organic support was 1.16 ± 1.15 nmol/L. The AUC-ROC of the preoperative MR-ProADM values associated with the need for organic support was 0.67 (95% CI: 0.59–0.75). The preoperative MR-ProADM value, which showed the best compromise in sensitivity and specificity for predicting the need for organic support, was 0.70 nmol/L. The negative predictive value was 91%. A multivariate analysis confirmed that a preoperative level of MR-ProADM ≥ 0.70 nmol/L is an independent factor associated with risk of postoperative organic support (OR 2, 6). Elevated preoperative MR-ProADM levels are associated with the need for postoperative organic support. Therefore, MR-ProADM may be a useful biomarker for perioperative risk assessment.

Resumen: La norma ISO 15189:2012 exige una serie de requisitos en cuanto a la gestión de muestras clínicas, el aseguramiento de la calidad del proceso y la gestión de la información del laboratorio. Además, la entidad acreditadora, ENAC en España, tiene establecidas las condiciones para el uso de la marca en el informe de resultados del laboratorio acreditado. Las recomendaciones planteadas aplican a las actividades incluidas en el proceso posanalítico del laboratorio, así como al personal implicado. Se indican los criterios para que el laboratorio defina y documente el tiempo y las condiciones de retención de las muestras, para diseñar un control de calidad interno que verifique si las actividades posanalíticas alcanzan la calidad esperada, los requisitos que debe cumplir la gestión de la información y la necesidad de disponer de un plan de contingencia que asegure la comunicación de los resultados en todo momento. Asimismo, se describe el uso correcto de la marca de acreditación en los informes. Diversos gobiernos y sociedades científicas abogan por la obligatoriedad de la acreditación de los laboratorios clínicos. Siendo la norma ISO 15189 la más específica para demostrar su competencia técnica, es indispensable el conocimiento y la comprensión de sus requisitos para su correcta implantación.

Objective. Identify which biomarkers performed in the first emergency analysis help to stratify COVID-19 patients according to mortality risk. Method. Observational, descriptive and cross-sectional study performed with data collected from patients with suspected COVID-19 in the Emergency Department from February 24 to March 16, 2020. The univariate and multivariate study was performed to find independent mortality markers and calculate risk by building a severity score. Results. A total of 163 patients were included, of whom 33 died and 29 of them were positive for the COVID-19 PCR test. We obtained as possible factors to conform the Mortality Risk Score age> 75 years ((adjusted OR = 12,347, 95% CI: 4,138-36,845 p = 0.001), total leukocytes> 11,000 cells / mm3 (adjusted OR = 2,649, 95% CI: 0.879-7.981 p = 0.083), glucose> 126 mg / dL (adjusted OR = 3.716, 95% CI: 1.247-11.074 p = 0.018) and creatinine> 1.1 mg / dL (adjusted OR = 2.566, 95% CI: 0.889- 7.403, p = 0.081) This score was called COVEB (COVID, Age, Basic analytical profile) with an AUC 0.874 (95% CI: 0.816-0.933, p <0.001; Cut-off point = 1 (sensitivity = 89.66 % (95% CI: 72.6% -97.8%), specificity = 75.59% (95% CI: 67.2% -82.8%). A score <1 has a negative predictive value = 100% (95% CI: 93.51% -100%) and a positive predictive value = 18.59% (95% CI: 12.82% -25.59%). Conclusions. Clinical severity scales, kidney function biomarkers, white blood cell count parameters, the total neutrophils / total lymphocytes ratio and procalcitonin are early risk factors for mortality. The variables age, glucose, creatinine and total leukocytes stand out as the best predictors of mortality. A COVEB score <1 indicates with a 100% probability that the patient with suspected COVID-19 will not die in the next 30 days.