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BACKGROUND: Timely and accurate assessment of coagulopathy is crucial for the management of primary postpartum hemorrhage (PPH). Thromboelastography (TEG) provides a comprehensive assessment of coagulation status and is useful for guiding the treatment of hemorrhagic events in various diseases. This study aimed to evaluate the role of TEG in predicting hypofibrinogenemia in emergency department (ED) patients with primary PPH. METHODS: We conducted a retrospective observational study in the ED of a university-affiliated tertiary hospital between November 2015 and August 2023. TEG was performed upon admission. The cutoff value for hypofibrinogenemia was 200 mg/dL. The primary outcome was the presence of hypofibrinogenemia. RESULTS: Among the 174 patients, 73 (42.0%) had hypofibrinogenemia. The need for massive transfusion was higher in the hypofibrinogenemia group (37.0% vs. 5.0%, p < 0.001). Among the TEG parameters, all values were significantly different between the groups, except for lysis after 30 min, suggesting a tendency toward hypocoagulability. Multivariable analysis revealed that the alpha angle (odds ratio (OR) 0.924, 95% confidence interval (CI) 0.876-0.978) and maximum amplitude (MA) (OR 0.867, 95% CI 0.801-0.938) were independently associated with hypofibrinogenemia. The optimal cutoff values for the alpha angle and maximum amplitude (MA) for hypofibrinogenemia were 63.8 degrees and 56.1 mm, respectively. CONCLUSION: Point-of-care TEG could be a valuable tool for the early identification of hypofibrinogenemia in ED patients with primary PPH.

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Bedside screening tests for predicting difficult intubation play a crucial role in clinical practice, although their utility remains limited. This prospective observational study aimed to assess the predictive value of the Acromio-Axillo-Suprasternal Notch Index (AASI) for difficult visualization of the larynx (DVL). Following approval from the Institutional Ethics Sub-Committee (Research Protocol No.: IESC/FP/68/2023), this prospective, observational, single-center study involved a sample size of 100 consecutive adult patients, both male and female, aged 20 to 65 years. The participants were classified as American Society of Anesthesiologists (ASA) grade I or II and were scheduled for elective surgeries necessitating endotracheal intubation. Before the operation, the following factors were assessed: AASI, modified Mallampati test (MMT), sternomental distance (SMD), thyromental distance (TMD), and inter-incisor distance (IID). Larynx visualization was evaluated using the Cormack-Lehane (CL) grading system, where grades III and IV indicate difficult laryngeal visualization. Qualified anesthesiologists performed direct laryngoscopy while remaining unaware of the outcomes of the airway predictors being assessed. The main aim of the investigation was to assess the efficacy of the AASI as a means of predicting DVL. The research study's secondary goals involved evaluating the accuracy of AASI in predicting challenging airways compared to other predictors such as MMT, SMD, TMD, and IID. DVL was observed in 21% of patients, out of which 10 and 11 were males and females, respectively. The sensitivity, specificity, and area under the curve (AUC) of the AASI were observed and reported with a 95% confidence interval (CI), being 98.73% (93.2-99.9%), 71.43% (47.8-88.7%), and 0.851 (0.732-0.970), respectively. AUC analysis revealed that AASI outperformed MMT, SMD, TMD, and IID as a predictor of DVL. AASI (≥0.5) serves as an excellent predictor for DVL during direct laryngoscopy. This finding suggests the clinical utility of AASI in identifying patients who may require special consideration during intubation procedures.

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Objetivo: Evaluar el valor predictivo negativo de la ratio antigénica y conocer su rentabilidad para descartar preeclampsia precoz en pacientes de alto riesgo de desarrollarla, con profilaxis de ácido acetilsalicílico. Métodos: Se realizó un estudio descriptivo transversal que recogió a las gestantes con cribado de preeclampsia precoz de alto riesgo (384 gestantes) en el Hospital Santa Lucía durante el año 2021, para lo que se usó test Elecsys® tabulado a un riesgo mayor a 1/150 en primer trimestre, y que tomaran ácido acetilsalicílico antes de la semana 16, quedando en 368 gestantes vistas en las semanas 20, 26, 31 y 36. Se realizó biometría, ratio angiogénica y doppler. Resultados: La incidencia de preeclampsia precoz en la población fue 4 casos (incidencia 1,08 %). Son significativos por su alto valor predictivo negativo del 100 % de preeclampsia precoz: la ratio angiogénica mayor a 38 en la semana 26 y el doppler de las uterinas en semana 20 y 26. Conclusión: En gestaciones con cribado de alto riesgo de preeclampsia que tomen ácido acetilsalicílico, una ratio angiogénica menor a 38 en la semana 26, además de un doppler uterino normal en semana 20 y 26 permite reducir el seguimiento gestacional(AU)

Objective: Our main objective was to evaluate the negative predictive value of the angiogenic ratio and to know its profitability to rule out early preeclampsia in patients at high risk of early preeclampsia with acetylsalicylic acid prophylaxis. Methods: A cross-sectional descriptive study was carried out that included pregnant women with high-risk early preeclampsia screening (384 pregnant women) at the Santa Lucía Hospital during the year 2021, for which the Elecsys® test tabulated at a risk >1/ was used. 150 in the first trimester, and who take acetylsalicylic acid before week 16, leaving 368 pregnant women seen in weeks 20, 26, 31 and 36, with biometry, angiogenic ratio and Doppler performed. Results: The incidence of early preeclampsia in the population was 4 cases (incidence 1.08%). They are significant due to their high negative predictive value of 100% of early preeclampsia: Angiogenic ratio > 38 in week 26, uterine Doppler in weeks 20 and 26. Conclusion: Pregnancies with high risk screening for preeclampsia who take acid acetylsalicylic acid, an angiogenic ratio < 38 at week 26 in addition to a normal uterine Doppler at weeks 20 and 26 allows for reduced gestational follow-up(AU)

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OBJECTIVE: There is a need for refined methods to detect and quantify brain injuries that may be undetectable by magnetic resonance imaging and neurologic examination. This review evaluates the potential efficacy of circulating brain injury biomarkers for predicting outcomes following elective neurosurgical procedures. METHODS: A comprehensive search was conducted using the Cochrane, PubMed, and Scopus databases. RESULTS: Analysis of 23 relevant studies revealed that specific biomarkers, including glial fibrillary acidic protein, neurofilament light chain, neuron-specific enolase, S100B, and tau, are significantly associated with the extent of brain injury and could potentially predict postsurgical outcomes. The evaluated studies described intracranial tumor surgeries and miscellaneous neurosurgical interventions and demonstrated the complex relationship between biomarker levels and patient outcomes. CONCLUSIONS: Circulating brain injury biomarkers show promise for providing objective insights into the extent of perioperative brain injury and improving prognostication of postsurgical outcomes. However, the heterogeneity in study designs and outcomes along with the lack of standardized biomarker thresholds underscore the need for further research.

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This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from March to December 2021 were included retrospectively. The PPV was evaluated according to the true-positive (TP) and false-positive (FP) diagnosis determined by radiologists. To know the factors that might influence the results, logistic regression with generalized estimating equation was used. Among a total of 87,658 CXRs, 308 CXRs with 331 pneumothoraces from 283 patients were finally included. The overall PPV of AI about pneumothorax was 41.1% (TF:FP = 136:195). The PA view (odds ratio [OR], 29.837; 95% confidence interval [CI], 15.062-59.107), high abnormality score (OR, 1.081; 95% CI, 1.066-1.097), large amount of pneumothorax (OR, 1.005; 95% CI, 1.003-1.007), presence of ipsilateral atelectasis (OR, 3.508; 95% CI, 1.509-8.156) and a small amount of ipsilateral pleural effusion (OR, 5.277; 95% CI, 2.55-10.919) had significant effects on the increasing PPV. Therefore, PPV for pneumothorax diagnosis using AI can vary based on patients' factors, image-acquisition protocols, and the presence of concurrent lesions on CXR.

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BACKGROUND: In patients with peripheral pulmonary lesions (PPLs), nondiagnostic bronchoscopy results are not uncommon. The conventional approach to estimate the probability of cancer (pCA) after bronchoscopies relies on dichotomous test assumptions, using prevalence, sensitivity, and specificity to determine negative predictive value. However, bronchoscopy is a multidisease test, raising concerns about the accuracy of dichotomous methods. RESEARCH QUESTION: By how much does calculating pCA using a dichotomous approach (pCAdichotomous) underestimate the true pCA when applied to multidisease tests like bronchoscopy for the diagnosis of PPL? METHODS: In this meta-analysis of cohort studies involving radial endobronchial ultrasound for PPL, Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed, constructing 2 × 2 contingency tables for calculating pCAdichotomous. For the multidisease test approach, 3 × 3 contingency tables for calculating probability of malignancy for a test that can have multiple test different categories of results and can diagnose multiple diseases (pCAmultidisease) using the likelihood ratio (LR) method for nondiagnostic results (LR(T0)) was used. Observed malignancy rates in patients with nondiagnostic results were compared with pCAdichotomous and pCAmultidisease. RESULTS: In 46 studies (7,506 patients), malignancy was the underlying diagnosis in 76%, another specific disease in 13%, and nonspecific fibrosis or scar in 10%. The percentage of patients with nondiagnostic results who had malignancy matched pCAmultidisease across all studies. In contrast, pCAdichotomous consistently underestimated cancer risk (median difference, 0.12; interquartile range, 0.06-0.23), particularly in studies with a higher prevalence of nonmalignant disease. The pooled LR(T0) was 0.46 (95% CI, 0.40-0.52; I2 = 76%; P < .001) and correlated with the prevalence of nonmalignant diseases (P = .001). INTERPRETATION: Conventional dichotomous methods for estimating pCA after nondiagnostic bronchoscopies underestimate the likelihood of malignancy. Physicians should opt for the multidisease test approach when interpreting bronchoscopy results.

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OBJECTIVE: This study aims to develop and validate predictive models that assess the risk of leprosy development among contacts, contributing to an enhanced understanding of disease occurrence in this population. METHODS: A cohort of 600 contacts of people with leprosy treated at the National Reference Center for Leprosy and Health Dermatology at the Federal University of Uberlândia (CREDESH/HC-UFU) was followed up between 2002 and 2022. The database was divided into two parts: two-third to construct the disease risk score and one-third to validate this score. Multivariate logistic regression models were used to construct the disease score. RESULTS: Of the four models constructed, model 3, which included the variables anti-phenolic glycolipid I immunoglobulin M positive, absence of Bacillus Calmette-Guérin vaccine scar and age ≥60 years, was considered the best for identifying a higher risk of illness, with a specificity of 89.2%, a positive predictive value of 60% and an accuracy of 78%. CONCLUSIONS: Risk prediction models can contribute to the management of leprosy contacts and the systematisation of contact surveillance protocols.

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BACKGROUND: Dynamic arterial elastance (Eadyn) has been investigated for its ability to predict hypotension during the weaning of vasopressors. Our study focused on assessing Eadyn's performance in the context of critically ill adult patients admitted to the intensive care unit, regardless of diagnosis. MAIN BODY: Our study was conducted in accordance with the Preferred Reported Items for Systematic Reviews and Meta-Analysis checklist. The protocol was registered in PROSPERO (CRD42023421462) on May 26, 2023. We included prospective observational studies from the MEDLINE and Embase databases through May 2023. Five studies involving 183 patients were included in the quantitative analysis. We extracted data related to patient clinical characteristics, and information about Eadyn measurement methods, results, and norepinephrine dose. Most patients (76%) were diagnosed with septic shock, while the remaining patients required norepinephrine for other reasons. The average pressure responsiveness rate was 36.20%. The synthesized results yielded an area under the curve of 0.85, with a sensitivity of 0.87 (95% CI 0.74-0.93), specificity of 0.76 (95% CI 0.68-0.83), and diagnostic odds ratio of 19.07 (95% CI 8.47-42.92). Subgroup analyses indicated no variations in the Eadyn based on norepinephrine dosage, the Eadyn measurement device, or the Eadyn diagnostic cutoff to predict cessation of vasopressor support. CONCLUSIONS: Eadyn, evaluated through subgroup analyses, demonstrated good predictive ability for the discontinuation of vasopressor support in critically ill patients.

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Artificial intelligence (AI) systems are already being used in various healthcare areas. Similarly, they can offer many advantages in hospital emergency services. The objective of this work is to demonstrate that through the novel use of AI, a trained system can be developed to detect patients at potential risk of infection in a new pandemic more quickly than standardized triage systems. This identification would occur in the emergency department, thus allowing for the early implementation of organizational preventive measures to block the chain of transmission. MATERIALS AND METHODS: In this study, we propose the use of a machine learning system in emergency department triage during pandemics to detect patients at the highest risk of death and infection using the COVID-19 era as an example, where rapid decision making and comprehensive support have becoming increasingly crucial. All patients who consecutively presented to the emergency department were included, and more than 89 variables were automatically analyzed using the extreme gradient boosting (XGB) algorithm. RESULTS: The XGB system demonstrated the highest balanced accuracy at 91.61%. Additionally, it obtained results more quickly than traditional triage systems. The variables that most influenced mortality prediction were procalcitonin level, age, and oxygen saturation, followed by lactate dehydrogenase (LDH) level, C-reactive protein, the presence of interstitial infiltrates on chest X-ray, and D-dimer. Our system also identified the importance of oxygen therapy in these patients. CONCLUSIONS: These results highlight that XGB is a useful and novel tool in triage systems for guiding the care pathway in future pandemics, thus following the example set by the well-known COVID-19 pandemic.

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OBJECTIVES: The objective was to estimate the probability that finding a Streptococcus pyogenes (Group A Streptococcus) in a throat swab in a patient with a sore throat reflects the aetiology. We also investigated to what extent this is influenced by age, carrier rates of S. pyogenes and climate zone. METHODS: We conducted a comprehensive search of Medline and Scopus up until October 2023 for case-control studies reporting the prevalence of S. pyogenes in patients with a sore throat and healthy controls. We only included studies with separate data for children and adults. We used the positive and negative etiologic predictive values (P-EPV and N-EPV) to estimate the probability of a link between a sore throat and a finding of S. pyogenes. RESULTS: We included 15 studies in our meta-analysis. The overall P-EPV for children and adults were 63% (49-74%) and 92% (87-95%), respectively. The P-EPV rose to 83% (64-93%) for children and 94% (90-97%) for adults when only patients with 3-4 Centor criteria were included. The overall N-EPV was 97% (96-98%) for children and 96% (95-97%) for adults. CONCLUSION: Detecting S. pyogenes in adult patients with an uncomplicated acute sore throat is useful to rule in S. pyogenes as the likely aetiologic agent. The P-EPV significantly increased for children when those with 3-4 Centor criteria were selected. A negative throat swab is always useful for both children and adults to rule out S. pyogenes as the cause of sore throat.

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Background/Aim: A cutoff value for lymph node diameter in colorectal cancer lymph node metastases has not been established. This prospective study aimed to investigate the direct association between swollen lymph nodes identified on preoperative computed tomography (CT) and pathological findings and proposed a cutoff value. Patients and Methods: We enrolled patients scheduled to undergo curative surgery with lymph node dissection for colorectal adenocarcinoma who underwent preoperative contrast-enhanced CT and had swollen lymph nodes ≥7 mm in diameter. Two gastrointestinal surgeons intraoperatively identified the target lymph nodes to assess the association between lymph node diameter and pathological findings. The diagnostic performance for lymph node metastasis was determined using multi-level logistic modelling. Results: A total of 109 patients were enrolled, and 225 swollen lymph nodes were pathologically evaluated. Using a cutoff value of ≥9 mm for the short diameter, the positive and negative predictive values, sensitivity, and specificity were 100.0% (99.6%-100.0%), 99.9% (99.1%-100.0%), 62.0% (45.6%-76.0%), and 84.9% (67.0%-94.0%), respectively. Conclusion: The cutoff value for improving the positive predictive value for the preoperative lymph node metastasis diagnosis in colorectal cancer patients should be at least 9 mm in diameter.

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BACKGROUND: Early identification of large vessel occlusion (LVO) in patients with ischemic stroke is crucial for timely interventions. We propose a machine learning-based algorithm (JLK-CTL) that uses handcrafted features from noncontrast computed tomography to predict LVO. METHODS: We included patients with ischemic stroke who underwent concurrent noncontrast computed tomography and computed tomography angiography in seven hospitals. Patients from 5 of these hospitals, admitted between May 2011 and March 2015, were randomly divided into training and internal validation (9:1 ratio). Those from the remaining 2 hospitals, admitted between March 2021 and September 2021, were designated for external validation. From each noncontrast computed tomography scan, we extracted differences in volume, tissue density, and Hounsfield unit distribution between bihemispheric regions (striatocapsular, insula, M1-M3, and M4-M6, modified from the Alberta Stroke Program Early Computed Tomography Score). A deep learning algorithm was used to incorporate clot signs as an additional feature. Machine learning models, including ExtraTrees, random forest, extreme gradient boosting, support vector machine, and multilayer perceptron, as well as a deep learning model, were trained and evaluated. Additionally, we assessed the models' performance after incorporating the National Institutes of Health Stroke Scale scores as an additional feature. RESULTS: Among 2919 patients, 83 were excluded. Across the training (n=2463), internal validation (n=275), and external validation (n=95) datasets, the mean ages were 68.5±12.4, 67.6±13.8, and 67.9±13.6 years, respectively. The proportions of men were 57%, 53%, and 59%, with LVO prevalences of 17.0%, 16.4%, and 26.3%, respectively. In the external validation, the ExtraTrees model achieved a robust area under the curve of 0.888 (95% CI, 0.850-0.925), with a sensitivity of 80.1% (95% CI, 72.0-88.1) and a specificity of 88.6% (95% CI, 84.7-92.5). Adding the National Institutes of Health Stroke Scale score to the ExtraTrees model increased sensitivity (from 80.1% to 92.1%) while maintaining specificity. CONCLUSIONS: Our algorithm provides reliable predictions of LVO using noncontrast computed tomography. By enabling early LVO identification, our algorithm has the potential to expedite the stroke workflow.

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Purpose: Hypertension is an important risk factor in cardio-epidemiological research, but data quality remains a concern. We validated different registry-based definitions of hypertension. Patients and Methods: The cohort included all first-time responders of the Danish National Health Surveys (2010, 2013, or 2017). Prescription-defined hypertension was defined as ≥1 or ≥2 filled prescriptions of antihypertensive specific drugs in ≥1 or ≥2 different antihypertensive drug classes within 90, 180, or 365 days before survey response. Hospital-diagnosed hypertension was defined from hypertension diagnoses within five years before the survey response. Considering self-reported hypertension as the reference, we calculated the positive predictive value (PPV), the negative predictive value (NVP), the sensitivity, and the specificity of prescription-defined and hospital-diagnosed hypertension. Results: Among 442,490 survey responders, 127,247 (29%) had self-reported hypertension. For prescription-defined hypertension with 365-day lookback, the PPV was highest for ≥2 prescriptions in ≥2 drug classes (94%) and lowest for ≥1 prescription in ≥1 drug class (85%). The NPV was highest for ≥1 prescription in ≥2 drug classes (94%) and lowest for ≥1 prescription in ≥2 drug classes (80%). The sensitivity was highest for ≥1 prescription in ≥1 drug class (79%) and lowest for ≥2 prescriptions in ≥2 drug classes (30%). The specificity was ≥94% for all algorithms. The PPV and specificity did not change noteworthy with length of lookback period, whereas the NPV and the sensitivity generally were higher for longer lookback. The algorithm ≥1 prescription in ≥2 drug classes with 365-day lookback was among the best balanced across all measures of validity (PPV=88%, NPV=94%, sensitivity=75%, specificity=96%). For hospital-diagnosed hypertension, the PPV was 90%, the NPV was 76%, the sensitivity was 22%, and the specificity was 99%. Conclusion: Compared with self-reported hypertension, the algorithms for prescription-defined and hospital-diagnosed hypertension had high predictive values and specificity, but low sensitivity.

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BACKGROUND: Atrial fibrillation (AF) is often asymptomatic and undiagnosed. As AF and hypertension often coexist, opportunistic AF detection during routine automated blood pressure (BP) measurement appears to be an attractive screening method. METHODS: A systematic literature search was conducted to identify studies assessing the diagnostic test accuracy of office, home, or 24-hour ambulatory BP measuring devices with AF detection algorithms versus reference electrocardiography. Analyses were performed per participant (AF status based on several BP readings; most office/home devices) or per reading (AF status based on individual readings; all ambulatory devices). A meta-analysis stratified by device type (office/home/ambulatory) was conducted to calculate pooled measures of diagnostic accuracy. Sensitivity/meta-regression analyses were also performed. RESULTS: Among 3096 records initially retrieved, 23 diagnostic test accuracy studies were included. Data derived from 11 093 individuals (weighted age 69 years, males 56%, hypertensives 79%, diabetics 24%, and AF prevalence 17%) indicated a pooled sensitivity 0.97 (95% CI, 0.92-0.99), specificity 0.93 (95% CI, 0.90-0.95), and accuracy 0.93 (95% CI, 0.89-0.95), with generally consistent results using office, home, or ambulatory BP devices (slightly lower specificity with the latter). The positive and negative predictive values were 0.70 (95% CI, 0.60-0.80) and 0.99 (95% CI, 0.98-1.00), respectively. Sensitivity analyses indicated lower specificity in studies implementing reading versus participant analyses. Most studies presented a low risk of bias and minor applicability concerns. CONCLUSIONS: There is considerable and consistent evidence suggesting high diagnostic accuracy of AF detection algorithms implemented in automated BP monitors during routine BP measurements in and out of the office. AF diagnosis requires verification (electrocardiography) before treatment is administered.

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BACKGROUND: This study aimed to evaluate the association between initial fibrinogen levels and massive transfusion (MT) in emergency department (ED) patients with primary postpartum hemorrhage (PPH). METHODS: This retrospective study was conducted in the ED of a university-affiliated, tertiary referral center from January 2004 to August 2023. Patients were divided into two groups: the MT group, which included those who received a transfusion of 10 or more units of packed red blood cells within the first 24 h, and the Non-MT group. RESULTS: Out of the 364 patients included in the study, 97 (26.6%) required MT. Fibrinogen, shock index, and lactate were independently associated with MT (odds ratio [OR] 0.987; 95% confidence interval [CI] 0.983-0.991; p < 0.001, OR 7.277; 95% CI 1.856-28.535; p = 0.004, and OR 1.261; 95% CI 1.021-1.557; p = 0.031, respectively). The area under the receiver operating characteristic curve for fibrinogen, shock index, and lactate in predicting MT was 0.871 (95% CI 0.832-0.904; p < 0.001), 0.821 (95% CI 0.778-0.859; p < 0.001), and 0.784 (95% CI 0.738-0.825; p < 0.001), respectively. When the cutoff value of fibrinogen was 400 mg/dL, both the sensitivity and negative predictive values for predicting MT were 100.0%. When the cutoff value of fibrinogen was 100 mg/dL, the specificity and positive predictive values were 91.8% and 70.7%, respectively. CONCLUSION: The initial fibrinogen levels were independently associated with the need for MT in ED patients with primary PPH.

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IntroducciónLa guía clínica para el manejo de la sepsis recomienda usar muestras de sangre arterial para el control glucémico. Un estudio multicéntrico en 86 unidades de cuidados intensivos españolas reveló que el 85,4% de estas utilizaban punción capilar.ObjetivoAnalizar la fiabilidad de la glucemia comparando diferentes muestras sanguíneas (arterial, venosa, capilar) e instrumentos (glucómetros, gasómetros, laboratorio central). Secundariamente, estimar el efecto de variables confusoras y el rendimiento de los instrumentos de medición determinados por las diferentes normas de calidad.MetodologíaRevisión sistemática y metanálisis con búsqueda en las bases de datos PubMed, CINAHL y Embase en septiembre-2021 y septiembre-2022, sin límites temporales ni idiomáticos. Fuentes de literatura gris: DART-Europe, OpenGrey y Google Académico. Resultados resumidos mediante síntesis cualitativa (descripción de resultados, características de los estudios) y cuantitativa (metanálisis para evaluar la diferencia de medias estandarizadas). Calidad metodológica de artículos evaluada con Quality Assessment of Diagnostic Accuracy Studies-2. Protocolo: https://osf.io/ DOI 10.17605/OSF.IO/T8KYP.ResultadosSe incluyeron un total de 32 artículos y 5.451 pacientes. No se obtuvieron discrepancias entre muestras arteriales con glucómetro vs. laboratorio (sesgo [IC95%]: 0,01 [−0,12 a 0,14] mg/dL). En cambio, muestras arteriales con gasómetro sí sobreestimaron de forma significativa (sesgo [IC95%]: 0,12 [0,01 a 0,24] mg/dL). La misma tendencia presentan capilares con glucómetro, aunque no de forma significativa (sesgo [IC95%]: 0,07 [−0,02 a 0,15] mg/dL). Hay discrepancia entre los estudios sobre el efecto del hematocrito y el equilibrio ácido-base. El mayor consenso se da en la poca concordancia del glucómetro con muestras capilares vs. laboratorio en presencia de shock y soporte vasopresor, situación de fallo renal o durante el tratamiento con vitamina C.Conclusiones... (AU)

IntroductionThe clinical guideline for the management of sepsis recommends using arterial blood samples for glycaemic control. A multicentre study in 86 Spanish intensive care units revealed that 85.4% of these used capillary puncture.ObjectiveTo analyse the reliability of glycaemia by comparing different blood samples (arterial, venous, capillary) and instruments (glucometers, gasometers, central laboratory). Secondarily, to estimate the effect of confounding variables and the performance of measuring instruments as determined by different quality standards.MethodologySystematic review and meta-analysis with search in PubMed, CINAHL and Embase databases in September-2021 and September-2022, with no time or language limits. Grey literature sources: DART-Europe, OpenGrey and Google Scholar. Results summarised by qualitative (description of results, study characteristics) and quantitative (meta-analysis to assess standardised mean difference) synthesis. Methodological quality of articles assessed with Quality Assessment of Diagnostic Accuracy Studies-2. Protocol: https://osf.io/ DOI 10.17605/OSF.IO/T8KYP.ResultsA total of 32 articles and 5451 patients were included. No discrepancies were obtained between arterial glucometer vs. laboratory samples (bias [95%CI]: 0.01 [−0.12 to 0.14] mg/dL). In contrast, arterial samples with a gasometer did significantly overestimate (bias [95%CI]: 0.12 [0.01 to 0.24] mg/dL). The same trend is seen in capillaries with a glucometer, although not significantly (bias [95%CI]: 0.07 [−0.02 to 0.15] mg/dL). There is discrepancy between studies on the effect of haematocrit and acid-base balance. The greatest consensus is on the poor agreement of glucometer with capillary vs. laboratory samples in the presence of shock and vasopressor support, renal failure or during vitamin C treatment.Conclusions... (AU)

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IntroducciónLa guía clínica para el manejo de la sepsis recomienda usar muestras de sangre arterial para el control glucémico. Un estudio multicéntrico en 86 unidades de cuidados intensivos españolas reveló que el 85,4% de estas utilizaban punción capilar.ObjetivoAnalizar la fiabilidad de la glucemia comparando diferentes muestras sanguíneas (arterial, venosa, capilar) e instrumentos (glucómetros, gasómetros, laboratorio central). Secundariamente, estimar el efecto de variables confusoras y el rendimiento de los instrumentos de medición determinados por las diferentes normas de calidad.MetodologíaRevisión sistemática y metanálisis con búsqueda en las bases de datos PubMed, CINAHL y Embase en septiembre-2021 y septiembre-2022, sin límites temporales ni idiomáticos. Fuentes de literatura gris: DART-Europe, OpenGrey y Google Académico. Resultados resumidos mediante síntesis cualitativa (descripción de resultados, características de los estudios) y cuantitativa (metanálisis para evaluar la diferencia de medias estandarizadas). Calidad metodológica de artículos evaluada con Quality Assessment of Diagnostic Accuracy Studies-2. Protocolo: https://osf.io/ DOI 10.17605/OSF.IO/T8KYP.ResultadosSe incluyeron un total de 32 artículos y 5.451 pacientes. No se obtuvieron discrepancias entre muestras arteriales con glucómetro vs. laboratorio (sesgo [IC95%]: 0,01 [−0,12 a 0,14] mg/dL). En cambio, muestras arteriales con gasómetro sí sobreestimaron de forma significativa (sesgo [IC95%]: 0,12 [0,01 a 0,24] mg/dL). La misma tendencia presentan capilares con glucómetro, aunque no de forma significativa (sesgo [IC95%]: 0,07 [−0,02 a 0,15] mg/dL). Hay discrepancia entre los estudios sobre el efecto del hematocrito y el equilibrio ácido-base. El mayor consenso se da en la poca concordancia del glucómetro con muestras capilares vs. laboratorio en presencia de shock y soporte vasopresor, situación de fallo renal o durante el tratamiento con vitamina C.Conclusiones... (AU)

IntroductionThe clinical guideline for the management of sepsis recommends using arterial blood samples for glycaemic control. A multicentre study in 86 Spanish intensive care units revealed that 85.4% of these used capillary puncture.ObjectiveTo analyse the reliability of glycaemia by comparing different blood samples (arterial, venous, capillary) and instruments (glucometers, gasometers, central laboratory). Secondarily, to estimate the effect of confounding variables and the performance of measuring instruments as determined by different quality standards.MethodologySystematic review and meta-analysis with search in PubMed, CINAHL and Embase databases in September-2021 and September-2022, with no time or language limits. Grey literature sources: DART-Europe, OpenGrey and Google Scholar. Results summarised by qualitative (description of results, study characteristics) and quantitative (meta-analysis to assess standardised mean difference) synthesis. Methodological quality of articles assessed with Quality Assessment of Diagnostic Accuracy Studies-2. Protocol: https://osf.io/ DOI 10.17605/OSF.IO/T8KYP.ResultsA total of 32 articles and 5451 patients were included. No discrepancies were obtained between arterial glucometer vs. laboratory samples (bias [95%CI]: 0.01 [−0.12 to 0.14] mg/dL). In contrast, arterial samples with a gasometer did significantly overestimate (bias [95%CI]: 0.12 [0.01 to 0.24] mg/dL). The same trend is seen in capillaries with a glucometer, although not significantly (bias [95%CI]: 0.07 [−0.02 to 0.15] mg/dL). There is discrepancy between studies on the effect of haematocrit and acid-base balance. The greatest consensus is on the poor agreement of glucometer with capillary vs. laboratory samples in the presence of shock and vasopressor support, renal failure or during vitamin C treatment.Conclusions... (AU)

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BACKGROUND: Efficiently identifying patients with human immunodeficiency virus (HIV) using administrative health care data (e.g., claims) can facilitate research on their quality of care and health outcomes. No prior study has validated the use of only ICD-10-CM HIV diagnosis codes to identify patients with HIV. METHODS: We validated HIV diagnosis codes among women enrolled in a large U.S. integrated health care system during 2010-2020. We examined HIV diagnosis code-based algorithms that varied by type, frequency, and timing of the codes in patients' claims data. We calculated the positive predictive values (PPVs) and 95% confidence intervals (CIs) of the algorithms using a medical record-confirmed diagnosis of HIV as the gold standard. RESULTS: A total of 272 women with ≥ 1 HIV diagnosis code in the administrative claims data were identified and medical records were reviewed for all 272 women. The PPV of an algorithm classifying women as having HIV as of the first HIV diagnosis code during the observation period was 80.5% (95% CI: 75.4-84.8%), and it was 93.9% (95% CI: 90.0-96.3%) as of the second. Little additional increase in PPV was observed when a third code was required. The PPV of an algorithm based on ICD-10-CM-era codes was similar to one based on ICD-9-CM-era codes. CONCLUSION: If the accuracy measure of greatest interest is PPV, our findings suggest that use of ≥ 2 HIV diagnosis codes to identify patients with HIV may perform well. However, health care coding practices may vary across settings, which may impact generalizability of our results.

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