Development of a predictive nomogram for early identification of pulmonary embolism in hospitalized patients: a retrospective cohort study.

Hospitalized patients often present with complex clinical conditions, but there is a lack of effective tools to assess their risk of pulmonary embolism (PE). Therefore, our study aimed to develop a nomogram model for better predicting PE in hospitalized populations. Data from hospitalized patients (aged ≥ 15 years) who underwent computed tomography pulmonary angiography (CTPA) to confirm PE and non-PE were collected from December 2013 to April 2023. Univariate and multivariate stepwise logistic regression analyses were conducted to identify independent predictors of PE, followed by the construction of a predictive nomogram and internal validation. The efficiency and clinical utility of the nomogram model were assessed using receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and clinical impact curve (CIC). The study included 313 PE and 339 non-PE hospitalized patients. Male gender, dyspnea or shortness of breath, interstitial lung disease, lower limb deep vein thrombosis, elevated fibrin degradation product (FDP), pulmonary arterial hypertension, and tricuspid regurgitation were identified as independent risk factors. The AUC of the predictive nomogram model was 0.956 (95% CI: 0.939-0.974), demonstrating superior performance compared with the simplified Wells score of 0.698 (95% CI: 0.654-0.741) and the modified Geneva score of 0.758 (95% CI: 0.717-0.799). Our study demonstrated that challenges remain in the accuracy of the Wells score and revised Geneva score in assessing PE in hospitalized patients. Fortunately, the nomogram we developed has shown a favorable ability to discriminate PE cases, providing high reference value for clinical practice. However, given that this was a single-center study, we plan to expand efforts to collect data from additional centers to further validate our model.

Cao Z ，Yang L ，Han J ，Lv X ，Wang X ，Zhang B ，Ye X ，Ye H ... -  《BMC Pulmonary Medicine》

Development and Evaluation of a Nomogram for Predicting Pulmonary Embolism in Children With Severe Mycoplasma pneumoniae Pneumonia.

To construct a nomogram utilizing pediatric severe Mycoplasma pneumoniae pneumonia (SMPP) risk factors for pulmonary embolism (PE), facilitating the clinical identification and management of high-risk patients and reducing the excessive use of CT pulmonary angiography (CTPA). This was a retrospective analysis conducted between August 2021 and March 2024. We identified 35 children with SMPP complicated by PE, forming the PE group. A control group of 70 age- and sex-matched children with SMPP without PE was randomly selected at a 1:2 ratio. Clinical, laboratory, and CT findings were compared between the groups. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to develop a scoring model using a nomogram. The model's performance was assessed via the receiver operating characteristic curve (ROC), fivefold cross-validation, calibration curve, and clinical decision curve analysis. LASSO regression and multivariate logistic regression analyses revealed that D-dimer, neutrophil ratio, time to admission, pleural effusion, and necrotizing pneumonia were independent risk factors for PE in patients with SMPP. A nomogram prediction model was established based on the aforementioned independent risk factors. The area under ROC curve was 0.900. Fivefold cross-validation results further confirmed the model's stability. The calibration curve revealed good agreement between the predicted and actual probabilities of PE caused by SMPP, and the decision curve demonstrated that the nomogram model had a higher clinical net benefit. The nomogram serves as a predictive tool to aid in early intervention for pediatric patients with SMPP at high risk for PE, while minimizing unnecessary CTPA and overtreatment in low-risk patients.

Guan Y ，Zhao B ，Song C ，Hou Q ，Tong T ，Xu S ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Development of a nomogram model to predict 30-day mortality in ICU cancer patients with acute pulmonary embolism.

Cancer patients with acute pulmonary embolism (APE) admitted to the intensive care unit (ICU) face a high short-term mortality rate. The simplified pulmonary embolism severity index (sPESI) is tool for predicting adverse outcomes. However, its effectiveness in ICU cancer patients with APE remains unclear. This study aimed to validate the sPESI score and develop a predictive model for 30-day mortality in this specific patient group. We conducted a retrospective analysis using data from the MIMIC-IV database, focusing on ICU patients with cancer and APE. The primary outcome of interest was 30-day mortality. Predictors were initially selected using Least Absolute Shrinkage and Selection Operator (LASSO) analysis. A multivariable logistic regression model was then developed. The performance of the nomogram was assessed using calibration, decision curve analysis (DCA), and receiver operating characteristic (ROC) curve analysis to evaluate accuracy, clinical utility, and discrimination, respectively. A total of 286 cancer patients with APE were included in the study, with an average age of 68.9 years; the cohort comprised 137 males (47.9%) and 149 females (52.1%), and the 30-day mortality rate was 32.2%. Multivariable logistic regression analysis identified SOFA score, tumor metastasis, hemoglobin level, anion gap, weight and the prevalence of liver disease as independent predictors of 30-day mortality. The area under the curves (AUCs) of ROC for sPESI and the nomogram model were 0.568 (95% CI, 0.500-0.637) and 0.761 (95% CI, 0.701-0.821). The nomogram model had a higher predictive value for 30-day mortality in patients with acute pulmonary embolism and cancer compared to the sPESI score (P < 0.05). We developed a nomogram to predict the probability of 30-day mortality for ICU patients with acute pulmonary embolism and cancer. This nomogram demonstrated robust performance and serves as a valuable tool for clinicians to identify patients at high risk of 30-day mortality.

Li S ，Huang S ，Feng Y ，Mao Y ... -  《Scientific Reports》

Sex as a prognostic factor for mortality in adults with acute symptomatic pulmonary embolism.

Pulmonary embolism (PE) is relatively common worldwide. It is a serious condition that can be life-threatening. Studies on the relationship between adverse outcomes of this condition and whether a patient is male or female have yielded inconsistent results. Determining whether there is an association between sex and short-term mortality in patients with acute PE is important as this information may help guide different approaches to PE monitoring and treatment. To determine whether sex (i.e. being a male or a female patient) is an independent prognostic factor for predicting mortality in adults with acute symptomatic pulmonary embolism. The Cochrane Vascular Information Specialist searched the Cochrane Vascular Specialised Register, CENTRAL, MEDLINE, Embase, and CINAHL databases, and the World Health Organization International Clinical Trials Registry Platform and ClinicalTrials.gov trials register up to 17 February 2023. We scanned conference abstracts and reference lists of included studies and systematic reviews. We also contacted experts to identify additional studies. There were no restrictions with respect to language or date of publication. We included phase 2-confirmatory prognostic studies, that is, any longitudinal study (prospective or retrospective) evaluating the independent association between sex (male or female) and mortality in adults with acute PE. We followed the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of prognostic factor studies (CHARMS-PF) and the Cochrane Prognosis Methods Group template for prognosis reviews. Two review authors independently screened the studies, extracted data, assessed the risk of bias according to the Quality in Prognosis Studies (QUIPS) tool, and assessed the certainty of the evidence (GRADE). Meta-analyses were performed by pooling adjusted estimates. When meta-analysis was not possible, we reported the main results narratively. We included seven studies (726,293 participants), all of which were retrospective cohort studies with participants recruited and managed in hospitals between 2000 and 2018. Studies took place in the USA, Spain, and Japan. Most studies were multicentre. None were conducted in low- or middle-income countries. The participants' mean age ranged from 62 to 69 years, and the proportion of females was higher in six of the seven studies, ranging from 46% to 60%. Sex and gender terms were used inconsistently. Participants received different PE treatments: reperfusion, inferior vena cava filter, anticoagulation, and haemodynamic/respiratory support. The prognostication time (the point from which the outcome was predicted) was frequently omitted. The included studies provided data for three of our outcomes of interest. We did not consider any of the studies to be at an overall low risk of bias for any of the outcomes analysed. We judged the certainty of the evidence as moderate to low due to imprecision and risk of bias. We found moderate-certainty evidence (due to imprecision) that for female patients there is likely a small but clinically important reduction in all-cause mortality at 30 days (odds ratio (OR) 0.81, 95% confidence interval (CI) 0.72 to 0.92; I2 = 0%; absolute risk difference (ARD) 24 fewer deaths in women per 1000 participants, 95% CI 35 to 10 fewer; 2 studies, 17,627 participants). However, the remaining review outcomes do not indicate lower mortality in female patients. There is low-certainty evidence (due to serious risk of bias and imprecision) indicating that for females with PE, there may be a small but clinically important increase in all-cause hospital mortality (OR 1.11, 95% CI 1.00 to 1.22; I2 = 21.7%; 95% prediction interval (PI) 0.76 to 1.61; ARD 13 more deaths in women per 1000 participants, 95% CI 0 to 26 more; 3 studies, 611,210 participants). There is also low-certainty evidence (due to very serious imprecision) indicating that there may be little to no difference between males and females in PE-related mortality at 30 days (OR 1.08, 95% CI 0.55 to 2.12; I2 = 0%; ARD 4 more deaths in women per 1000 participants, 95% CI 22 fewer to 50 more; 2 studies, 3524 participants). No study data was found for the other outcomes, including sex-specific mortality data at one year. Moreover, due to insufficient studies, many of our planned methods were not implemented. In particular, we were unable to conduct assessments of heterogeneity or publication bias or subgroup and sensitivity analyses. The evidence is uncertain about sex (being male or female) as an independent prognostic factor for predicting mortality in adults with PE. We found that, for female patients with PE, there is likely a small but clinically important reduction in all-cause mortality at 30 days relative to male patients. However, this result should be interpreted cautiously, as the remaining review outcomes do not point to an association between being female and having a lower risk of death. In fact, the evidence in the review also suggested that, in female patients, there may be a small but clinically important increase in all-cause hospital mortality. It also showed that there may be little to no difference in PE-related mortality at 30 days between male and female patients. There is currently no study evidence from longitudinal studies for our other review outcomes. Although the available evidence is conflicting and therefore cannot support a recommendation for or against routinely considering sex to quantify prognosis or to guide personalised therapeutic approaches for patients with PE, this Cochrane review offers information to guide future primary research and systematic reviews.

Jimenez Tejero E ，Lopez-Alcalde J ，Correa-Pérez A ，Stallings E ，Gaetano Gil A ，Del Campo Albendea L ，Mateos-Haro M ，Fernandez-Felix BM ，Stallings R ，Alvarez-Diaz N ，García Laredo E ，Solier A ，Fernández-Martínez E ，Morillo Guerrero R ，de Miguel M ，Perez R ，Antequera A ，Muriel A ，Jimenez D ，Zamora J ... -  《Cochrane Database of Systematic Reviews》