Home Correlation of cardiac troponin T and APACHE III score with all-cause in-hospital mortality in critically ill patients with acute pulmonary embolism
Article Open Access

Correlation of cardiac troponin T and APACHE III score with all-cause in-hospital mortality in critically ill patients with acute pulmonary embolism

  • Hongxia Wang EMAIL logo , Yang Ji , Keke Zhang and Guangqiang Shao
Published/Copyright: August 1, 2022

Abstract

Pulmonary embolism (PE) is a fatal condition particularly in critically ill patients. We determined the association among the cardiac troponin T (cTnT) level, acute physiologic and chronic health evaluation (APACHE III) scoring system, and in-hospital mortality in critically ill patients with acute PE. A total of 501 patients with PE were initially enrolled. According to the multivariable logistic regression model for in-hospital mortality, the odds ratio of the cTnT level and APACHE III score was 1.96 (95% confidence interval [CI] = 1.18–3.24, P = 0.008) and 1.03 (95% CI = 1.02–1.05, P < 0.001), respectively. The area under the curve (AUC) of cTnT and APACHE III score for in-hospital mortality was 0.630 (95% CI = 0.586–0.672, P = 0.03) and 0.740 (95% CI = 0.699–0.778, P = 0.02), respectively. The discriminatory cTnT and APACHE III threshold values for in-hospital mortality were 0.08 ng/L and 38 score, respectively; the sensitivities and specificities of cTnT were 46.48 and 83.10%, respectively, whereas those of the APACHE III score were 74.88 and 54.19%, respectively. The cTnT and APACHE III scores were combined in the logistic analysis model, and a regression equation was derived to calculate the in-hospital mortality. The AUC was found to increase to 0.788 (95% CI = 0.734–0.840, P = 0.025). The sensitivity and specificity increased to 84.5 and 71.4%, respectively. The cTnT and APACHE III scores exhibited a significant association with in-hospital mortality of critically ill patients with PE. In conclusion, these parameters in combination can significantly improve the in-hospital mortality prediction.

1 Introduction

Pulmonary embolism (PE) is a fatal disease having an annual incidence of 39–115 cases per 100 thousand people [1]. The mortality rate of patients with untreated PE is 30% [2], whereas those of high-risk and moderate-risk patients with PE are 25–52% [3] and 8–15% [4], respectively. Mortality can be reduced by identifying high-risk patients through simple and easily available methods and by administering treatment in a timely manner. Predicting in-hospital mortality in critically ill patients with acute PE is challenging, and even the simplified PE severity index (sPESI), the most common tool for determining the prognosis and severity of PE, is considered unsuitable for mortality prediction in these patients. sPESI is calculated based on the following indicators: sex (10 points for men and 0 point for women), heart rate >110 beats/min (20 points), tumor (30 points), heart failure (10 points), chronic lung disease (10 points), systolic blood pressure <100 mmHg (30 points), respiratory rate <30 beats/min (20 points), body temperature <36°C (20 points), mental change (60 points), and arterial blood gas analysis oxygen saturation <90% (20 points). Generally, sPESI indicators have only two grades, which aggravates the disease severity level among critically ill patients to such an extent that makes the stratification of critically ill patients with acute PE challenging. Therefore, identifying more specific and comprehensive tools to stratify these critically ill patients is essential.

Another most extensively used system to evaluate the disease severity and prognosis of patients in the intensive care unit (ICU) is the acute physiologic and chronic health evaluation (APACHE III) scoring system. This scoring system was developed and expanded based on the APACHE II scoring system, and it comprises age, physiological scores, and health status as indicators. The APACHE III scoring system has been used in previous studies to predict hospital mortality in patients undergoing surgery [5] and in those with liver cirrhosis [6] and respiratory failure [7]; however, none of the studies have investigated its efficacy in predicting mortality of patients with acute PE.

Troponin, a cardiac disease marker, is a specific and sensitive marker for myocardial infarction. An increased troponin level was found to be significantly associated with right ventricular dysfunction [8], which is a crucial mortality predictor in acute PE [9]. However, the usefulness of troponin in predicting the prognosis of acute PE remains to be confirmed. A study by Jiménez et al. demonstrated that the elevated troponin level could not predict mortality adequately [10]. Furthermore, a study by El-Menyar et al. indicated that the increased troponin level is significantly related to high mortality in PE patients [11].

Although the APACHE III score can be a mortality predictor in patients in the ICU and cardiac troponin T (cTnT) can predict the mortality of patients with PE, no study has investigated the role of both APACHE III and cTnT as the predictor for in-hospital mortality in patients with acute PE admitted in the ICU. The current study explored the relationship between the cTnT level and APACHE III score and the all-cause in-hospital mortality of such patients. The study also attempted to determine whether all-cause in-hospital mortality prediction could be improved by the combined use of these parameters in these special study populations.

2 Materials and methods

2.1 Patient and public involvement

Neither patients nor the public were involved in the design, conduct, reporting, or dissemination of this research.

2.2 Ethics approval statement

This study was exempted from the institutional review board review and informed consent from patients was not required because an anonymous public database was used to retrieve data, thus waiving the need for ethical approval.

2.3 Database

The present retrospective study used the data extracted from the Medical Information Mart for Intensive Care III (MIMIC-III), which is an extensive, free access database containing de-identified health-related data collected from nearly 40,000 patients admitted to the ICU in the Beth Israel Deaconess Medical Center from 2001 to 2012. Informed consent was not required because the current study used data from a third-party anonymous public database, and our institution is exempted from institutional review board approval. A researcher certified by the National Institute of Health online training course (certification number: 39067458) extracted data by using PostgreSQL Tools (v. 4.24).

2.4 Study population and data extraction

Patients with an age of more than 18 years who were admitted to the ICU due to acute PE and stayed in the ICU for more than 24 h were recruited as study participants. Patients diagnosed as having acute PE during their ICU stay were not included in the study, and those with unavailable data for the cTnT level were also excluded. The first ICU admission record in the database of patients with more than one record was utilized. Figure 1 summarizes the detailed procedure for participant selection.

Figure 1 
                  Flow chart depicting the patient selection process. Abbreviations: ICU, intensive care unit.
Figure 1

Flow chart depicting the patient selection process. Abbreviations: ICU, intensive care unit.

The SQL program was used to extract the following clinical data: PE was recognized according to ICD-9-CM codes (41,519); demographic information included age, sex, weight, height, sequential organ failure assessment (SOFA), Glasgow coma score (GCS), systemic inflammatory response syndrome (SIRS), simplified acute physiology score (SAPS), and treatment variables such as renal replacement therapy and mechanical ventilation (MV). Information on comorbidities such as bacterial pneumonia, ventilator-associated pneumonia, chronic obstructive pulmonary disease, cardiac dysrhythmias, congestive heart failure, hypertension, uncomplicated and complicated diabetes, bacterial pneumonia, malignant tumor, and deep vein thrombosis, which were also determined according to ICD-9-CM codes, was extracted. Laboratory measurements comprised white blood cell (WBC) count, platelet count, hemoglobin level, cTnT level, serum creatinine, potassium (K+) and sodium (Na+) levels, blood urea nitrogen levels, and partial pressure of carbon dioxide (PCO2) and oxygen (PO2).

2.5 Definitions

In the database, cTnT values <0.01 were input as 0.009, whereas cTnT values >25 were input as 25.1, but the proportion of total were not >5%. “cTnT max” denotes the maximum value during hospitalization, whereas “cTnT min” denotes the minimum value during hospitalization.

2.5.1 APACHE III scoring system

The APACHE Ⅲ scoring system is a critical illness evaluation method proposed by Knaus in 1991. It includes the acute physiology score (APS), chronic health status score (CHS), and age score. The APS score ranges from 0 to 252, the CHS score ranges from 4 to 23, and the age score ranges from 0 to 24; the total score ranges from 0 to 299. The APS includes 17 parameters of the Apache III physiological scoring system: heart rate, mean arterial pressure, body temperature, respiratory rate, arterial oxygen partial pressure, alveolar–arferial oxygen partial pressure (only for the patients with intubation), hematocrit, leukocyte count, creatinine, 24 h urine volume, urea nitrogen, serum sodium, albumin, total bilirubin, blood glucose, acid–base imbalance score and GCS. The CHS includes liver failure, lymphoma, tumor metastasis, leukemia, immunosuppressive, and cirrhosis.

2.6 Study outcome

In-hospital mortality after ICU admission was the major outcome of this study.

2.7 Statistical analyses

Data are presented as the mean value and standard deviation, numbers (percentages), or median (25% quartile, 75% quartile) according to the distribution and type of variables. The Kruskal–Wallis test and Chi-square (or Fisher’s exact) test were employed to compare group differences. A logistic regression model with a stepwise backward elimination method was constructed to analyze the all-cause in-hospital mortality. We input all the variables in Table 1 in the logistic regression model. The variables with a significance level of 0.05 were entered in the final multivariable logistic regression model. A variance inflation factor (VIF) was used to test potential multicollinearity, with a value of ≥5 indicating multicollinearity and the VIF of the final model was 4.7. The variables cTnT level, APACHE III score, age, BMI, hemoglobin level, WBC count, invasive MV, and malignant tumor were entered in the final model (Table 2). Age, hemoglobin, WBC count, invasive MV, and malignant tumor were also the components of the APACHE III scoring system. In order to facilitate clinical application, we simplified the model and selected a combination of only the cTnT level and APACHE III score to estimate the in-hospital mortality. The ROC curve was drawn, and the corresponding area under the curve (AUC), sensitivity, specificity, and optimal threshold value were calculated. All statistical tests were two-sided and conducted using Stata software (version 15.0). A P value of <0.05 was considered statistically significant.

Table 1

Comparison of clinical characteristics and laboratory findings between survivors and non-survivors

Total (n = 501) Survivors (n = 430) Non-survivors (n = 71) P-value
Age (years) 65.63 ± 16.3 64.3 ± 16.5 73.29 ± 12.6 <0.001
 Males 265 (52.89%) 234 (54.42%) 31 (43.66%) 0.09
 Females 236 (47.11%) 196 (45.58%) 40 (56.34%)
 BMI 25.0 (20.5, 27.9) 25.4 (20.8, 28.3) 22.4 (18.6, 25.0) <0.001
Score
 SAPS 17 (13, 20) 16.3 (13, 20) 21.6 (17, 25) <0.001
 SIRS 2.9 (2, 4) 2.8 (2, 4) 3.2 (3, 4) <0.001
 GCS 13.7 (14, 15) 13.9 (14, 15) 12.8 (13, 15) 0.15
 SOFA 3.87 (1, 6) 3.51 (1, 5) 6.02 (3, 9) <0.001
 APACHE III 43.5 (30, 52) 40.6 (28, 49) 60.5 (40, 73) <0.001
MV
 Invasive 196 (39.12%) 152 (35.35%) 44 (61.97%) <0.001
 NIV 194 (9.8%) 170 (10.3%) 24 (7.6%) 0.89
 Sepsis 151 (30.14%) 126 (29.3%) 25 (35.2%) 0.31
 Renal replacement therapy on first day 21 (4.19%) 19 (4.42%) 2(2.82%) 0.53
Comorbidities
 DVT 142 (28.3%) 124 (28.8%) 18 (25.4%) 0.54
 Bacterial pneumonia 9 (1.8%) 8 (1.86%) 1 (1.41%) 0.79
 Ventilator-associated Pneumonia 17 (3.39%) 16 (3.72%) 1 (1.41%) 0.31
 COPD 90 (17.96%) 74 (17.21%) 16 (22.54%) 0.27
 Coronary 71 (14.17%) 62 (14.42%) 9 (12.68%) 0.69
 Cardiac dysrhythmias 62 (12.38%) 56 (13.02%) 6 (8.45%) 0.27
 Acute myocardial infarction 16 (3.20%) 15 (3.49%) 1 (1.41%) 0.35
 Congestive heart failure 167 (33.3%) 148 (34.4%) 19 (26.7%) 0.20
 Complicated diabetes 28 (5.59%) 25 (5.81%) 3 (4.23%) 0.58
 Uncomplicated diabetes 112 (22.36%) 101 (23.49%) 11 (15.49%) 0.13
 Hypertension 235 (46.91%) 201 (46.74%) 34 (47.89%) 0.06
 Malignant tumor 132 (26.35%) 106 (24.65%) 26 (36.6%) 0.03
 Liver disease 19 (3.79%) 18 (4.19%) 1 (1.41%) 0.23
 Cerebral infarction 21 (4.19%) 19 (4.42%) 2 (2.28%) 0.53
Vitals first day
 Heartrate, min 91 (79, 103) 91 (80, 103) 91 (76, 105) 0.85
 SBP, mmHg 117 (106, 126) 118 (107, 127) 112 (101, 124) 0.012
 DBP, mmHg 63 (55, 70) 64 (56, 70) 60 (53, 65) <0.001
 Resprate, min 21 (17, 24) 21 (17, 24) 22 (18, 25) 0.10
 Temp, °C 36.8 (36.3, 37.2) 36.8 (36.4, 37.2) 36.6 (36.3, 37.1) 0.29
 SpO2 97 (95, 98) 97 (95, 98) 96 (94, 98) 0.19
Laboratory parameters
 cTnT initial, ng/mL 0.15 (0.01, 0.1) 0.11 (0.01, 0.09) 0.33 (0.01, 0.27) <0.001
 cTnT max ng/mL 0.32 (0.01, 0.2) 0.30 (0.01, 0.16) 0.52 (0.04, 0.42) <0.001
 cTnT min ng/mL 0.07 (0.01, 0.05) 0.06 (0.01, 0.04) 0.18 (0.01, 0.13) <0.001
 WBCs count, 109/L 12.3 (7.6, 14) 11.5 (7.5, 13.4) 16.8 (9.9, 17.4) <0.001
 Platelet count, 109/L 237 (159, 284) 238 (161, 281) 230 (141, 295) 0.36
 Hemoglobin, g/dL 10.8 (9.3, 12) 10.8 (9.3, 12) 10.8 (9.8, 11.7) 0.59
 Creatinine, mg/dL 3.59 (0.7, 1.3) 3.9 (0.7, 1.2) 1.47 (0.8, 1.7) 0.02
 BUN, mg/dl 23.48 (16, 39) 21.9 (12, 26) 32.3 (17, 46) <0.001
 K+, mEq/L 4.07 (3.7, 4.6) 4.04 (3.7, 4.3) 4.23 (3.7, 4.6) 0.35
 Na+, mEq/L 138.9 (137, 141) 138.9 (137, 141) 138.8 (136, 142) 0.95
 PO2, mmHg 128 (78, 148) 127 (78, 147) 132 (71, 165) 0.94
 PCO2, mmHg 42.3 (35, 47) 42.9 (36, 47) 41.2 (33, 48) 0.11
 Length of ICU stay (days) 5.5 (1.7, 6) 5.4 (1.7, 5.6) 6.0 (1.9, 7.4) 0.04
 Length of hospital stay (days) 14.2 (5.9, 16.8) 14.7 (6.2, 18) 11.39 (3.7, 13.6) 0.002

Notes: Data are expressed as mean value ± standard deviation, median (25th, 75th percentiles) or n (%). Kruskal–Wallis or Chi-square (or Fisher’s exact) tests were used for comparisons between groups. *Statistical significance (P < 0.05).

Abbreviations: ICU, intensive care unit; SOFA, sequential organ failure assessment data; APACHE III, acute physiologic and chronic health evaluation scoring system III; cTnT, cardiac troponin T; SIRS, systemic inflammatory response syndrome; K, serum potassium levels; Na, serum sodium levels; SBP, systolic blood pressure; DBP, diastolic blood pressure; Temp, temperature; SpO2, oxygen saturation; WBC, white blood cell; BUN, blood urea nitrogen levels; PCO2, partial pressure of carbon dioxide; PO2, partial pressure of oxygen; DVT, deep vein thrombosis; GCS, Glasgowcomascore; COPD, chronic obstructive pulmonary disease; NIV, non-invasive mechanical.

Table 2

Multivariable logistic regression analysis of factors associated with in-hospital mortality in critically ill patients with acute PE

Variables OR 95% CI P-value
cTnT 1.96 1.18–3.24 0.008
APACHE III 1.03 1.02–1.05 <0.001
Age 1.04 1.02–1.07 <0.001
BMI 0.94 0.88–0.99 0.032
Hemoglobin 1.21 1.03–1.42 0.016
WBC count 1.02 1.01–1.03 0.026
Invasive MV 3.11 1.69–5.72 <0.001
Malignant tumor 1.99 1.07–3.68 0.028

Abbreviations: OR, odds ratio; CI, confidence interval; APACHE III, acute physiologic and chronic health evaluation scoring system III; cTnT, cardiac troponin T; WBC, white blood cell; MV, mechanical ventilation.

3 Results

3.1 Baseline characteristics of the study cohort

Seventy one out of the 501 patients who were included initially died, thereby indicating 14.17% mortality. Finally, a total of 430 patients (average patient age: 65.6 ± 16.3 years) were included. The comparison of demographics, clinical features, and laboratory measurements between the two groups is presented in Table 1. A large proportion of patients who did not survive required invasive MV. No significant difference was noted in the prevalence of comorbidities between these two patient groups. The notable exception was the presence of malignant tumor (24.65% vs 36.6%, P = 0.03). The level of cTnT and APACHE III score in the patients who did not survive were significantly higher than those who survived (P < 0.05).

3.2 Association between factors and study outcome

The multivariate logistic regression analysis indicated a positive association of cTnT and APACHE III score with in-hospital mortality in patients with PE. The odds ratio of cTnT and APACHE III score for in-hospital mortality was 1.96 (95% confidence interval [CI] = 1.18–3.24, P = 0.008) and 1.03 (95% CI = 1.02–1.05, P < 0.001), respectively (Table 2).

3.3 ROC curve of cTnT

The AUC of the cTnT level and APACHE III score for in-hospital mortality in patients with PE was 0.630 (95% CI = 0.586–0.672, P = 0.03) and 0.740 (95% CI = 0.699–0.778, P = 0.02), respectively. The discriminatory cTnT and APACHE III threshold values for in-hospital mortality were 0.08 ng/L and 38, respectively. The sensitivities for the same were 46.48 and 83.10%, respectively, and the specificities were 74.88 and 54.19%, respectively. The cTnT and APACHE III were combined in the logistic analysis model, and a regression equation was derived to calculate in-hospital mortality. Consequently, the AUC was found to increase to 0.788 (95% CI = 0.734–0.840, P = 0.025), whereas the sensitivity and specificity were found to increase to 84.5 and 71.4%, respectively (Figure 2; Table 3). The discriminatory cTnT and APACHE III threshold values were the same cut-off (0.08 ng/L and 38, respectively) for the combined logistic regression analysis.

Figure 2 
                  The area under the ROC curve (AUC) of cTnT combined with the APACHE III score was the highest (0.788), followed by that of the APACHE III score and cTnT alone (0.740 and 0.630, respectively). All P values are less than 0.05. Abbreviations: APACHE III, acute physiologic and chronic health evaluation scoring system III; cTnT, cardiac troponin T.
Figure 2

The area under the ROC curve (AUC) of cTnT combined with the APACHE III score was the highest (0.788), followed by that of the APACHE III score and cTnT alone (0.740 and 0.630, respectively). All P values are less than 0.05. Abbreviations: APACHE III, acute physiologic and chronic health evaluation scoring system III; cTnT, cardiac troponin T.

Table 3

Predictive value of troponin T, APACHE III, and the combination thereof for in-hospital mortality in critically ill patients with acute PE

Troponin T APACHE III Troponin T + APACHE III
Optimal threshold 0.08 38 cTnT 0.08
APACHE III 38
Sensitivity 46.48 83.10 84.5
Specificity 74.88 54.19 71.4
+LR 1.85 1.81 2.5
-LR 0.71 0.31 0.18
AUC 0.630 0.740 0.788
95% CI 0.586–0.672 0.699–0.778 0.734–0.845

Abbreviations: AUC, area under the receiver operator characteristic curve; CI, confidence interval. +LR, positive likelihood ratio; -LR, negative likelihood ratio.

4 Discussion

As a marker of cardiac disease, cTnT is particularly specific and sensitive for myocardial infarction. Four types of troponin, namely HsTnT, HsTnI, cTn, and cTnI, are widely used in clinic. All these troponins are associated with cardiovascular disease mortality and heart failure. El-Menyar et al. demonstrated that regardless of the measurement methods and troponin types, an elevated troponin level was significantly associated with high mortality in patients with PE [11]. Welsh et al. observed that cardiac troponin I is highly specific to the mortality risk in composite coronary disease and cardiovascular disease, whereas cTnT is closely related to mortality in non-cardiovascular disease [12]. Compared with other troponin types, cTnT has been most widely studied as an in-hospital mortality predictor [13,14,15]. Most studies have evaluated patients in the general ward or outpatient department, and this study is the first to report an association of cTnT with acute PE in patients in the ICU. The multivariable logistic regression analysis in the present study exhibited that an elevated cTnT level is associated with in-hospital deaths in patients with PE in the ICU. In the ROC curve analysis, the specificity of cTnT for in-hospital mortality prediction was found to be 74.88, with an AUC of 0.630. A correlation between these parameters and in-hospital mortality was noted, which is consistent with the findings of other studies.

The threshold troponin value in all-cause in-hospital mortality prediction has been controversial due to different troponin types and measurement methods, which contribute to a large difference between the values. Moreover, immeasurable extreme values such as >25 or <0.01 ng/L are often observed. Thus, several studies have considered certain extreme values such as 0.01 µg/L [16], 0.03 ng/mL [14], and 0.1 µg/L [17] as the cut-off to evaluate mortality in patients with PE. Because these extreme values account for a small proportion, we reassigned them. The cTnT values <0.01 ng/L were considered to be 0.009 ng/L, whereas those >25 ng/L were considered to be 25.1 ng/L. A novel discriminatory threshold value of 0.08 ng/L was observed in the ROC analysis.

A few studies have evaluated the PE scoring systems. The sPESI is a widely used tool for determining the severity and prognosis of PE. Recently, the modified Glasgow prognostic score was also reported useful for predicting in-hospital mortality in patients with stable hemodynamics [18]. However, both these methods are unsuitable for assessing mortality in critically ill patients with acute PE. Several scoring systems such as the SOFA, APACHE score, SIRS, Glasgow score, and SAPS have been developed for the assessment of critically ill patients. All these systems were developed for assessment in different groups of patients in the ICU; however, their precision in patient subgroups is poor [19]. Patients with PE in the ICU are typically evaluated using the commonly used scoring systems. The present study exhibited that not all scoring systems can predict mortality. The APACHE III scoring system proved to be the only acceptable prognostic scoring system, with a discriminatory threshold value for in-hospital mortality of 38. However, the specificity was only 54.19%. To further improve the in-hospital mortality prediction of patients with acute PE, we investigated whether a combination of cTnT and APACHE III score could improve sensitivity and specificity of in-hospital mortality prediction. The present study demonstrated that a combination of cTnT and APACHE III score could increase the AUC to 0.788 and the sensitivity and specificity to 84.5 and 71.4%, respectively. The area under the ROC of combining cardiac color ultrasound and cTnT to predict in-hospital mortality was >0.9. Studies have suggested that color Doppler echocardiography can predict patient prognosis by monitoring the right ventricular function [20]. The APACHE III score measurement is far easier to perform than the cardiac color ultrasound, particularly in patients with critical illness. The present study exhibited that a combination of cTnT and APACHE III score can significantly improve in-hospital mortality prediction. This finding could be helpful for clinicians in charge of patients and for managers involved in resource allocation and performance evaluation.

5 Limitations of the study

This study has certain limitations. We did not include the treatment type into the multivariate analysis, because most patients included in this study had received standardized treatment during ICU stay, suggesting that the type of treatment had a slight effect on the results. Additionally, only a few patients such as those with massive hemorrhage, gastrointestinal hemorrhage, or intracranial hemorrhage were unable to receive standardized treatment, and such patients could not be identified by us during the selection process. However, we propose a new method to predict the prognosis of critically ill patients with acute PE.

6 Conclusion

cTnT and APACHE III scores are significantly associated with all-cause in-hospital mortality in critically ill PE patients. Combination of cTnT and APACHE III score can significantly improve in-hospital mortality prediction.


tel: +86-13528460931

  1. Funding information: This study was financially supported by the Sanming Project of Medicine in Shenzhen “the Integrated Airways Disease team led by Professor Kian Fan Chung from Imperial College London” (SZSM201612096).

  2. Author contributions: Hongxia Wang designed the study. Yang Ji, Keke Zhang, and Guangqiang Shao performed computation and data analysis and prepared all the figures and tables. Hongxia Wang wrote the main manuscript text. All authors contributed to discussions about the results and revised the manuscript.

  3. Conflict of interest: No conflicts of interest, financial or otherwise, are declared by the authors.

  4. Data availability statement: Data are available in a public, open-access repository from the critical care database MIMIC-III.

References

[1] Keller K, Hobohm L, Ebner M, Kresoja KP, Münzel T, Konstantinides SV, et al. Trends in thrombolytic treatment and outcomes of acute pulmonary embolism in Germany. Eur Heart J. 2020 Jan 21;41(4):522–9.10.1093/eurheartj/ehz236Search in Google Scholar PubMed

[2] Rali PM, Criner GJ. Submassive pulmonary embolism. Am J Respir Crit Care Med. 2018 Sep 1;198(5):588–98.10.1164/rccm.201711-2302CISearch in Google Scholar PubMed

[3] Sanchez O, Planquette B, Wermert D, Marié E, Meyer G. Embolies pulmonaires graves [Massive pulmonary embolism]. Presse Med. 2008 Oct;37(10):1439–46. French.10.1016/j.lpm.2008.07.003Search in Google Scholar PubMed

[4] Pollack CV, Schreiber D, Goldhaber SZ, Slattery D, Fanikos J, O’Neil BJ, et al. Clinical characteristics, management, and outcomes of patients diagnosed with acute pulmonary embolism in the emergency department: initial report of EMPEROR (Multicenter Emergency Medicine Pulmonary Embolism in the Real World Registry). J Am Coll Cardiol. 2011 Feb 8;57(6):700–6.10.1016/j.jacc.2010.05.071Search in Google Scholar PubMed

[5] Zauner CA, Apsner RC, Kranz A, Kramer L, Madl C, Schneider B, et al. Outcome prediction for patients with cirrhosis of the liver in a medical ICU: a comparison of the APACHE scores and liver-specific scoring systems. Intensive Care Med. 1996 Jun;22(6):559–63.10.1007/BF01708096Search in Google Scholar PubMed

[6] Barie PS, Hydo LJ, Fischer E. Comparison of APACHE II and III scoring systems for mortality prediction in critical surgical illness. Arch Surg. 1995 Jan;130(1):77–82.10.1001/archsurg.1995.01430010079016Search in Google Scholar PubMed

[7] Hsu CW, Wann SR, Chiang HT, Lin CH, Kung MH, Lin SL. Comparison of the APACHE II and APACHE III scoring systems in patients with respiratory failure in a medical intensive care unit. J Formos Med Assoc. 2001 Jul;100(7):437–42.Search in Google Scholar

[8] Punukollu G, Khan IA, Gowda RM, Lakhanpal G, Vasavada BC, Sacchi TJ. Cardiac troponin I release in acute pulmonary embolism in relation to the duration of symptoms. Int J Cardiol. 2005 Mar 18;99(2):207–311.10.1016/j.ijcard.2004.01.012Search in Google Scholar PubMed

[9] Daquarti G, March Vecchio N, Mitrione CS, Furmento J, Ametrano MC, Dominguez Pace MP, et al. High-sensitivity troponin and right ventricular function in acute pulmonary embolism. Am J Emerg Med. 2016 Aug;34(8):1579–82.10.1016/j.ajem.2016.05.071Search in Google Scholar PubMed

[10] Jiménez D, Uresandi F, Otero R, Lobo JL, Monreal M, Martí D, et al. Troponin-based risk stratification of patients with acute nonmassive pulmonary embolism: systematic review and meta-analysis. Chest. 2009 Oct;136(4):974–82.10.1378/chest.09-0608Search in Google Scholar PubMed

[11] El-Menyar A, Sathian B, Al-Thani H. Elevated serum cardiac troponin and mortality in acute pulmonary embolism: Systematic review and meta-analysis. Respir Med. 2019 Oct;157:26–35.10.1016/j.rmed.2019.08.011Search in Google Scholar PubMed

[12] Welsh P, Preiss D, Hayward C, Shah ASV, McAllister D, Briggs A, et al. Cardiac Troponin T and Troponin I in the General Population. Circulation. 2019 Jun 11;139(24):2754–64.10.1161/CIRCULATIONAHA.118.038529Search in Google Scholar PubMed PubMed Central

[13] Cotugno M, Orgaz-Molina J, Rosa-Salazar V, Guirado-Torrecillas L, García-Pérez B. Right ventricular dysfunction in acute pulmonary embolism: NT-proBNP vs. troponin T. Med Clin (Barc). 2017 Apr 21;148(8):339–44. English, Spanish.10.1016/j.medcle.2017.04.007Search in Google Scholar

[14] Borz-Baba C, Munir M, Wakefield D, Feinn R. Brain natriuretic peptide and troponin T in patients with acute pulmonary embolism and grade 3 obesity: a retrospective analysis. Cureus. 2020 Jul 19;12(7):e9265.10.7759/cureus.9265Search in Google Scholar PubMed PubMed Central

[15] Hendriks SV, Lankeit M, den Exter PL, Zondag W, Brouwer R, Eijsvogel M, et al. Uncertain value of high-sensitive troponin T for selecting patients with acute pulmonary embolism for outpatient treatment by hestia criteria. Acad Emerg Med. 2020 Oct;27(10):1043–6.10.1111/acem.13943Search in Google Scholar PubMed PubMed Central

[16] Ng AC, Yong AS, Chow V, Chung T, Freedman SB, Kritharides L. Cardiac troponin-T and the prediction of acute and long-term mortality after acute pulmonary embolism. Int J Cardiol. 2013 Apr 30;165(1):126–33.10.1016/j.ijcard.2011.07.107Search in Google Scholar PubMed

[17] Giannitsis E, Müller-Bardorff M, Kurowski V, Weidtmann B, Wiegand U, Kampmann M, et al. Independent prognostic value of cardiac troponin T in patients with confirmed pulmonary embolism. Circulation. 2000 Jul 11;102(2):211–7. 10.1161/01.cir.102.2.211. PMID: 10889133.Search in Google Scholar PubMed

[18] Celik AI, Bezgin T, Biteker M. Predictive role of the modified Glasgow prognostic score for in-hospital mortality in stable acute pulmonary embolism. Med Clin (Barc). 2022 Feb 11;158(3):99–104.10.1016/j.medcli.2020.11.041Search in Google Scholar PubMed

[19] Vincent JL, Moreno R. Clinical review: scoring systems in the critically ill. Crit Care. 2010;14(2):207.10.1186/cc8204Search in Google Scholar PubMed PubMed Central

[20] Li H, Kang L, Sun Y. Clinical value of cardiac color ultrasound and cardiac troponin T combined with dynamic electrocardiogram in treatment of acute pulmonary embolism. Exp Ther Med. 2018 Feb;15(2):2044–8.10.3892/etm.2017.5658Search in Google Scholar PubMed PubMed Central

Received: 2022-02-15
Revised: 2022-07-10
Accepted: 2022-07-11
Published Online: 2022-08-01

© 2022 Hongxia Wang et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Research Articles
  2. AMBRA1 attenuates the proliferation of uveal melanoma cells
  3. A ceRNA network mediated by LINC00475 in papillary thyroid carcinoma
  4. Differences in complications between hepatitis B-related cirrhosis and alcohol-related cirrhosis
  5. Effect of gestational diabetes mellitus on lipid profile: A systematic review and meta-analysis
  6. Long noncoding RNA NR2F1-AS1 stimulates the tumorigenic behavior of non-small cell lung cancer cells by sponging miR-363-3p to increase SOX4
  7. Promising novel biomarkers and candidate small-molecule drugs for lung adenocarcinoma: Evidence from bioinformatics analysis of high-throughput data
  8. Plasmapheresis: Is it a potential alternative treatment for chronic urticaria?
  9. The biomarkers of key miRNAs and gene targets associated with extranodal NK/T-cell lymphoma
  10. Gene signature to predict prognostic survival of hepatocellular carcinoma
  11. Effects of miRNA-199a-5p on cell proliferation and apoptosis of uterine leiomyoma by targeting MED12
  12. Does diabetes affect paraneoplastic thrombocytosis in colorectal cancer?
  13. Is there any effect on imprinted genes H19, PEG3, and SNRPN during AOA?
  14. Leptin and PCSK9 concentrations are associated with vascular endothelial cytokines in patients with stable coronary heart disease
  15. Pericentric inversion of chromosome 6 and male fertility problems
  16. Staple line reinforcement with nebulized cyanoacrylate glue in laparoscopic sleeve gastrectomy: A propensity score-matched study
  17. Retrospective analysis of crescent score in clinical prognosis of IgA nephropathy
  18. Expression of DNM3 is associated with good outcome in colorectal cancer
  19. Activation of SphK2 contributes to adipocyte-induced EOC cell proliferation
  20. CRRT influences PICCO measurements in febrile critically ill patients
  21. SLCO4A1-AS1 mediates pancreatic cancer development via miR-4673/KIF21B axis
  22. lncRNA ACTA2-AS1 inhibits malignant phenotypes of gastric cancer cells
  23. circ_AKT3 knockdown suppresses cisplatin resistance in gastric cancer
  24. Prognostic value of nicotinamide N-methyltransferase in human cancers: Evidence from a meta-analysis and database validation
  25. GPC2 deficiency inhibits cell growth and metastasis in colon adenocarcinoma
  26. A pan-cancer analysis of the oncogenic role of Holliday junction recognition protein in human tumors
  27. Radiation increases COL1A1, COL3A1, and COL1A2 expression in breast cancer
  28. Association between preventable risk factors and metabolic syndrome
  29. miR-29c-5p knockdown reduces inflammation and blood–brain barrier disruption by upregulating LRP6
  30. Cardiac contractility modulation ameliorates myocardial metabolic remodeling in a rabbit model of chronic heart failure through activation of AMPK and PPAR-α pathway
  31. Quercitrin protects human bronchial epithelial cells from oxidative damage
  32. Smurf2 suppresses the metastasis of hepatocellular carcinoma via ubiquitin degradation of Smad2
  33. circRNA_0001679/miR-338-3p/DUSP16 axis aggravates acute lung injury
  34. Sonoclot’s usefulness in prediction of cardiopulmonary arrest prognosis: A proof of concept study
  35. Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation
  36. Decreased expression of miR-195 mediated by hypermethylation promotes osteosarcoma
  37. LMO3 promotes proliferation and metastasis of papillary thyroid carcinoma cells by regulating LIMK1-mediated cofilin and the β-catenin pathway
  38. Cx43 upregulation in HUVECs under stretch via TGF-β1 and cytoskeletal network
  39. Evaluation of menstrual irregularities after COVID-19 vaccination: Results of the MECOVAC survey
  40. Histopathologic findings on removed stomach after sleeve gastrectomy. Do they influence the outcome?
  41. Analysis of the expression and prognostic value of MT1-MMP, β1-integrin and YAP1 in glioma
  42. Optimal diagnosis of the skin cancer using a hybrid deep neural network and grasshopper optimization algorithm
  43. miR-223-3p alleviates TGF-β-induced epithelial-mesenchymal transition and extracellular matrix deposition by targeting SP3 in endometrial epithelial cells
  44. Clinical value of SIRT1 as a prognostic biomarker in esophageal squamous cell carcinoma, a systematic meta-analysis
  45. circ_0020123 promotes cell proliferation and migration in lung adenocarcinoma via PDZD8
  46. miR-22-5p regulates the self-renewal of spermatogonial stem cells by targeting EZH2
  47. hsa-miR-340-5p inhibits epithelial–mesenchymal transition in endometriosis by targeting MAP3K2 and inactivating MAPK/ERK signaling
  48. circ_0085296 inhibits the biological functions of trophoblast cells to promote the progression of preeclampsia via the miR-942-5p/THBS2 network
  49. TCD hemodynamics findings in the subacute phase of anterior circulation stroke patients treated with mechanical thrombectomy
  50. Development of a risk-stratification scoring system for predicting risk of breast cancer based on non-alcoholic fatty liver disease, non-alcoholic fatty pancreas disease, and uric acid
  51. Tollip promotes hepatocellular carcinoma progression via PI3K/AKT pathway
  52. circ_0062491 alleviates periodontitis via the miR-142-5p/IGF1 axis
  53. Human amniotic fluid as a source of stem cells
  54. lncRNA NONRATT013819.2 promotes transforming growth factor-β1-induced myofibroblastic transition of hepatic stellate cells by miR24-3p/lox
  55. NORAD modulates miR-30c-5p-LDHA to protect lung endothelial cells damage
  56. Idiopathic pulmonary fibrosis telemedicine management during COVID-19 outbreak
  57. Risk factors for adverse drug reactions associated with clopidogrel therapy
  58. Serum zinc associated with immunity and inflammatory markers in Covid-19
  59. The relationship between night shift work and breast cancer incidence: A systematic review and meta-analysis of observational studies
  60. LncRNA expression in idiopathic achalasia: New insight and preliminary exploration into pathogenesis
  61. Notoginsenoside R1 alleviates spinal cord injury through the miR-301a/KLF7 axis to activate Wnt/β-catenin pathway
  62. Moscatilin suppresses the inflammation from macrophages and T cells
  63. Zoledronate promotes ECM degradation and apoptosis via Wnt/β-catenin
  64. Epithelial-mesenchymal transition-related genes in coronary artery disease
  65. The effect evaluation of traditional vaginal surgery and transvaginal mesh surgery for severe pelvic organ prolapse: 5 years follow-up
  66. Repeated partial splenic artery embolization for hypersplenism improves platelet count
  67. Low expression of miR-27b in serum exosomes of non-small cell lung cancer facilitates its progression by affecting EGFR
  68. Exosomal hsa_circ_0000519 modulates the NSCLC cell growth and metastasis via miR-1258/RHOV axis
  69. miR-455-5p enhances 5-fluorouracil sensitivity in colorectal cancer cells by targeting PIK3R1 and DEPDC1
  70. The effect of tranexamic acid on the reduction of intraoperative and postoperative blood loss and thromboembolic risk in patients with hip fracture
  71. Isocitrate dehydrogenase 1 mutation in cholangiocarcinoma impairs tumor progression by sensitizing cells to ferroptosis
  72. Artemisinin protects against cerebral ischemia and reperfusion injury via inhibiting the NF-κB pathway
  73. A 16-gene signature associated with homologous recombination deficiency for prognosis prediction in patients with triple-negative breast cancer
  74. Lidocaine ameliorates chronic constriction injury-induced neuropathic pain through regulating M1/M2 microglia polarization
  75. MicroRNA 322-5p reduced neuronal inflammation via the TLR4/TRAF6/NF-κB axis in a rat epilepsy model
  76. miR-1273h-5p suppresses CXCL12 expression and inhibits gastric cancer cell invasion and metastasis
  77. Clinical characteristics of pneumonia patients of long course of illness infected with SARS-CoV-2
  78. circRNF20 aggravates the malignancy of retinoblastoma depending on the regulation of miR-132-3p/PAX6 axis
  79. Linezolid for resistant Gram-positive bacterial infections in children under 12 years: A meta-analysis
  80. Rack1 regulates pro-inflammatory cytokines by NF-κB in diabetic nephropathy
  81. Comprehensive analysis of molecular mechanism and a novel prognostic signature based on small nuclear RNA biomarkers in gastric cancer patients
  82. Smog and risk of maternal and fetal birth outcomes: A retrospective study in Baoding, China
  83. Let-7i-3p inhibits the cell cycle, proliferation, invasion, and migration of colorectal cancer cells via downregulating CCND1
  84. β2-Adrenergic receptor expression in subchondral bone of patients with varus knee osteoarthritis
  85. Possible impact of COVID-19 pandemic and lockdown on suicide behavior among patients in Southeast Serbia
  86. In vitro antimicrobial activity of ozonated oil in liposome eyedrop against multidrug-resistant bacteria
  87. Potential biomarkers for inflammatory response in acute lung injury
  88. A low serum uric acid concentration predicts a poor prognosis in adult patients with candidemia
  89. Antitumor activity of recombinant oncolytic vaccinia virus with human IL2
  90. ALKBH5 inhibits TNF-α-induced apoptosis of HUVECs through Bcl-2 pathway
  91. Risk prediction of cardiovascular disease using machine learning classifiers
  92. Value of ultrasonography parameters in diagnosing polycystic ovary syndrome
  93. Bioinformatics analysis reveals three key genes and four survival genes associated with youth-onset NSCLC
  94. Identification of autophagy-related biomarkers in patients with pulmonary arterial hypertension based on bioinformatics analysis
  95. Protective effects of glaucocalyxin A on the airway of asthmatic mice
  96. Overexpression of miR-100-5p inhibits papillary thyroid cancer progression via targeting FZD8
  97. Bioinformatics-based analysis of SUMOylation-related genes in hepatocellular carcinoma reveals a role of upregulated SAE1 in promoting cell proliferation
  98. Effectiveness and clinical benefits of new anti-diabetic drugs: A real life experience
  99. Identification of osteoporosis based on gene biomarkers using support vector machine
  100. Tanshinone IIA reverses oxaliplatin resistance in colorectal cancer through microRNA-30b-5p/AVEN axis
  101. miR-212-5p inhibits nasopharyngeal carcinoma progression by targeting METTL3
  102. Association of ST-T changes with all-cause mortality among patients with peripheral T-cell lymphomas
  103. LINC00665/miRNAs axis-mediated collagen type XI alpha 1 correlates with immune infiltration and malignant phenotypes in lung adenocarcinoma
  104. The perinatal factors that influence the excretion of fecal calprotectin in premature-born children
  105. Effect of femoral head necrosis cystic area on femoral head collapse and stress distribution in femoral head: A clinical and finite element study
  106. Does the use of 3D-printed cones give a chance to postpone the use of megaprostheses in patients with large bone defects in the knee joint?
  107. lncRNA HAGLR modulates myocardial ischemia–reperfusion injury in mice through regulating miR-133a-3p/MAPK1 axis
  108. Protective effect of ghrelin on intestinal I/R injury in rats
  109. In vivo knee kinematics of an innovative prosthesis design
  110. Relationship between the height of fibular head and the incidence and severity of knee osteoarthritis
  111. lncRNA WT1-AS attenuates hypoxia/ischemia-induced neuronal injury during cerebral ischemic stroke via miR-186-5p/XIAP axis
  112. Correlation of cardiac troponin T and APACHE III score with all-cause in-hospital mortality in critically ill patients with acute pulmonary embolism
  113. LncRNA LINC01857 reduces metastasis and angiogenesis in breast cancer cells via regulating miR-2052/CENPQ axis
  114. Endothelial cell-specific molecule 1 (ESM1) promoted by transcription factor SPI1 acts as an oncogene to modulate the malignant phenotype of endometrial cancer
  115. SELENBP1 inhibits progression of colorectal cancer by suppressing epithelial–mesenchymal transition
  116. Visfatin is negatively associated with coronary artery lesions in subjects with impaired fasting glucose
  117. Treatment and outcomes of mechanical complications of acute myocardial infarction during the Covid-19 era: A comparison with the pre-Covid-19 period. A systematic review and meta-analysis
  118. Neonatal stroke surveillance study protocol in the United Kingdom and Republic of Ireland
  119. Oncogenic role of TWF2 in human tumors: A pan-cancer analysis
  120. Mean corpuscular hemoglobin predicts the length of hospital stay independent of severity classification in patients with acute pancreatitis
  121. Association of gallstone and polymorphisms of UGT1A1*27 and UGT1A1*28 in patients with hepatitis B virus-related liver failure
  122. TGF-β1 upregulates Sar1a expression and induces procollagen-I secretion in hypertrophic scarring fibroblasts
  123. Antisense lncRNA PCNA-AS1 promotes esophageal squamous cell carcinoma progression through the miR-2467-3p/PCNA axis
  124. NK-cell dysfunction of acute myeloid leukemia in relation to the renin–angiotensin system and neurotransmitter genes
  125. The effect of dilution with glucose and prolonged injection time on dexamethasone-induced perineal irritation – A randomized controlled trial
  126. miR-146-5p restrains calcification of vascular smooth muscle cells by suppressing TRAF6
  127. Role of lncRNA MIAT/miR-361-3p/CCAR2 in prostate cancer cells
  128. lncRNA NORAD promotes lung cancer progression by competitively binding to miR-28-3p with E2F2
  129. Noninvasive diagnosis of AIH/PBC overlap syndrome based on prediction models
  130. lncRNA FAM230B is highly expressed in colorectal cancer and suppresses the maturation of miR-1182 to increase cell proliferation
  131. circ-LIMK1 regulates cisplatin resistance in lung adenocarcinoma by targeting miR-512-5p/HMGA1 axis
  132. LncRNA SNHG3 promoted cell proliferation, migration, and metastasis of esophageal squamous cell carcinoma via regulating miR-151a-3p/PFN2 axis
  133. Risk perception and affective state on work exhaustion in obstetrics during the COVID-19 pandemic
  134. lncRNA-AC130710/miR-129-5p/mGluR1 axis promote migration and invasion by activating PKCα-MAPK signal pathway in melanoma
  135. SNRPB promotes cell cycle progression in thyroid carcinoma via inhibiting p53
  136. Xylooligosaccharides and aerobic training regulate metabolism and behavior in rats with streptozotocin-induced type 1 diabetes
  137. Serpin family A member 1 is an oncogene in glioma and its translation is enhanced by NAD(P)H quinone dehydrogenase 1 through RNA-binding activity
  138. Silencing of CPSF7 inhibits the proliferation, migration, and invasion of lung adenocarcinoma cells by blocking the AKT/mTOR signaling pathway
  139. Ultrasound-guided lumbar plexus block versus transversus abdominis plane block for analgesia in children with hip dislocation: A double-blind, randomized trial
  140. Relationship of plasma MBP and 8-oxo-dG with brain damage in preterm
  141. Identification of a novel necroptosis-associated miRNA signature for predicting the prognosis in head and neck squamous cell carcinoma
  142. Delayed femoral vein ligation reduces operative time and blood loss during hip disarticulation in patients with extremity tumors
  143. The expression of ASAP3 and NOTCH3 and the clinicopathological characteristics of adult glioma patients
  144. Longitudinal analysis of factors related to Helicobacter pylori infection in Chinese adults
  145. HOXA10 enhances cell proliferation and suppresses apoptosis in esophageal cancer via activating p38/ERK signaling pathway
  146. Meta-analysis of early-life antibiotic use and allergic rhinitis
  147. Marital status and its correlation with age, race, and gender in prognosis of tonsil squamous cell carcinomas
  148. HPV16 E6E7 up-regulates KIF2A expression by activating JNK/c-Jun signal, is beneficial to migration and invasion of cervical cancer cells
  149. Amino acid profiles in the tissue and serum of patients with liver cancer
  150. Pain in critically ill COVID-19 patients: An Italian retrospective study
  151. Immunohistochemical distribution of Bcl-2 and p53 apoptotic markers in acetamiprid-induced nephrotoxicity
  152. Estradiol pretreatment in GnRH antagonist protocol for IVF/ICSI treatment
  153. Long non-coding RNAs LINC00689 inhibits the apoptosis of human nucleus pulposus cells via miR-3127-5p/ATG7 axis-mediated autophagy
  154. The relationship between oxygen therapy, drug therapy, and COVID-19 mortality
  155. Monitoring hypertensive disorders in pregnancy to prevent preeclampsia in pregnant women of advanced maternal age: Trial mimicking with retrospective data
  156. SETD1A promotes the proliferation and glycolysis of nasopharyngeal carcinoma cells by activating the PI3K/Akt pathway
  157. The role of Shunaoxin pills in the treatment of chronic cerebral hypoperfusion and its main pharmacodynamic components
  158. TET3 governs malignant behaviors and unfavorable prognosis of esophageal squamous cell carcinoma by activating the PI3K/AKT/GSK3β/β-catenin pathway
  159. Associations between morphokinetic parameters of temporary-arrest embryos and the clinical prognosis in FET cycles
  160. Long noncoding RNA WT1-AS regulates trophoblast proliferation, migration, and invasion via the microRNA-186-5p/CADM2 axis
  161. The incidence of bronchiectasis in chronic obstructive pulmonary disease
  162. Integrated bioinformatics analysis shows integrin alpha 3 is a prognostic biomarker for pancreatic cancer
  163. Inhibition of miR-21 improves pulmonary vascular responses in bronchopulmonary dysplasia by targeting the DDAH1/ADMA/NO pathway
  164. Comparison of hospitalized patients with severe pneumonia caused by COVID-19 and influenza A (H7N9 and H1N1): A retrospective study from a designated hospital
  165. lncRNA ZFAS1 promotes intervertebral disc degeneration by upregulating AAK1
  166. Pathological characteristics of liver injury induced by N,N-dimethylformamide: From humans to animal models
  167. lncRNA ELFN1-AS1 enhances the progression of colon cancer by targeting miR-4270 to upregulate AURKB
  168. DARS-AS1 modulates cell proliferation and migration of gastric cancer cells by regulating miR-330-3p/NAT10 axis
  169. Dezocine inhibits cell proliferation, migration, and invasion by targeting CRABP2 in ovarian cancer
  170. MGST1 alleviates the oxidative stress of trophoblast cells induced by hypoxia/reoxygenation and promotes cell proliferation, migration, and invasion by activating the PI3K/AKT/mTOR pathway
  171. Bifidobacterium lactis Probio-M8 ameliorated the symptoms of type 2 diabetes mellitus mice by changing ileum FXR-CYP7A1
  172. circRNA DENND1B inhibits tumorigenicity of clear cell renal cell carcinoma via miR-122-5p/TIMP2 axis
  173. EphA3 targeted by miR-3666 contributes to melanoma malignancy via activating ERK1/2 and p38 MAPK pathways
  174. Pacemakers and methylprednisolone pulse therapy in immune-related myocarditis concomitant with complete heart block
  175. miRNA-130a-3p targets sphingosine-1-phosphate receptor 1 to activate the microglial and astrocytes and to promote neural injury under the high glucose condition
  176. Review Articles
  177. Current management of cancer pain in Italy: Expert opinion paper
  178. Hearing loss and brain disorders: A review of multiple pathologies
  179. The rationale for using low-molecular weight heparin in the therapy of symptomatic COVID-19 patients
  180. Amyotrophic lateral sclerosis and delayed onset muscle soreness in light of the impaired blink and stretch reflexes – watch out for Piezo2
  181. Interleukin-35 in autoimmune dermatoses: Current concepts
  182. Recent discoveries in microbiota dysbiosis, cholangiocytic factors, and models for studying the pathogenesis of primary sclerosing cholangitis
  183. Advantages of ketamine in pediatric anesthesia
  184. Congenital adrenal hyperplasia. Role of dentist in early diagnosis
  185. Migraine management: Non-pharmacological points for patients and health care professionals
  186. Atherogenic index of plasma and coronary artery disease: A systematic review
  187. Physiological and modulatory role of thioredoxins in the cellular function
  188. Case Reports
  189. Intrauterine Bakri balloon tamponade plus cervical cerclage for the prevention and treatment of postpartum haemorrhage in late pregnancy complicated with acute aortic dissection: Case series
  190. A case of successful pembrolizumab monotherapy in a patient with advanced lung adenocarcinoma: Use of multiple biomarkers in combination for clinical practice
  191. Unusual neurological manifestations of bilateral medial medullary infarction: A case report
  192. Atypical symptoms of malignant hyperthermia: A rare causative mutation in the RYR1 gene
  193. A case report of dermatomyositis with the missed diagnosis of non-small cell lung cancer and concurrence of pulmonary tuberculosis
  194. A rare case of endometrial polyp complicated with uterine inversion: A case report and clinical management
  195. Spontaneous rupturing of splenic artery aneurysm: Another reason for fatal syncope and shock (Case report and literature review)
  196. Fungal infection mimicking COVID-19 infection – A case report
  197. Concurrent aspergillosis and cystic pulmonary metastases in a patient with tongue squamous cell carcinoma
  198. Paraganglioma-induced inverted takotsubo-like cardiomyopathy leading to cardiogenic shock successfully treated with extracorporeal membrane oxygenation
  199. Lineage switch from lymphoma to myeloid neoplasms: First case series from a single institution
  200. Trismus during tracheal extubation as a complication of general anaesthesia – A case report
  201. Simultaneous treatment of a pubovesical fistula and lymph node metastasis secondary to multimodal treatment for prostate cancer: Case report and review of the literature
  202. Two case reports of skin vasculitis following the COVID-19 immunization
  203. Ureteroiliac fistula after oncological surgery: Case report and review of the literature
  204. Synchronous triple primary malignant tumours in the bladder, prostate, and lung harbouring TP53 and MEK1 mutations accompanied with severe cardiovascular diseases: A case report
  205. Huge mucinous cystic neoplasms with adhesion to the left colon: A case report and literature review
  206. Commentary
  207. Commentary on “Clinicopathological features of programmed cell death-ligand 1 expression in patients with oral squamous cell carcinoma”
  208. Rapid Communication
  209. COVID-19 fear, post-traumatic stress, growth, and the role of resilience
  210. Erratum
  211. Erratum to “Tollip promotes hepatocellular carcinoma progression via PI3K/AKT pathway”
  212. Erratum to “Effect of femoral head necrosis cystic area on femoral head collapse and stress distribution in femoral head: A clinical and finite element study”
  213. Erratum to “lncRNA NORAD promotes lung cancer progression by competitively binding to miR-28-3p with E2F2”
  214. Retraction
  215. Expression and role of ABIN1 in sepsis: In vitro and in vivo studies
  216. Retraction to “miR-519d downregulates LEP expression to inhibit preeclampsia development”
  217. Special Issue Computational Intelligence Methodologies Meets Recurrent Cancers - Part II
  218. Usefulness of close surveillance for rectal cancer patients after neoadjuvant chemoradiotherapy
Downloaded on 18.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/med-2022-0534/html
Scroll to top button