Chest Pain in Primary Care: A Systematic Review of Risk Stratification Tools to Rule Out Acute Coronary Syndrome.

PURPOSE: Chest pain frequently poses a diagnostic challenge for general practitioners (GPs). Utilizing risk stratification tools might help GPs to rule out acute coronary syndrome (ACS) and make appropriate referral decisions. We conducted a systematic review of studies evaluating risk stratification tools for chest pain in primary care settings, both with and without troponin assays. Our aims were to assess the performance of tools for ruling out ACS and to provide a comprehensive review of the current evidence. METHODS: We searched PubMed and Embase for articles up to October 9, 2023 concerning adult patients with acute chest pain in primary care settings, for whom risk stratification tools (clinical decision rules [CDRs] and/or single biomarker tests) were used. To identify eligible studies, a combination of active learning and backward snowballing was applied. Screening, data extraction, and quality assessment (following the Quality Assessment of Diagnostic Accuracy Studies-2 tool) were performed independently by 2 researchers. RESULTS: Of the 1,204 studies screened, 14 were included in the final review. Nine studies validated 7 different CDRs without troponin. Sensitivities ranged from 75.0% to 97.0%, and negative predictive values (NPV) ranged from 82.4% to 99.7%. None of the CDRs outperformed the unaided judgment of GP's. Five studies reported on strategies using troponin measurements. Studies using high-sensitivity troponin showed highest diagnostic accuracy with sensitivity 83.3% to 100% and NPV 98.8% to 100%. CONCLUSION: Clinical decision rules without troponin and the use of conventional troponin showed insufficient sensitivity to rule out ACS in primary care and are not recommended as standalone tools. High-sensitivity troponin strategies are promising, but studies are limited. Further prospective validation in primary care is needed before implementation.

Do Thresholds for Invasive Ventilation in Hypoxemic Respiratory Failure Exist? A Cohort Study.

Rationale: Invasive ventilation is a significant event for patients with respiratory failure. Physiologic thresholds standardize the use of invasive ventilation in clinical trials, but it is unknown whether thresholds prompt invasive ventilation in clinical practice. Objectives: To measure, in patients with hypoxemic respiratory failure, the probability of invasive ventilation within 3 hours after meeting physiologic thresholds. Methods: We studied patients admitted to intensive care receiving FiO2 of 0.4 or more via nonrebreather mask, noninvasive positive pressure ventilation, or high-flow nasal cannula, using data from the Medical Information Mart for Intensive Care (MIMIC)-IV database (2008-2019) and the Amsterdam University Medical Centers Database (AmsterdamUMCdb) (2003-2016). We evaluated 17 thresholds, including the ratio of arterial to inspired oxygen, the ratio of saturation to inspired oxygen ratio, composite scores, and criteria from randomized trials. We report the probability of invasive ventilation within 3 hours of meeting each threshold and its association with covariates using odds ratios (ORs) and 95% credible intervals (CrIs). Measurements and Main Results: We studied 4,726 patients (3,365 from MIMIC, 1,361 from AmsterdamUMCdb). Invasive ventilation occurred in 28% (1,320). In MIMIC, the highest probability of invasive ventilation within 3 hours of meeting a threshold was 20%, after meeting prespecified neurologic or respiratory criteria while on vasopressors, and 19%, after a ratio of arterial to inspired oxygen of <80 mm Hg. In AmsterdamUMCdb, the highest probability was 34%, after vasopressor initiation, and 25%, after a ratio of saturation to inspired oxygen of <90. The probability after meeting the threshold from randomized trials was 9% (MIMIC) and 13% (AmsterdamUMCdb). In MIMIC, a race/ethnicity of Black (OR, 0.75; 95% CrI, 0.57-0.96) or Asian (OR, 0.6; 95% CrI, 0.35-0.95) compared with White was associated with decreased probability of invasive ventilation after meeting a threshold. Conclusions: The probability of invasive ventilation within 3 hours of meeting physiologic thresholds was low and associated with patient race/ethnicity.

Factors predicting long-term outcomes following physiotherapy in patients with subacromial pain syndrome: a secondary analysis.

BACKGROUND: Although patients with shoulder complaints are frequently referred to physiotherapy, putative predictive factors for outcomes are still unclear. In this regard, only a limited amount of scientific data for patients with subacromial pain syndrome exist, with inconsistent results. An improved knowledge about the ability of baseline variables to predict outcomes could help patients make informed treatment decisions, prevent them from receiving ineffective treatments, and minimize the risk of developing chronic pain. AIM: The aims of this secondary longitudinal analysis are threefold: First, to investigate baseline differences between patients with and without successful long-term outcomes following physiotherapy. Second, to compare the predictive ability of two sets of putative predictive variables on outcomes, one based on the literature and one based on the data of the original trial. Third, to explore the contribution of short-term follow-up data to predictive models. METHODS: Differences between responders and nonresponders were calculated. The predictive ability of variables defined through literature and of variables based on the Akaike Information Criterion (AIC) from the original trial dataset on the Shoulder Pain and Disability Index and the Patients' Global Impression of Change at the one-year follow-up were analyzed. To test the robustness of the results, different statistical models were used. To investigate the contribution of follow-up data to prediction, short-term data were included in the analyses. RESULTS: A sample of 87 patients with subacromial pain syndrome was analyzed. 77% (n = 67) of these participants were classified as responders. Higher expectations and short-term change scores were positive, and higher fear avoidance beliefs, greater baseline disability and pain levels were negative predictors of long-term outcomes in patients with subacromial pain syndrome. CONCLUSIONS: Although our results are in line with previous research and support the use of clinical factors for prediction, our findings suggest that psychological factors, especially patient expectations and fear avoidance beliefs, also contribute to long-term outcomes and should therefore be considered in the clinical context and further research. However, the hypotheses and recommendations generated from our results need to be confirmed in further studies due to their explorative nature. TRIAL REGISTRATION: The original trial was registered at Current Controlled Trials under the trial registration number ISRCTN86900354 on March 17, 2010.

Patient outcomes following medical emergency team review on general wards: Development of predictive models.

AIM: To develop and internally validate risk prediction models for subsequent clinical deterioration, unplanned ICU admission and death among ward patients following medical emergency team (MET) review. DESIGN: A retrospective cohort study of 1500 patients who remained on a general ward following MET review at an Australian quaternary hospital. METHOD: Logistic regression was used to model (1) subsequent MET review within 48 h, (2) unplanned ICU admission within 48 h and (3) hospital mortality. Models included demographic, clinical and illness severity variables. Model performance was evaluated using discrimination and calibration with optimism-corrected bootstrapped estimates. Findings are reported using the TRIPOD guideline for multivariable prediction models for prognosis or diagnosis. There was no patient or public involvement in the development and conduct of this study. RESULTS: Within 48 h of index MET review, 8.3% (n = 125) of patients had a subsequent MET review, 7.2% (n = 108) had an unplanned ICU admission and in-hospital mortality was 16% (n = 240). From clinically preselected predictors, models retained age, sex, comorbidity, resuscitation limitation, acuity-dependency profile, MET activation triggers and whether the patient was within 24 h of hospital admission, ICU discharge or surgery. Models for subsequent MET review, unplanned ICU admission, and death had adequate accuracy in development and bootstrapped validation samples. CONCLUSION: Patients requiring MET review demonstrate complex clinical characteristics and the majority remain on the ward after review for deterioration. A risk score could be used to identify patients at risk of poor outcomes after MET review and support general ward clinical decision-making. RELEVANCE TO CLINICAL PRACTICE: Our risk calculator estimates risk for patient outcomes following MET review using clinical data available at the bedside. Future validation and implementation could support evidence-informed team communication and patient placement decisions.

[Predictive effect of the dual-parametric MRI modified maximum diameter of the lesions with PI-RADS 4 and 5 on the clinically significant prostate cancer].

OBJECTIVE: To assess the rationality of the maximum lesion diameter of 15 mm in prostate imaging reporting and data system (PI-RADS) as a criterion for upgrading a lesion from category 4 to 5 and improve it to enhance the prediction of clinically significant prostate cancer (csPCa). METHODS: In this study, the patients who underwent prostate magnetic resonance imaging (MRI) and prostate biopsy at Peking University First Hospital from 2019 to 2022 as a development cohort, and the patients in 2023 as a validation cohort were reviewed. The localization and maximum diameter of the lesion were fully evaluated. The area under the curve (AUC) and the cut-off value of the maximum diameter of the lesion to predict the detection of csPCa were calculated from the receiver operating characteristics (ROC) curve. Confounding factors were reduced by propensity score matching (PSM). Diagnostic efficacy was compared in the validation cohort. RESULTS: Of the 589 patients in the development cohort, 358 (60.8%) lesions were located in the peripheral zone and 231 (39.2%) were located in the transition zone, and 496 (84.2%) patients detected csPCa. The median diameter of the lesions in the peripheral zone was smaller than that in the transition zone (14 mm vs. 19 mm, P < 0.001). In the ROC analysis of the maximal diameter on the csPCa prediction, there was no statistically significant difference between the peri-pheral zone (AUC=0.709) and the transition zone (AUC=0.673, P=0.585), and the cut-off values were calculated to be 11.5 mm for the peripheral zone and 16.5 mm for the migrating zone. By calcula-ting the Youden index for the cut-off values in the validation cohort, we found that the categorisation by lesion location led to better predictive results. Finally, the net reclassification index (NRI) was 0.170. CONCLUSION: 15 mm as a criterion for upgrading the PI-RADS score from 4 to 5 is reasonable but too general. The cut-off value for peripheral zone lesions is smaller than that in transitional zone. In the future consideration could be given to setting separate cut-off values for lesions in different locations.

Validation of a prediction model for post-chemotherapy fibrosis in nonseminoma patients.

OBJECTIVE: To validate Vergouwe's prediction model using the Swedish and Norwegian Testicular Cancer Group (SWENOTECA) RETROP database and to define its clinical utility. MATERIALS AND METHODS: Vergouwe's prediction model for benign histopathology in post-chemotherapy retroperitoneal lymph node dissection (PC-RPLND) uses the following variables: presence of teratoma in orchiectomy specimen; pre-chemotherapy level of alpha-fetoprotein; ß-Human chorionic gonadotropin and lactate dehydrogenase; and lymph node size pre- and post-chemotherapy. Our validation cohort consisted of patients included in RETROP, a prospective population-based database of patients in Sweden and Norway with metastatic nonseminoma, who underwent PC-RPLND in the period 2007-2014. Discrimination and calibration analyses were used to validate Vergouwe's prediction model results. Calibration plots were created and a Hosmer-Lemeshow test was calculated. Clinical utility, expressed as opt-out net benefit (NBopt-out ), was analysed using decision curve analysis. RESULTS: Overall, 284 patients were included in the analysis, of whom 130 (46%) had benign histology after PC-RPLND. Discrimination analysis showed good reproducibility, with an area under the receiver-operating characteristic curve (AUC) of 0.82 (95% confidence interval 0.77-0.87) compared to Vergouwe's prediction model (AUC between 0.77 and 0.84). Calibration was acceptable with no recalibration. Using a prediction threshold of 70% for benign histopathology, NBopt-out was 0.098. Using the model and this threshold, 61 patients would have been spared surgery. However, only 51 of 61 were correctly classified as benign. CONCLUSIONS: The model was externally validated with good reproducibility. In a clinical setting, the model may identify patients with a high chance of benign histopathology, thereby sparing patients of surgery. However, meticulous follow-up is required.

Development and internal validation of a screening tool for chronic prostatitis (S-CP).

PURPOSE: We developed a simple self-checkable screening tool for chronic prostatitis (S-CP) and internally validated it to encourage men (in the general population) with possible chronic prostatitis to consult urologists. METHODS: The expert panel proposed the S-CP, which comprises three domains: Area of pain or discomfort (6 components), accompanying Symptom (6 components), and Trigger for symptom flares (4 components). We employed logistic regression to predict chronic prostatitis prevalence with the S-CP. We evaluated the predictive performance using data from a representative national survey of Japanese men aged 20 to 84. We calculated the optimism-adjusted area under the curve using bootstrapping. We assessed sensitivity/specificity, likelihood ratio, and predictive value for each cutoff of the S-CP. RESULTS: Data were collected for 5,010 men-71 (1.4%) had a chronic prostatitis diagnosis. The apparent and adjusted area under the curve for the S-CP was 0.765 [95% confidence interval (CI) 0.702, 0.829] and 0.761 (0.696, 0.819), respectively. When the cutoff was two of the three domains being positive, sensitivity and specificity were 62.0% (95% CI 49.7, 73.2) and 85.4% (95% CI 84.4, 86.4), respectively. The positive/negative likelihood ratios were 4.2 (95% CI 3.5, 5.2) and 0.45 (95% CI 0.33, 0.60), respectively. The positive/negative predictive values were 5.7 (95% CI 4.2, 7.6) and 99.4 (95% CI 99.1, 99.6), respectively. CONCLUSION: The reasonable predictive performance of the S-CP indicated that patients (in the general population) with chronic prostatitis were screened as a first step. Further research would develop another tool for diagnostic support in actual clinical settings.

Using a CT-based scale to evaluate disease extension and the resectability of locally advanced thyroid cancer.

OBJECTIVES: To establish a computed tomography (CT)-based scale to evaluate the resectability of locally advanced thyroid cancer. METHODS: This twin-centre retrospective study included 95 locally advanced thyroid cancer patients from the 1st centre as the training cohort and 31 patients from the 2nd centre as the testing cohort, who were categorised into the resectable and unresectable groups. Three radiologists scored the CT scans of each patient by evaluating the extension to the recurrent laryngeal nerve (RLN), trachea, oesophagus, artery, vein, soft tissue, and larynx. A 14-score scale (including all comprised structures) and a 12-score scale (excluding larynx) were developed. Receiver-operating characteristic (ROC) analysis was used to evaluate the performance of the scales. Stratified fivefold cross-validation and external verification were used to validate the scale. RESULTS: In the training cohort, compromised RLN (p < 0.001), trachea (p = 0.001), oesophagus (p = 0.002), artery (p < 0.001), vein (p = 0.005), and soft tissue (p < 0.001) were predictors for unresectability, while compromised larynx (p = 0.283) was not. The 12-score scale (AUC = 0.882, 95%CI: 0.812-0.952) was not inferior to the 14-score scale (AUC = 0.891, 95%CI: 0.823-0.960). In subgroup analysis, the AUCs of the 12-score scale were 0.826 for treatment-naïve patients and 0.976 for patients with prior surgery. The 12-score scale was further validated with a fivefold cross-validation analysis, with an overall accuracy of 78.9-89.4%. Finally, external validation using the testing cohort showed an AUC of 0.875. CONCLUSIONS: The researchers built a CT-based 12-score scale to evaluate the resectability of locally advanced thyroid cancer. Validation with a larger sample size is required to confirm the efficacy of the scale. CLINICAL RELEVANCE STATEMENT: This 12-score CT scale would help clinicians evaluate the resectability of locally advanced thyroid cancer. KEY POINTS: • The researchers built a 12-score CT scale (including recurrent laryngeal nerve, trachea, oesophagus, artery, vein, and soft tissue) to evaluate the resectability of locally advanced thyroid cancer. • This scale has the potential to help clinicians make treatment plans for locally advanced thyroid cancer.

Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19.

OBJECTIVES: COVID-19 pandemic seems to be under control. However, despite the vaccines, 5 to 10% of the patients with mild disease develop moderate to critical forms with potential lethal evolution. In addition to assess lung infection spread, chest CT helps to detect complications. Developing a prediction model to identify at-risk patients of worsening from mild COVID-19 combining simple clinical and biological parameters with qualitative or quantitative data using CT would be relevant to organizing optimal patient management. METHODS: Four French hospitals were used for model training and internal validation. External validation was conducted in two independent hospitals. We used easy-to-obtain clinical (age, gender, smoking, symptoms' onset, cardiovascular comorbidities, diabetes, chronic respiratory diseases, immunosuppression) and biological parameters (lymphocytes, CRP) with qualitative or quantitative data (including radiomics) from the initial CT in mild COVID-19 patients. RESULTS: Qualitative CT scan with clinical and biological parameters can predict which patients with an initial mild presentation would develop a moderate to critical form of COVID-19, with a c-index of 0.70 (95% CI 0.63; 0.77). CT scan quantification improved the performance of the prediction up to 0.73 (95% CI 0.67; 0.79) and radiomics up to 0.77 (95% CI 0.71; 0.83). Results were similar in both validation cohorts, considering CT scans with or without injection. CONCLUSION: Adding CT scan quantification or radiomics to simple clinical and biological parameters can better predict which patients with an initial mild COVID-19 would worsen than qualitative analyses alone. This tool could help to the fair use of healthcare resources and to screen patients for potential new drugs to prevent a pejorative evolution of COVID-19. CLINICAL TRIAL REGISTRATION: NCT04481620. CLINICAL RELEVANCE STATEMENT: CT scan quantification or radiomics analysis is superior to qualitative analysis, when used with simple clinical and biological parameters, to determine which patients with an initial mild presentation of COVID-19 would worsen to a moderate to critical form. KEY POINTS: • Qualitative CT scan analyses with simple clinical and biological parameters can predict which patients with an initial mild COVID-19 and respiratory symptoms would worsen with a c-index of 0.70. • Adding CT scan quantification improves the performance of the clinical prediction model to an AUC of 0.73. • Radiomics analyses slightly improve the performance of the model to a c-index of 0.77.

Mechanical ventilation and death in pregnant patients admitted for COVID-19: a prognostic analysis from the Brazilian COVID-19 registry score.

BACKGROUND: The assessment of clinical prognosis of pregnant COVID-19 patients at hospital presentation is challenging, due to physiological adaptations during pregnancy. Our aim was to assess the performance of the ABC2-SPH score to predict in-hospital mortality and mechanical ventilation support in pregnant patients with COVID-19, to assess the frequency of adverse pregnancy outcomes, and characteristics of pregnant women who died. METHODS: This multicenter cohort included consecutive pregnant patients with COVID-19 admitted to the participating hospitals, from April/2020 to March/2022. Primary outcomes were in-hospital mortality and the composite outcome of mechanical ventilation support and in-hospital mortality. Secondary endpoints were pregnancy outcomes. The overall discrimination of the model was presented as the area under the receiver operating characteristic curve (AUROC). Overall performance was assessed using the Brier score. RESULTS: From 350 pregnant patients (median age 30 [interquartile range (25.2, 35.0)] years-old]), 11.1% had hypertensive disorders, 19.7% required mechanical ventilation support and 6.0% died. The AUROC for in-hospital mortality and for the composite outcome were 0.809 (95% IC: 0.641-0.944) and 0.704 (95% IC: 0.617-0.792), respectively, with good overall performance (Brier = 0.0384 and 0.1610, respectively). Calibration was good for the prediction of in-hospital mortality, but poor for the composite outcome. Women who died had a median age 4 years-old higher, higher frequency of hypertensive disorders (38.1% vs. 9.4%, p < 0.001) and obesity (28.6% vs. 10.6%, p = 0.025) than those who were discharged alive, and their newborns had lower birth weight (2000 vs. 2813, p = 0.001) and five-minute Apgar score (3.0 vs. 8.0, p < 0.001). CONCLUSIONS: The ABC2-SPH score had good overall performance for in-hospital mortality and the composite outcome mechanical ventilation and in-hospital mortality. Calibration was good for the prediction of in-hospital mortality, but it was poor for the composite outcome. Therefore, the score may be useful to predict in-hospital mortality in pregnant patients with COVID-19, in addition to clinical judgment. Newborns from women who died had lower birth weight and Apgar score than those who were discharged alive.

Predicting length of stay for acute medical admissions in New Zealand: the MALICE score.

Predicting length of stay (LoS) in hospital can help guide patient placement, facilitate rapid discharge and aid identification of patients at risk of prolonged stay, in whom early multidisciplinary intervention is warranted. We aimed to pilot the applicability of a modified decision aid (MALICE score) for predicting LoS for acute medical admissions at a New Zealand hospital. A prospective pilot study of 220 acute general medical admissions was performed. Clinical records were reviewed and MALICE scores were calculated for each patient and compared with LoS data using the Kruskal-Wallis H test. A statistically significant increase in LoS was seen with rising MALICE scores (H value 26.85, P < 0.001). MALICE scoring could be employed to guide patient placement and identify patients at risk of prolonged stays, though further study of bedside feasibility and applicability is required.

A competing risk predictive model for kidney failure in patients with advanced chronic kidney disease.

BACKGROUND/PURPOSE: Predictive modeling aids in identifying patients at high risk of adverse events. Using routinely collected data, we report a competing risk prediction model for kidney failure. METHODS: A total of 5138 patients with CKD stages 3b-5 were included and randomized into the development and validation cohorts at a ratio of 7:3. The outcome was end-stage kidney disease, defined as the initiation of dialysis or kidney transplantation. All patients were followed-up until December 31, 2020. A Fine and Gray model was applied to estimate the sub-hazard ratio of kidney failure, with death as a competing event. RESULTS: In the development cohort, the mean age was 67.6 ± 13.9 years and 60 % were male. The mean index eGFR and median urinary protein-creatinine ratio (UPCR) were 26.5 ± 12.8 mL/min/1.73 m2 and 1051 mg/g, respectively. The median follow-up duration was 1051 days. The proportion of patients with kidney failure and death was 25.4 % and 14.1 %, respectively. Four models were applied, including eGFR, age, sex, UPCR, systolic and diastolic blood pressure, serum albumin, phosphate, uric acid, haemoglobin, and potassium levels had the best goodness of fit. All models had good discrimination with time-to-event c statistics of 0.89-0.95 in the development cohort and 0.86-0.95 in the validation cohort. The prediction models showed excellent and fairly good calibration at 2 and 5-year risk, respectively. CONCLUSION: Using real-world data, our competing risk model can accurately predict progression to kidney failure over 2 years in patients with advanced CKD.

Establishment of a simplified score for predicting risk during intrahospital transport of critical patients: A prospective cohort study.

AIMS AND OBJECTIVES: To establish a simple score that enables nurses to quickly, conveniently and accurately identify patients whose condition may change during intrahospital transport. BACKGROUND: Critically ill patients may experience various complications during intrahospital transport; therefore, it is important to predict their risk before they leave the emergency department. The existing scoring systems were not developed for this population. DESIGN: A prospective cohort study. METHODS: This study used convenience sampling and continuous enrolment from 1 January, 2019, to 30 June, 2021, and 584 critically ill patients were included. The collected data included vital signs and any condition change during transfer. The STROBE checklist was used. RESULTS: The median age of the modelling group was 74 (62, 83) years; 93 (19.7%) patients were included in the changed group, and 379 (80.3%) were included in the stable group. The five independent model variables (respiration, pulse, oxygen saturation, systolic pressure and consciousness) were statistically significant (p < .05). The above model was simplified based on beta coefficient values, and each variable was assigned 1 point, for a total score of 0-5 points. The AUC of the simplified score in the modelling group was 0.724 (95% CI: 0.682-0.764); the AUC of the simplified score in the validation group (112 patients) was 0.657 (95% CI: 0.566-0.741). CONCLUSIONS: This study preliminarily established a simplified scoring system for the prediction of risk during intrahospital transport from the emergency department to the intensive care unit. It provides emergency nursing staff with a simple assessment tool to quickly, conveniently and accurately identify a patient's transport risk. RELEVANCE TO CLINICAL PRACTICE: This study suggested the importance of strengthening the evaluation of the status of critical patients before intrahospital transport, and a simple score was formed to guide emergency department nurses in evaluating patients.

Concordance between 21-gene recurrence score assay and clinicopathological predictive models in early-breast cancer patients cared for at a cancer center in Colombia.

INTRODUCTION: The genomic-based 21-gene recurrence score assay (21-GRSA) allows to determine the usefulness of adjuvant chemotherapy in patients with luminal-type early breast cancer (LTEBC). Additional predictive models have also been developed, such as Magee equations (ME), the Predict model (PM), and the Tennessee nomogram score (TNS). OBJECTIVE: To evaluate the concordance between 21-GRSA, ME, PM and TNS. METHODS: Patients with unifocal LTEBC and 21-GRSA, ME, PM and TNS results were included. A subgroup analysis of women older than 50 years was carried out. Concordance between the models and 21-GRSA was evaluated using Cohen's kappa index (KI). RESULTS: One-hundred and twenty-two women were included. Concordance between 21-GRSA and ME (KI = 0.35) and PM (KI = 0.24) was fair (p < 0.001). Concordance between 21-GRSA and TNS was inferior (KI = 0.16, p = 0.04). Eighty patients older than 50 years with sufficient data to calculate all three predictive models were included. Concordance was found between the low-risk classification on 21-GRSA and all three combined models in 36/37 patients (negative predictive value of 97.3%). CONCLUSION: 21-GRSA can be omitted in women older than 50 years with LTEBC classified with low risk scores on all three predictive models.

INTRODUCCIÓN: La prueba genómica de recurrencia de 21 genes (PGR21) permite determinar la utilidad de la quimioterapia adyuvante en pacientes con cáncer de mama temprano luminal (CMTL). Se han desarrollado modelos predictivos adicionales, como las ecuaciones de Magee (EM), el modelo Predict (MP) y la puntuación del nomograma de la Universidad de Tennessee (NT). OBJETIVO: Evaluar la concordancia entre PGR21, EM, MP y NT. MÉTODOS: Se incluyeron pacientes con CMTL unifocal y con resultados de PGR21, EM, MP y NT. Se efectuó subanálisis de mujeres mayores de 50 años. La concordancia se evaluó mediante índice kappa de Cohen (IK). RESULTADOS: Se incluyeron 122 mujeres. La concordancia entre PGR21 y EM (IK = 0.35) y MP (IK = 0.24) fue aceptable (p < 0.001); entre PGR21 y NT fue inferior (IK = 0.16, p = 0.04). Se incluyeron 80 pacientes mayores de 50 años con datos suficientes para calcular los tres modelos. Se encontró concordancia entre la clasificación de bajo riesgo mediante PGR21 y los tres modelos combinados en 36/37 pacientes (valor predictivo negativo de 97.3 %). CONCLUSIÓN: Se puede omitir la PGR21 en las mujeres mayores de 50 años con CMTL que se clasifica de bajo riesgo en los tres modelos predictivos.

Application of the pulmonary embolism rule-out criteria (PERC rule) and age-adjusted D-Dimer in patients undergoing computed tomography pulmonary angiography for diagnosis of pulmonary embolism.

Background: Diagnosis of pulmonary embolism (PE) constitutes a challenge for practitioners. Current practice involves use of pre-test probability prediction rules. Several strategies to optimize this process have been explored. Objectives: To explore whether application of the pulmonary embolism rule-out criteria (PERC rule) and age-adjusted D-dimer (DD) would have reduced the number of computed tomography pulmonary angiography (CTPA) examinations performed in patients with suspected PE. Methods: A retrospective cross-sectional study of adult patients taken for CTPA under suspicion of PE in 2018 and 2020. The PERC rule and age-adjusted DD were applied. The number of cases without indications for imaging studies was estimated and the operational characteristics for diagnosis of PE were calculated. Results: 302 patients were included. PE was diagnosed in 29.8%. Only 27.2% of 'not probable' cases according to the Wells criteria had D-dimer assays. Age adjustment would have reduced tomography use by 11.1%, with an AUC of 0.5. The PERC rule would have reduced use by 7%, with an AUC of 0.72. Conclusions: Application of age-adjusted D-dimer and the PERC rule to patients taken for CTPA because of suspected PE seems to reduce the number of indications for the procedure.

Contexto: O diagnóstico de embolia pulmonar (EP) representa um desafio para o profissional. A prática atual envolve o uso de modelos de previsão de probabilidade pré-teste e, para otimizar esse processo, várias estratégias têm sido exploradas. Objetivos: Investigar se a aplicação dos critérios de exclusão de EP (pulmonary embolism rule-out criteria, PERC) e do D-dímero (DD) ajustado para idade diminui o número de angiografias computadorizadas (ATCs) pulmonares realizadas em pacientes com suspeita de EP. Métodos: Estudo transversal retrospectivo com pacientes adultos submetidos a ATC pulmonar com suspeita de EP em 2018 e 2020. Foram aplicados os critérios PERC e o DD ajustado para idade. Foi estimado o número de casos não indicados para exames de imagem, e foram calculadas as características operacionais para o diagnóstico de EP. Resultados: Foram incluídos 302 pacientes, dos quais 29,8% apresentaram diagnóstico de EP. Apenas 27,2% dos casos não prováveis ​​de acordo com os critérios de Wells apresentaram DD; o ajuste implicou em uma diminuição de ACTs de 11,1%, com área sob a curva de 0,5. Os critérios PERC diminuiriam em 7%, com área sob a curva de 0,72. Conclusões: A aplicação do DD ajustado para idade e dos critérios PERC em pacientes submetidos a ATC pulmonar por suspeita de EP parece diminuir a indicação para tais exames.

Development and Validation of Models to Predict Pathological Outcomes of Radical Prostatectomy in Regional and National Cohorts.

PURPOSE: Prediction models are recommended by national guidelines to support clinical decision making in prostate cancer. Existing models to predict pathological outcomes of radical prostatectomy (RP)-the Memorial Sloan Kettering (MSK) models, Partin tables, and the Briganti nomogram-have been developed using data from tertiary care centers and may not generalize well to other settings. MATERIALS AND METHODS: Data from a regional cohort (Michigan Urological Surgery Improvement Collaborative [MUSIC]) were used to develop models to predict extraprostatic extension (EPE), seminal vesicle invasion (SVI), lymph node invasion (LNI), and nonorgan-confined disease (NOCD) in patients undergoing RP. The MUSIC models were compared against the MSK models, Partin tables, and Briganti nomogram (for LNI) using data from a national cohort (Surveillance, Epidemiology, and End Results [SEER] registry). RESULTS: We identified 7,491 eligible patients in the SEER registry. The MUSIC model had good discrimination (SEER AUC EPE: 0.77; SVI: 0.80; LNI: 0.83; NOCD: 0.77) and was well calibrated. While the MSK models had similar discrimination to the MUSIC models (SEER AUC EPE: 0.76; SVI: 0.80; LNI: 0.84; NOCD: 0.76), they overestimated the risk of EPE, LNI, and NOCD. The Partin tables had inferior discrimination (SEER AUC EPE: 0.67; SVI: 0.76; LNI: 0.69; NOCD: 0.72) as compared to other models. The Briganti LNI nomogram had an AUC of 0.81 in SEER but overestimated the risk. CONCLUSIONS: New models developed using the MUSIC registry outperformed existing models and should be considered as potential replacements for the prediction of pathological outcomes in prostate cancer.

Prognostic value of patient-reported outcome measures (PROMs) in adults with non-small cell Lung Cancer: a scoping review.

BACKGROUND: There is growing interest in the collection and use of patient-reported outcome measures (PROMs) to support clinical decision making in patients with non-small cell lung cancer (NSCLC). However, an overview of research into the prognostic value of PROMs is currently lacking. AIM: To explore to what extent, how, and how robustly the value of PROMs for prognostic prediction has been investigated in adults diagnosed with NSCLC. METHODS: We systematically searched Medline, Embase, CINAHL Plus and Scopus for English-language articles published from 2011 to 2021 that report prognostic factor study, prognostic model development or validation study. Example data charting forms from the Cochrane Prognosis Methods Group guided our data charting on study characteristics, PROMs as predictors, predicted outcomes, and statistical methods. Two reviewers independently charted the data and critically appraised studies using the QUality In Prognosis Studies (QUIPS) tool for prognostic factor studies, and the risk of bias assessment section of the Prediction model Risk Of Bias ASsessment Tool (PROBAST) for prognostic model studies. RESULTS: Our search yielded 2,769 unique titles of which we included 31 studies, reporting the results of 33 unique analyses and models. Out of the 17 PROMs used for prediction, the EORTC QLQ-C30 was most frequently used (16/33); 12/33 analyses used PROM subdomain scores instead of the overall scores. PROMs data was mostly collected at baseline (24/33) and predominantly used to predict survival (32/33) but seldom other clinical outcomes (1/33). Almost all prognostic factor studies (26/27) had moderate to high risk of bias and all four prognostic model development studies had high risk of bias. CONCLUSION: There is an emerging body of research into the value of PROMs as a prognostic factor for survival in people with NSCLC but the methodological quality of this research is poor with significant bias. This warrants more robust studies into the prognostic value of PROMs, in particular for predicting outcomes other than survival. This will enable further development of PROM-based prediction models to support clinical decision making in NSCLC.

Improving appropriate use of anticoagulants in hospitalised patients: A pharmacist-led Check of Medication Appropriateness intervention.

AIMS: Inappropriate anticoagulant use increases the risk of bleeding and thrombotic events. We implemented clinical decision rules to promote judicious medication use, as part of the 'Check of Medication Appropriateness' (CMA). The CMA is a pharmacist-led review service, targeting potentially inappropriate prescriptions (PIPs). In this analysis, we aimed to evaluate the impact of the CMA on anticoagulant prescribing. METHODS: The number of anticoagulant-related PIPs was evaluated before and after implementation of the intervention in a quasi-experimental interrupted time series analysis. The pre-implementation cohort received usual care. The anticoagulant-focused CMA, comprising 13 clinical rules pertaining to anticoagulation therapies, was implemented in the post-implementation cohort. Segmented regression analysis was used to assess the impact of the intervention on the number of residual PIPs. A residual PIP was defined as a PIP which persisted up to 48 hours after the CMA intervention. Total number of recommendations and acceptance rate were documented for the 2-year post-implementation period. RESULTS: Pre-implementation, we observed 501 PIPs in 466 inpatients on 36 days, with a median proportion of 78.5% (range: 46.2%-100%) residual PIPs per day. Post-implementation, 538 PIPs were detected in 485 patients over the same number of days. The CMA intervention reduced the median proportion to 18.2% (range: 0-100%) per day. The effect coincided with an immediate relative reduction of 70% (95%CI 0.19-0.46) in anticoagulant-related residual PIPs. Post-implementation, 2778 recommendations were provided and 75.1% were accepted. CONCLUSION: Our CMA approach significantly reduced anticoagulant-related PIPs. Implementing a pharmacist-led intervention, based on clinical rules, may support safer prescribing of anticoagulants.

All-Cause Mortality Risk Prediction in Older Adults with Cancer: Practical Approaches and Limitations.

PURPOSE OF REVIEW: The prediction of all-cause mortality is an important component of shared decision-making across the cancer care continuum, particularly in older adults with limited life expectancy, for whom there is an increased risk of over-diagnosis and treatment. RECENT FINDINGS: Currently, several international societies recommend the use of all-cause mortality risk prediction tools when making decisions regarding screening and treatment in geriatric oncology. Here, we review some practical aspects of the utilization of those tools and dissect the characteristics of those most employed in geriatric oncology, highlighting both their advantages and their limitations.

Clinical prediction of laboratory-confirmed influenza in adults with influenza-like illness in primary care. A randomized controlled trial secondary analysis in 15 European countries.

BACKGROUND: Clinical findings do not accurately predict laboratory diagnosis of influenza. Early identification of influenza is considered useful for proper management decisions in primary care. OBJECTIVE: We evaluated the diagnostic value of the presence and the severity of symptoms for the diagnosis of laboratory-confirmed influenza infection among adults presenting with influenza-like illness (ILI) in primary care. METHODS: Secondary analysis of patients with ILI who participated in a clinical trial from 2015 to 2018 in 15 European countries. Patients rated signs and symptoms as absent, minor, moderate, or major problem. A nasopharyngeal swab was taken for microbiological identification of influenza and other microorganisms. Models were generated considering (i) the presence of individual symptoms and (ii) the severity rating of symptoms. RESULTS: A total of 2,639 patients aged 18 or older were included in the analysis. The mean age was 41.8 ± 14.7 years, and 1,099 were men (42.1%). Influenza was microbiologically confirmed in 1,337 patients (51.1%). The area under the curve (AUC) of the model for the presence of any of seven symptoms for detecting influenza was 0.66 (95% confidence interval [CI]: 0.65-0.68), whereas the AUC of the symptom severity model, which included eight variables-cough, fever, muscle aches, sweating and/or chills, moderate to severe overall disease, age, abdominal pain, and sore throat-was 0.70 (95% CI: 0.69-0.72). CONCLUSION: Clinical prediction of microbiologically confirmed influenza in adults with ILI is slightly more accurate when based on patient reported symptom severity than when based on the presence or absence of symptoms.

Influenza is usually diagnosed clinically. However, the accuracy of a diagnosis of influenza based on clinical features is limited because symptoms overlap considerably with those caused by other microorganisms. This study examined whether identification of the severity rather than the presence of key signs and symptoms could aid in the diagnosis of influenza, thereby helping clinicians to determine when antiviral agent use is appropriate. The authors used the database of a previous randomized clinical trial on the effectiveness of an antiviral carried out in primary care centers in 15 countries in Europe during three epidemic periods from 2015/2016 to 2017/2018. Participants with influenza symptoms were included and they were asked about the presence and severity of different symptoms during the baseline visit with their doctors and a nasopharyngeal swab was taken for microbiological analysis. Overall, only 51% of the patients aged 18 or older had a confirmed influenza infection. Clinical findings are not particularly useful for confirming or excluding the diagnosis of influenza. However, the results of our study recommend considering how intense the different symptoms are, since key symptoms rated as moderate or severe are slightly better for predicting flu rather than the presence or absence of these symptoms.