Next Article in Journal
Simplified Formula for Estimating Nasal Dimensions for 3-Dimensional Facial Reconstruction among Japanese Adults
Previous Article in Journal
Age-at-Death Estimation by Dental Means as a Part of the Skeletal Analysis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Improving Traditional Post Mortem Healthcare—The Cross-Sectional Use of Blood-Based Biomarkers

Faculty of Medicine, Department of Anatomy, University of Rijeka, 51000 Rijeka, Croatia
Forensic Sci. 2023, 3(3), 368-380; https://doi.org/10.3390/forensicsci3030028
Submission received: 15 May 2023 / Revised: 3 July 2023 / Accepted: 6 July 2023 / Published: 10 July 2023

Abstract

:
Many tools of clinical medicine, such as clinical chemistry and diagnostic imaging, are prioritized for clinical diagnosis over post mortem diagnosis. Indeed, it is reasonable that the assessment of a patient’s functional status should take priority over the post mortem, cross-sectional use of diagnostic tests and laboratory equipment. In addition, these tools are sometimes expensive, and their use does not always have a reasonable cost–benefit ratio. However, some post mortem observations, such as inflammation, pulmonary edema, or infiltration and cerebral swelling, cannot be explained without using immunohistochemical markers for post mortem diagnosis. Introducing blood-based biomarkers into post mortem care could significantly reduce the rates of inconclusive post mortems and discrepancies in autopsy findings and clinical diagnoses. This is particularly relevant in relation to vascular pathology, considering the significant burden that vascular diseases represent for overall mortality. Expanding traditional autopsies with blood-based (circulating) biomarkers to avoid invasive post mortem examination would have cultural, religious, and potentially economic advantages. All of the target molecules were discussed in the context of the processes they up-regulate or down-regulate, which turned out to be the final cause of death. Ultimately, it is evident that further studies are needed to provide concrete validation for using a combination of markers for each case to reach a post mortem diagnosis with or without clinical records.

1. Introduction

Biomarkers found in bodily fluids may represent the active disease process or the patient’s reaction to that disease [1]. Moreover, they can act as an alternative measure of outcomes to assess the efficacy of therapy. According to common wisdom, a biomarker is a protein, enzyme, or cytokine with discriminatory value in clinical care [2,3]. A variety of molecules have been evaluated, and although post mortem biomarkers and a multimarker strategy are best investigated in the light of sudden cardiac death and agonal cardiac function [4,5], their significant potential in relation to peripheral vasculature is yet to be addressed [1,6]. All biomarkers must meet certain criteria to constitute a surrogate endpoint, or to be able to predict a clinically relevant endpoint, such as the loss of vision or a decrease in quality of life. In addition, the effect of a proposed treatment on the surrogate must capture the effect of the treatment on the clinically relevant endpoint [7,8].
This information should be considered in the context of the fact that autopsies face a number of challenges; for example, the lack of regulation for governmental funding for hospital-based autopsies, or hospitals rejecting autopsies requested by families [9]. In any case, autopsy numbers have fallen significantly worldwide (Figure 1) [10,11,12,13,14], and the accessibility of post mortem healthcare is uneven [15]. It is necessary to improve these statistics and also to address the major problem of discrepancies between clinical diagnosis and initial autopsy findings regarding the panel of clinical biomarkers. This discrepancy ranges from 7.2% in a 1993 study by Stambouly et al. to 64% in Mitrovic et al., 2019 [16,17].
Compelling grounds for this review was improving the standard of post mortem healthcare. The use of biomarkers as a replacement or addition to traditional autopsy (TA) should help in dodging the huge number of inconclusive or discrepant autopsies. Duly, the data known at present on blood biomolecules, which make it possible to determine the cause of death, will be reviewed, and minimally invasive approaches to postmortems will be tackled. Thus, invasive procedures that require the full opening of the body when performing an autopsy may be avoided [18,19,20].

2. Traditional Post Mortem Healthcare

Despite its discrepancies with clinical records, autopsy remains the gold standard as the ultimate diagnostic procedure [21,22]. Although these discrepancies have decreased significantly over time, in 2010 their rate remained high [23]; in the “post-COVID” era, the rate has reached an unprecedented 42% [24]. This renders between one in two and one in three autopsies superfluous.
Our knowledge about normal circulation stems entirely from thorough post mortem dissection [25]. More than 40 years ago, in a series of 500 clinical autopsies, vascular disorders were found to account for 25.2% of anatomopathological diagnoses [26]. These figures were more or less the same in osteoarthritis/rheumatoid arthritis research from 2015 [27]. Data from the Eurostat indicate the same phenomenon: diseases of the circulatory system are the main cause of death in the EU and were responsible for almost 37% of all deaths in 2017 [28,29]. A biomarker may be a recording taken from an individual, an imaging test, or a biosample.
Earle et al. recently presented data on the cause of death in patients with a risk of pulmonary embolism (PE), and their figures are instructive [30]; PE was excluded using clinical decision-making rules in combination with a D-dimer assay (the D-dimer is so named because two D fragments of the fibrin protein are joined by a cross-link) [31]. A lack of circulating oxygen, altered enzymatic reactions, cellular degradation, and the cessation of the anabolic production of metabolites all caused extensive biochemical changes in all body tissues post mortem [32]. Aside from its implications for PE, the value of D-dimer as a biomarker was revealed during the coronavirus disease 2019 (COVID-19) pandemic, when it was used to assess patients for disease severity and mortality in a case–control study [33].
Etymologically, the term “biomarker” comes from the Greek form βιο-, from βίος, meaning life, and the Old English word meaning a mark [34,35]. Bearing in mind this Greek root, using the word ‘life’ in the context of a post mortem may seem slightly incongruous. This was the case until recently, when the COVID-19 pandemic brought about a radical shift in routine post mortem practice [36].

3. Options for Traditional Autopsy

Traditional autopsy may be criticized in the media, but it is an important tool for both criminal investigations and healthcare quality control. For this reason, minimally invasive alternatives to traditional autopsies are continuously emerging. Imaging and “verbal autopsy” (VA) were shown in a large series to be promising techniques compared with a full autopsy [37,38,39,40] (Figure 2). Various objective factors influence the autopsy rate, though it is less likely to be requested for deaths in the emergency department or on general surgery wards, and it is most likely to be requested for fetal, medicine-related, cardiothoracic surgery-related, and pediatric deaths [41]. Nevertheless, most countries globally do not report high autopsy rates (less than 70% of all-cause mortality) [42].
While the cost of electronic data systems and the long wait between data collection and analysis appear to be the main disadvantages of verbal autopsies, post mortem imaging is hampered by a lack of direct visualization of the soft tissue, as well as postmortem artifacts that obscure the natural causes of death and can be misinterpreted as antemortem pathologies [40,43]. However, VA has been preferred recently in the COVID-19-related pandemic context, with a satisfying effect [44]. Additionally, it is not invasive procedure, so it does not require the opening of the body when performing an autopsy [18,19,20]. Trained interviewers can use a questionnaire to interview the caregivers of the deceased. Due to its non-contact nature, the World Health Organization’s (WHO’s) declaration of COVID-19 as a pandemic constituted an opportunity to make use of the VA technique [45,46].
For deaths that occur outside the health system, health information and a description of the events preceding death are included in the VA. It was first used in a public health project concerning the relationships between nutrition, infection, and child development in India [47]. Nowadays, this method has been improved and augmented so that it yields suitably complete death certificates and ultimately estimates cause-specific mortality. Specifically, VA means the collection of anamnestic data through an in-person interview with a close relative or caregiver of a deceased. The interview takes place within a short time of death; these data include symptoms, signs, and circumstances prior to death [48]. In settings where most deaths are otherwise undocumented, which typically means in low- and middle-income countries, VA attempts to establish causes of death, allowing scientists to analyze disease patterns and direct public health policy decisions. The body of relevant literature reports that the specificity of the VA is commonly found to be higher than sensitivity [49]. Additionally, the negative predictive value (NPV) was higher than the positive predictive one [50]. When assessing the cost of VA in rural India, the total cost per death was USD 16.66 [51]. The annual cost for the whole population included in the study in year 1 was USD 24,943, inclusive of training. The average annual cost to run the system each year was USD 18104, and the cost per death was USD 12 for the next 3 years. Costs were reduced by using single-physician reviews and shortened re-training sessions.
In agreement with contemporary attainments, even conducting an autopsy can be transferred to a computerized environment, and digital tools can be employed. Accordingly, another accessible and recently developed modality of postmortem healthcare is a radiographic examination of the body after death—postmortem radiology. As much as they provide a strong complementary tool to the TA, imaging techniques used in everyday clinical work are applied to post mortem processing [43]. In cases where forensic radiology plays a primary ancillary role in the post mortem, this directs forensic pathologists to specific screening tests [52,53]. Various imaging techniques can be considered relatively reliable when the patient in the medicolegal setting needs to be assessed. For instance, post mortem cardiac magnetic resonance imaging offers a better insight into the cardiovascular diseases responsible for sudden cardiac death (SCD) [54]. Forensic pathologists can benefit from these tools, even when an autopsy, fluid analysis, and DNA sampling are required [55,56]. In most countries, at minimum post mortem Computed Tomography (PMCT) imaging is regarded as accessible, reproducible, reliable, and easy to implement.
The explicit potential economic benefits of the PMCT (magnetic resonance imaging—MRI) have not been assessed recently [38,57]; despite its numerous advantages, this method still exhibits the problem of a significant rate of diagnostic discrepancies [58,59]. Nevertheless, PMCT has 79% sensitivity and 92.1% specificity for the detection of the source of bleeding [60]. In another study, where MRI and ultrasound (US) were used as imaging modalities, no significant difference in the rates of agreement was reported [61]. A study that assessed the diagnostic accuracy of post mortem imaging claimed that the mean cost of TA was 70% more expensive; as such, having post mortem imaging available would leave the institution performing the autopsy with more funds [62].

4. Post Mortem Biomarkers

Biomarkers provide plenty of information for enhancing all aspects of vascular homeostasis through vascular beds [1]. Biomarkers are characteristic indicators of disease, a disease state, or disease progression. They were at first described as a “measurable and quantifiable biological parameter that could serve as an index for health assessment” and were ultimately defined as “a characteristic that is objectively measured as an indicator of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention” [63,64].
The post mortem period involves events such as autolysis or decay, and biomarkers found in bodily fluids may represent the progression of the active disease or a reaction to the disease. Therefore, the value of post mortem biomarkers should be evaluated with this in mind, even if their efficacy is clinically confirmed [65]. This compounds the value of clinical post mortem studies as not only a method of control but also a means of improving teaching methods in hospitals [13]. The augmentation of post mortems with blood-based (circulating) biomarkers, in order to avoid invasive autopsies, would have cultural, religious, and potentially economic benefits [38,57,66].
In fact, no contemporary studies compare the costs of the various post mortem optional modalities.

5. Biomarkers of Vascular Quiescence

Endothelial quiescence and normality are important for disease resistance. Circulating blood-based biomarkers are simply signs of organ-specific signaling pathways [67]. The vascular system has a resting layer of endothelial cells (EC) that does not divide. Moreover, this layer of long-lived cells of the mesodermal lineage, which line the inside of all blood vessels, forms a single layer of organotypically differentiated cells [68]. This is known as vascular quiescence, and little is known about how the body achieves and maintains it.

5.1. Circulating Markers of the Extracellular Matrix: Biomarkers Related to the Vascular Wall

Collagen fragmentation is typically found in abdominal aortic aneurysm (AAA) biopsies as an indicator of new types I and III collagen synthesis [69]. AAA is interesting in the context of post mortems since it bears the risk of a rupture or a dissection—life-threatening conditions with high mortality rates [70,71]. This mortality is about 25% at 6 h and rises to 50% by 24 h; this can be compared to the rates of 40–70% in cases of sepsis [72,73]. Therefore, the search for highly sensitive and specific biomarkers for AAA should be equally focused.
Both the carboxy-terminal and amino-terminal ends of the precursor molecule are released during collagen synthesis, and fragments represent candidate biomarkers. A larger study and confirmation of clinical validity in a larger cohort is needed to link these molecules to AAA. In that regard, another candidate biomarker that has been suggested is tenascin-X, due to its involvement in Ehlers–Danlos syndrome. AAA patients showed elevated serum levels compared to controls [74,75]. Considering that serum elastin peptide (SEP) is a degradation product of elastin, its role as a biomarker has been shifted from sepsis to the extracellular matrix in vascular quiescence [76,77].
Furthermore, the examination of the wall of aortic aneurysms has demonstrated medial arterial destruction, the accumulation of inflammatory cells, the fragmentation of elastin, increased concentrations of proteolytic cytokines, and an in situ thrombus [78]. As such, some additional enzymes, proteins, and cytokines have been explored in relation to this finding. This approach has most often been limited by the fact that all these features represent the end-stage of AAA development, and may not be indicative of the factors that initiate AAA development or stimulate AAA growth.
The fragmentation of the extracellular matrix implies the involvement of elastases and matrix metalloproteinases (MMPs) in the pathophysiology of AAAs. As AAAs are a setting for the abundant expression of the MMP-9, it is considered to play a pivotal role in their formation. Therefore, this enzyme was explored as a possible biomarker for the presence of AAA in case–control studies. Patients with AAA demonstrated elevated concentrations of circulating MMP-9 [79]. The possible use of elastases as serum biomarkers of extracellular matrix remodeling is the basis of some studies involving alpha-1 antitrypsin or p-elastase [80,81,82]. However, the short half-life of active MMP-9 implies that any active MMP-9 in the serum may have a more immediate origin, so this information could be relevant to clinical forensic scientists [83].
Higher MMP-9 levels are associated with plaque vulnerability in carotid artery atherosclerosis [84]. This is the result of an interaction between modified lipids, the extracellular matrix, macrophages, and activated vascular smooth muscle cells (VSMCs). Inflammation, lipid accumulation, apoptosis, thrombosis, angiogenesis, and proteolysis all take part in the evolution of atherosclerotic lesions, as these processes are linked to the morphological characteristics of an unstable plaque. Therefore, the search for a biomarker has focused on these processes [85]. The interplay of vascular wall remodeling and carotid pathology was first hinted at by Makita et al., who drew a link between CRP levels with the carotid intima–media complex thickness and plaque formation [86]. Today, there is a link between obesity in children and adolescents and MMP-9 [82,87]. On the other hand, decreases in MMP-3 and MMP-9 have been reported after successful endovascular repair [88,89]. However, these data have highly limited post mortem significance.
Biomarkers are actively sought out for diseases that damage society in developed countries (e.g., dementia, renal and cardiovascular disease, and most malignancies). Unfortunately, all the studies on this topic have involved small numbers of patients and similar numbers of control subjects [90,91]. Finding appropriately matched controls is a real challenge that decreases the odds of clinical validation. This is most often the case when aortic wall tissue is used in proteomics; it is difficult to obtain a normal-aged aorta to use as a control. Even if such tissue is obtained, the method and timing of its harvest and preservation will modify its protein expression.

5.2. Proteins Associated with Vascular Lumen: Inflammation and Thrombosis Biomarkers

Whether as the final product or an outgrowth of the signaling pathway of degradation, markers of inflammation in vascular disease include cell adhesion molecules, cytokines, pro-atherogenic enzymes, and CRP [82,92]. Biomarkers used to identify thrombosis are unlikely to translate into a universal clinical tool; conversely, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and procalcitonin (PCT) are often used [93]. Moreover, hyperhomocysteinemia has been identified as an indicator of oxidant stress and a significant cardiovascular risk factor [94,95], although this association is weak.
The principal markers that have been evaluated are fibrinogen, D-dimer, homocysteine, and CRP, the elevation of which is intimately linked to other inflammatory cytokines, including interleukins (ILs; e.g., IL-6) and macrophage activation [96,97]. Assessing protein complexes embedded in the coagulation cascade and CRP levels, which are elevated in large aneurysms, covers both processes [98]. CRP levels decrease quickly, with a half-life of about 19 h [99].
Out of all the acute-phase proteins, CRP is the most commonly investigated biomarker in vascular pathology. Its specific role is to activate the complement cascade in cell death [100], and it is inextricably linked to other inflammatory cytokines [97]. One such cytokine is IL-6, which was confirmed to be a product of AAA [101]. It is even present in uncomplicated thoracic aortic aneurysms, since the C-reactive protein/interleukin-6 ratio may be a marker of the size of the aneurysms [102]. Additionally, plasma IL-6 has been correlated with aortic diameter in patients without AAA [6].
Combined with CRP, PCT was tested as a biomarker for sepsis [103]. In terms of the diagnostic accuracy of using CRP as a marker for sepsis, the overall area under the summary receiver operator characteristic (SROC) curve was 0.73 (95% confidence interval (CI), 0.69–0.77), with a sensitivity and specificity of 0.80 (95% CI, 0.63–0.90) and 0.61 (95% CI, 0.50–0.72), respectively; the DOR was 6.89 (95% CI, 3.86–12.31). In terms of the diagnostic accuracy of using PCT for sepsis, the overall area under the SROC curve was 0.85 (95% CI, 0.82–0.88), with a sensitivity and specificity of 0.80 (95% CI, 0.69–0.87) and 0.77 (95% CI, 0.60–0.88), respectively, and the DOR was 12.50 (95% CI, 3.65–42.80) [104,105].
The molecular basis of blood coagulation first attracted attention in the search for blood-based biomarkers due to a plasma fibrinogen concentration that was positively correlated with the AAA diameter [106]. Nonetheless, its elevated plasma concentrations are induced by smoking, so the association can only be linked to the “black box” of smoking [107]. Due to various functional interactions, fibrinogen plays a crucial role in hemostasis. Specifically, it is a substrate for three major enzymes: thrombin, plasmin, and factor XIIIa [106].
As the clotting slows down, the clot breaks down and, together with the fibrin net, it ultimately dissolves. With this dissolution, fragments of protein are released into the bloodstream. One such specific fragment, which is formed only upon the degradation of cross-linked fibrin, is D-dimer [108]. Plasma concentrations of D-dimer show fibrin turnover in the circulation and are ultimately related to subsequent mortality from any cause [109]. Most importantly, the D-dimer level is a validated assay that is routinely used in general clinical practice to exclude a diagnosis of deep vein thrombosis (DVT) [110]. The current serum levels of D-dimer are directly proportional to recent fibrinolytic activity, as the half-life of D-dimer is four to six hours, and its levels stay elevated for about seven days [111]. This information could have great forensic value in the context of defining the time of death or establishing a chronological timeline [112]. Hence, the measurement of post mortem D-dimer may lead to a certain practical improvement in current post mortem healthcare.
The currently available D-dimer assays are not standardized and it is unclear whether these differences have an impact. On the other hand, these tests are rapid, simple, and inexpensive [113]. Therefore, to explore the differences between D-dimer assays and their impact on the diagnostic outcome, a prospective multicenter cohort outcome study evaluating 3462 patients with suspected PE (the YEARS study) was conducted. Four different D-dimer assays were used, and the median D-dimer concentrations differed significantly between the assays. The sensitivity, specificity, positive predictive value (PPV), and NPV for the detection of PE of all four assays were determined, using a cutoff level of 1000 ng/mL [31]. In post mortem blood, an immunochromatographic SERATEC PMB test was used [114]. This test targets human hemoglobin and D-dimer simultaneously, so it is used in forensic inquests for menstrual and peripheral blood spatters [115].
CRP and D-dimer are of significant interest, as they are widely used in clinical work [116]. While the role of both of these molecules as candidate biomarkers in clinical work has been explored, their use in post mortem processing is more a matter of the pathologist’s discretion.

6. Vascular Cognitive Impairment: Room for Biomarkers at Post Mortem

Vascular cognitive impairment (VCI) is a term used to encompass the entire spectrum of cognitive disorders related to the mental abilities of awareness, thinking, and feeling. It is associated with a variety of cerebral vascular brain injuries. VCI symptoms can range from forgetfulness to more serious problems with attention, memory, language, and executive functions such as problem solving. Cerebrovascular disease (CeVD) and neurodegenerative forms of dementia, such as Alzheimer’s disease (AD), are frequently associated comorbidities in the elderly, with similar risk factors and pathophysiological mechanisms, including neuroinflammation [117].
As an inflammatory marker that is upregulated in vascular diseases, as well as in AD, protein secreted to plasma (i.e., osteopontin (OPN)) has been tested as a biomarker of AD and VCI [118,119]. OPN’s involvement in lipid metabolism likely explains its role in conditions that fall under the spectrum of VCI. Moreover, among its numerous functions, OPN has emerged as an important potential biomarker for diagnosing and monitoring the treatment of cancer (including melanoma, breast, lung, gastric, and ovarian cancers) and other conditions [120,121].
Potentially relevant to practitioners is the fact that, by neutralizing OPN with various therapeutic antibody modalities, it is possible to conclude that the half-life of OPN differs depending on the antibody ligand interactions, pH, or “sweeper” used. The calculated half-lives for these four proteins range from 5 to 15 h [122].

7. Applying Clinical Biomarkers in a Post Mortem Setting

Applying clinical biomarkers in a post mortem setting does not violate the medicolegal requirements for death investigations. Nevertheless, instead of limiting the contents of the death investigation toolbox, biomarkers could be used to decrease the rate of clinical–autopsy discrepancies and to reduce post mortem healthcare inequalities [12,123,124].
At the time of this review, only a few countries had published data for both the autopsy rate and gross national product (GNP), so the correlation between the number of autopsies and GNP was weak and negative (r2 = −0.38; p = 0.004). Subject discrepancies were minimized over time and then increased significantly in the last few years [24,125]. One recent study found that there was no significant difference in treatment time between hemorrhagic and ischemic lesions seen later at brain autopsy (unpublished data [126]).
Predominately as a consequence of the decline in rates of clinical (hospital) autopsies, overall autopsy rates have declined in recent decades in many high-income countries [127]. This negative trend has been attributed to various factors such as costs, a lack of medical education, the development of new clinical diagnostic tools, medical malpractice implications, and difficulties in obtaining permission from relatives [128]. Even if performed, autopsies tend to be negative, failing to produce findings that reveal the cause of death. On the other hand, studies show substantial discrepancies between autopsy results and pre-mortal clinical diagnoses [21,129]. This is most clearly visible in the global autopsy rates in all-cause mortality, part of the World Health Organization’s (WHO’s) annual statistics [10,11]. Paratz et al. reported that these rates ranged from 0.01% to 83.9%, based on the data from the few countries—less than one-third worldwide—that report autopsy rates [42]. Their statistics are mostly derived from academic journals, rather than governmental data.
Healthcare practices have come a long way in reducing mortality, but the decreasing number of TAs demonstrates the need for a feasible alternative. Nonetheless, any form of post mortem investigative tool can provide additional information or a change in diagnosis regarding the cause of death in a great number of cases, either because of discrepancies between the clinical and autopsy diagnoses or through inconclusive autopsies. In order to maintain the viability of academic departments involved in post mortem care and to increase consent in post mortem investigations, a panel of noninvasive biomarkers is given in Table 1.

8. Conclusions

Autopsies are still needed for the determination and correction of causes of death, even in “clear-cut” cases. Moreover, post mortem sample handling and analysis are challenges that need to be addressed, as they can produce variability in the findings; for this reason, validation with biomarkers is of key importance. There are some limitations to this review because no published large-scale study has considered post mortem human blood samples. The risks of bias includes the inability to verify the reported figures, heterogeneity in the reporting of clinical versus medicolegal autopsies, and the limited number of studies specifically concerning overall vascular pathology.
Considering the half-lives of all the candidate molecules discussed in this review, it is not likely that any of these molecules will see wider usage. However, each of the highlighted markers could prove useful in confirming or ruling out a cause of death in cases of witnessed deaths or in situations where TA is not an option. In conclusion, further work is required in the search for a new candidate molecule.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Available on request.

Acknowledgments

This author acknowledges the University of Rijeka, Faculty of Medicine, for their constant support.

Conflicts of Interest

The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Nordon, I.M.; Hinchliffe, R.J. Biomarkers in Vascular Disease. In Mechanisms of Vascular Disease: A Reference Book for Vascular Specialists [Internet]; University of Adelaide Press: Adelaide, Australia, 2011. [Google Scholar]
  2. Cui, Z.; Zhao, G.; Liu, X. Blood fibrinogen level as a biomarker of adverse outcomes in patients with coronary artery disease: A systematic review and meta-analysis. Medicine 2022, 101, e30117. [Google Scholar] [CrossRef] [PubMed]
  3. Davis, K.D.; Aghaeepour, N.; Ahn, A.H.; Angst, M.S.; Borsook, D.; Brenton, A.; Burczynski, M.E.; Crean, C.; Edwards, R.; Gaudilliere, B.; et al. Discovery and validation of biomarkers to aid the development of safe and effective pain therapeutics: Challenges and opportunities. Nat. Rev. Neurol. 2020, 16, 381–400. [Google Scholar] [CrossRef] [PubMed]
  4. Kutlu, E.; Cil, N.; Avci, E.; Bir, F.; Kilic, I.D.; Dereli, A.K.; Acar, K. Significance of postmortem biomarkers and multimarker strategy in sudden cardiac death. Leg. Med. 2023, 61, 102212. [Google Scholar] [CrossRef] [PubMed]
  5. Cao, Z.; Zhao, M.; Xu, C.; Zhang, T.; Jia, Y.; Wang, T.; Zhu, B. Evaluation of Agonal Cardiac Function for Sudden Cardiac Death in Forensic Medicine with Postmortem Brain Natriuretic Peptide (BNP) and NT-proBNP: A Meta-analysis. J. Forensic. Sci. 2020, 65, 686–691. [Google Scholar] [CrossRef] [PubMed]
  6. Puchenkova, O.A.; Soldatov, V.O.; Belykh, A.E.; Bushueva, O.; Piavchenko, G.A.; Venediktov, A.A.; Shakhpazyan, N.K.; Deykin, A.V.; Korokin, M.V.; Pokrovskiy, M.V. Cytokines in Abdominal Aortic Aneurysm: Master Regulators With Clinical Application. Biomark. Insights 2022, 17, 11772719221095676. [Google Scholar] [CrossRef]
  7. Medeiros, F.A. Biomarkers and Surrogate Endpoints: Lessons Learned From Glaucoma. Investig. Ophthalmol. Vis. Sci. 2017, 58, BIO20–BIO26. [Google Scholar] [CrossRef] [Green Version]
  8. Vlachopoulos, C.; Xaplanteris, P.; Aboyans, V.; Brodmann, M.; Cifkova, R.; Cosentino, F.; De Carlo, M.; Gallino, A.; Landmesser, U.; Laurent, S.; et al. The role of vascular biomarkers for primary and secondary prevention. A position paper from the European Society of Cardiology Working Group on peripheral circulation: Endorsed by the Association for Research into Arterial Structure and Physiology (ARTERY) Society. Atherosclerosis 2015, 241, 507–532. [Google Scholar] [CrossRef] [Green Version]
  9. Basso, C.; Stone, J.R. Autopsy in the era of advanced cardiovascular imaging. Eur. Heart J. 2022, 43, 2461–2468. [Google Scholar] [CrossRef]
  10. (WHO), W.H.O. Autopsy Rate (%) for All Deaths. Available online: https://gateway.euro.who.int/en/indicators/hfa_545-6410-autopsy-rate-for-all-deaths/ (accessed on 3 May 2023).
  11. (WHO), W.H.O. Autopsy Rate (%) for Hospital Deaths. Available online: https://gateway.euro.who.int/en/indicators/hfa_544-6400-autopsy-rate-for-hospital-deaths/ (accessed on 3 May 2023).
  12. Waidhauser, J.; Martin, B.; Trepel, M.; Markl, B. Can low autopsy rates be increased? Yes, we can! Should postmortem examinations in oncology be performed? Yes, we should! A postmortem analysis of oncological cases. Virchows Arch. 2021, 478, 301–308. [Google Scholar] [CrossRef]
  13. Bunei, M.; Muturi, P.; Otiato, F.; Njuguna, H.N.; Emukule, G.O.; Otieno, N.A.; Dawa, J.; Chaves, S.S. Factors Influencing Acceptance of Post-Mortem Examination of Children at a Tertiary Care Hospital in Nairobi, Kenya. Ann. Glob. Health 2019, 85, 95. [Google Scholar] [CrossRef] [Green Version]
  14. Rosendahl, A.; Mjörnheim, B.; Eriksson, L.C. Autopsies and quality of cause of death diagnoses. SAGE Open Med. 2021, 9, 20503121211037169. [Google Scholar] [CrossRef] [PubMed]
  15. Lawrence, S.; Namusanya, D.; Hamuza, A.; Huwa, C.; Chasweka, D.; Kelley, M.; Molyneux, S.; Voskuijl, W.; Denno, D.M.; Desmond, N. Hypothetical acceptability of hospital-based post-mortem pediatric minimally invasive tissue sampling in Malawi: The role of complex social relationships. PLoS ONE 2021, 16, e0246369. [Google Scholar] [CrossRef] [PubMed]
  16. Stambouly, J.J.; Kahn, E.; Boxer, R.A. Correlation between clinical diagnoses and autopsy findings in critically ill children. Pediatrics 1993, 92, 248–251. [Google Scholar] [CrossRef]
  17. Mitrovic, D.; Savic, I.; Jankovic, R. Discrepancies between clinical and autopsy diagnosis of cause of death among psychiatric patients who died due to natural causes. A retrospective autopsy study. Vojnosanit. Pregl. 2019, 76, 278–283. [Google Scholar] [CrossRef] [Green Version]
  18. Herath, J.C.; Herath, S.O. Is it time for targeted and minimally invasive post-mortem examination using total body computed tomography in a medicolegal autopsy? Forensic Sci. Med. Pathol. 2021, 17, 175–176. [Google Scholar] [CrossRef] [PubMed]
  19. Mercala, E.; Benbow, E.W. Autopsy by Imaging: The Last 10 Years. Forensic Sci. 2022, 2, 696–714. [Google Scholar] [CrossRef]
  20. Ferencic, A.; Stemberger, C.; Cuculić, D.; Jakovac, H. Autopsies during COVID-19 pandemic—Caution is never too much: Postmortem detection of SARS-CoV-2 in the severely burned and carbonized bodies. Indian J. Pathol. Microbiol. 2022, 65, 959–960. [Google Scholar] [CrossRef] [PubMed]
  21. Kurz, S.D.; Sido, V.; Herbst, H.; Ulm, B.; Salkic, E.; Ruschinski, T.M.; Buschmann, C.T.; Tsokos, M. Discrepancies between clinical diagnosis and hospital autopsy: A comparative retrospective analysis of 1112 cases. PLoS ONE 2021, 16, e0255490. [Google Scholar] [CrossRef]
  22. Buja, L.M.; Barth, R.F.; Krueger, G.R.; Brodsky, S.V.; Hunter, R.L. The Importance of the Autopsy in Medicine: Perspectives of Pathology Colleagues. Acad. Pathol. 2019, 6, 2374289519834041. [Google Scholar] [CrossRef] [Green Version]
  23. van den Tweel, J.G.; Wittekind, C. The medical autopsy as quality assurance tool in clinical medicine: Dreams and realities. Virchows Arch. 2016, 468, 75–81. [Google Scholar] [CrossRef] [Green Version]
  24. Rodrigues, F.S.; Oliveira, I.C.; Cat, M.N.L.; Mattos, M.C.L.; Silva, G.A. Agreement between Clinical and Anatomopathological Diagnoses in Pediatric Intensive Care. Rev. Paul. Pediatr. 2021, 39, e2019263. [Google Scholar] [CrossRef] [PubMed]
  25. Thiene, G.; Saffitz, J.E. Autopsy as a Source of Discovery in Cardiovascular Medicine: Then and Now. Circulation 2018, 137, 2683–2685. [Google Scholar] [CrossRef] [PubMed]
  26. Bombi, J.A.; Llebaria, C.; Rives, A. Analysis of a series of 500 clinical post mortem studies. II. Basic diagnosis (author’s transl). Med. Clin. 1981, 77, 185–189. [Google Scholar]
  27. Smith, A.M.; Lingard, L.; Heslop, P.; Gray, J.; Walker, D.J. Vascular disease as a cause of death in patients with severe disability due to osteoarthritis and rheumatoid arthritis. Springerplus 2015, 4, 328. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Petersen, S.; Rayner, M.; Leal, J.; Luengo-Fernandez, R.; Gray, A. European Cardiovascular Disease Statistics; British Heart Foundation: Glasgow, UK, 2000. [Google Scholar]
  29. EUROSTAT. Causes of Death Statistics. Available online: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Causes_of_death_statistics (accessed on 3 May 2023).
  30. Earle, W.; Misra, S.; Herzig, M.; Abdallah, G.; Ross, C.D.; Secemsky, E.A.; Carroll, B. Cause of Death Analysis in Patients with Intermeditate Risk Acute Pulmonary Embolism. J. Am. Coll. Cardiol. 2023, 81, 2088. [Google Scholar] [CrossRef]
  31. Hamer, H.M.; Stroobants, A.K.; Bavalia, R.; Ponjee, G.A.E.; Klok, F.A.; van der Hulle, T.; Huisman, M.V.; Hendriks, H.A.; Middeldorp, S. Diagnostic accuracy of four different D-dimer assays: A post-hoc analysis of the YEARS study. Thromb. Res. 2021, 201, 18–22. [Google Scholar] [CrossRef]
  32. Donaldson, A.E.; Lamont, I.L. Biochemistry changes that occur after death: Potential markers for determining post-mortem interval. PLoS ONE 2013, 8, e82011. [Google Scholar] [CrossRef] [Green Version]
  33. Yao, Y.; Cao, J.; Wang, Q.; Shi, Q.; Liu, K.; Luo, Z.; Chen, X.; Chen, S.; Yu, K.; Huang, Z.; et al. D-dimer as a biomarker for disease severity and mortality in COVID-19 patients: A case control study. J. Intensive Care 2020, 8, 49. [Google Scholar] [CrossRef]
  34. Aronson, J.K. When I use a word.... Too much healthcare—Biomarkers. BMJ 2022, 379, o2533. [Google Scholar] [CrossRef]
  35. Aronson, J.K.; Ferner, R.E. Biomarkers-A General Review. Curr. Protoc. Pharmacol. 2017, 76, 9–23. [Google Scholar] [CrossRef]
  36. Solarino, B.; Ferorelli, D.; Dell’Erba, A. Post-mortem routine practice in the era of the COVID-19 pandemic. J. Forensic. Leg. Med. 2020, 74, 102010. [Google Scholar] [CrossRef] [PubMed]
  37. Roberts, I.S.; Benamore, R.E.; Benbow, E.W.; Lee, S.H.; Harris, J.N.; Jackson, A.; Mallett, S.; Patankar, T.; Peebles, C.; Roobottom, C.; et al. Post-mortem imaging as an alternative to autopsy in the diagnosis of adult deaths: A validation study. Lancet 2012, 379, 136–142. [Google Scholar] [CrossRef] [Green Version]
  38. Blokker, B.M.; Wagensveld, I.M.; Weustink, A.C.; Oosterhuis, J.W.; Hunink, M.G. Non-invasive or minimally invasive autopsy compared to conventional autopsy of suspected natural deaths in adults: A systematic review. Eur. Radiol. 2016, 26, 1159–1179. [Google Scholar] [CrossRef] [Green Version]
  39. Wichmann, D.; Obbelode, F.; Vogel, H.; Hoepker, W.W.; Nierhaus, A.; Braune, S.; Sauter, G.; Pueschel, K.; Kluge, S. Virtual autopsy as an alternative to traditional medical autopsy in the intensive care unit: A prospective cohort study. Ann. Intern. Med. 2012, 156, 123–130. [Google Scholar] [CrossRef]
  40. Flaxman, A.D.; Stewart, A.; Joseph, J.C.; Alam, N.; Alam, S.S.; Chowdhury, H.; Mooney, M.D.; Rampatige, R.; Remolador, H.; Sanvictores, D.; et al. Collecting verbal autopsies: Improving and streamlining data collection processes using electronic tablets. Popul. Health Metr. 2018, 16, 3. [Google Scholar] [CrossRef] [Green Version]
  41. Sinard, J.H. Factors affecting autopsy rates, autopsy request rates, and autopsy findings at a large academic medical center. Exp. Mol. Pathol. 2001, 70, 333–343. [Google Scholar] [CrossRef] [PubMed]
  42. Paratz, E.D.; Rowe, S.J.; Stub, D.; Pflaumer, A.; La Gerche, A. A systematic review of global autopsy rates in all-cause mortality and young sudden death. Heart Rhythm. 2023, 20, 607–613. [Google Scholar] [CrossRef] [PubMed]
  43. Michaud, K.; Jacobsen, C.; Basso, C.; Banner, J.; Blokker, B.M.; de Boer, H.H.; Dedouit, F.; O’Donnell, C.; Giordano, C.; Magnin, V. Application of postmortem imaging modalities in cases of sudden death due to cardiovascular diseases–current achievements and limitations from a pathology perspective. Virchows Archiv. 2023, 482, 385–406. [Google Scholar] [CrossRef]
  44. De Souza, P.M.M.; Gerson, G.; Dias, J.S.; De Melo, D.N.; De Souza, S.G.; Ruiz, E.M.; Fernandes Tavora, F.R.; Cavalcanti, L.P.D.G. Validation of verbal autopsy and nasopharyngeal swab collection for the investigation of deaths at home during the COVID-19 pandemics in Brazil. PLoS Neglected Trop. Dis. 2020, 14, e0008830. [Google Scholar] [CrossRef]
  45. Rosen, T.; Safford, M.M.; Sterling, M.R.; Goyal, P.; Patterson, M.; Al Malouf, C.; Ballin, M.; Del Carmen, T.; LoFaso, V.M.; Raik, B.L.; et al. Development of the Verbal Autopsy Instrument for COVID-19 (VAIC). J. Gen. Intern. Med. 2021, 36, 3522–3529. [Google Scholar] [CrossRef]
  46. Nasaruddin, N.H.; Ganapathy, S.S.; Awaluddin, S.M.; Anuar, M.F.M.; Binti Alias, N.; Mang, C.Y.; Wan-Fei, K. Conducting verbal autopsy by telephone interview during the pandemic to support mortality surveillance: A feasibility study in Malaysia. West. Pac. Surveill. Response J. 2022, 13, 8–14. [Google Scholar] [CrossRef] [PubMed]
  47. Singh, A. Childhood Malnutrition in India. In Perspective of Recent Advances in Acute Diarrhea; IntechOpen: London, UK, 2020. [Google Scholar]
  48. Caleo, G.; Sy, A.; Balandine, S.; Polonsky, J.; Palma, P.; Grais, R. The 2012 WHO verbal autopsy instrument. Lancet 2018, 12, 1–11. [Google Scholar]
  49. Thomas, L.M.; D’Ambruoso, L.; Balabanova, D. Verbal autopsy in health policy and systems: A literature review. BMJ Glob. Health 2018, 3, e000639. [Google Scholar] [CrossRef] [Green Version]
  50. Mahesh, B.P.K.; Hart, J.D.; Acharya, A.; Chowdhury, H.R.; Joshi, R.; Adair, T.; Hazard, R.H. Validation studies of verbal autopsy methods: A systematic review. BMC Public Health 2022, 22, 2215. [Google Scholar] [CrossRef]
  51. Joshi, R.; Praveen, D.; Jan, S.; Raju, K.; Maulik, P.; Jha, V.; Lopez, A.D. How much does a verbal autopsy based mortality surveillance system cost in rural India? PLoS ONE 2015, 10, e0126410. [Google Scholar] [CrossRef] [PubMed]
  52. Krehbiel, K.; Pinckard, J.K. The Toolbox Approach to Forensic Pathology. Acad. Forensic Pathol. 2015, 5, 534–547. [Google Scholar] [CrossRef]
  53. Yi-Li, G.W.; Lai, P.S.; Noor, M.H.M.; Chinna, K.; Ibrahim, M. Reliability of Post-Mortem Computed Tomography in Measuring Foramen Magnum Dimensions: A Pilot Study. Forensic Anthropol. 2023, 1–9. [Google Scholar] [CrossRef]
  54. Guidi, B.; Aquaro, G.D.; Gesi, M.; Emdin, M.; Di Paolo, M. Postmortem cardiac magnetic resonance in sudden cardiac death. Heart Fail. Rev. 2018, 23, 651–665. [Google Scholar] [CrossRef]
  55. Cartocci, G.; Santurro, A.; Neri, M.; Zaccagna, F.; Catalano, C.; La Russa, R.; Turillazzi, E.; Panebianco, V.; Frati, P.; Fineschi, V. Post-mortem computed tomography (PMCT) radiological findings and assessment in advanced decomposed bodies. Radiol. Med. 2019, 124, 1018–1027. [Google Scholar] [CrossRef] [Green Version]
  56. Filograna, L.; Manenti, G.; O’Donnell, C.; Floris, R.; Oliva, A. Potentials of post-mortem CT (PMCT) in paediatric cases related to SARS-CoV-2 infection. Forensic. Sci. Med. Pathol. 2023, 19, 289–290. [Google Scholar] [CrossRef]
  57. Hyde, G.; Rummery, R.; Whitby, E.H.; Bloor, J.; Raghavan, A.; Cohen, M.C. Benefits and Limitations of the Minimally Invasive Postmortem: A Review of an Innovative Service Development. Pediatr. Dev. Pathol. 2020, 23, 431–437. [Google Scholar] [CrossRef] [PubMed]
  58. Zech, W.D.; Jackowski, C.; Schwendener, N.; Brencicova, E.; Schuster, F.; Lombardo, P. Postmortem CT versus forensic autopsy: Frequent discrepancies of tracheobronchial content findings. Int. J. Legal. Med. 2016, 130, 191–198. [Google Scholar] [CrossRef] [Green Version]
  59. Mondello, C.; Baldino, G.; Bottari, A.; Sapienza, D.; Perri, F.; Argo, A.; Asmundo, A.; Ventura Spagnolo, E. The role of PMCT for the assessment of the cause of death in natural disaster (landslide and flood): A Sicilian experience. Int. J. Legal. Med. 2022, 136, 237–244. [Google Scholar] [CrossRef] [PubMed]
  60. Chatzaraki, V.; Thali, M.J.; Ampanozi, G. Diagnostic accuracy of postmortem computed tomography for bleeding source determination in cases with hemoperitoneum. Int. J. Legal. Med. 2021, 135, 593–603. [Google Scholar] [CrossRef] [PubMed]
  61. Shelmerdine, S.C.; Sebire, N.J.; Arthurs, O.J. Diagnostic accuracy of postmortem ultrasound vs. postmortem 1.5-T MRI for non-invasive perinatal autopsy. Ultrasound Obstet. Gynecol. 2021, 57, 449–458. [Google Scholar] [CrossRef] [Green Version]
  62. Thayyil, S.; Chandrasekaran, M.; Chitty, L.S.; Wade, A.; Skordis-Worrall, J.; Bennett-Britton, I.; Cohen, M.; Withby, E.; Sebire, N.J.; Robertson, N.J.; et al. Diagnostic accuracy of post-mortem magnetic resonance imaging in fetuses, children and adults: A systematic review. Eur. J. Radiol. 2010, 75, e142–e148. [Google Scholar] [CrossRef]
  63. Puntmann, V.O. How-to guide on biomarkers: Biomarker definitions, validation and applications with examples from cardiovascular disease. Postgrad. Med. J. 2009, 85, 538–545. [Google Scholar] [CrossRef]
  64. Bondareva, O.; Sheikh, B.N. Vascular Homeostasis and Inflammation in Health and Disease-Lessons from Single Cell Technologies. Int. J. Mol. Sci. 2020, 21, 4688. [Google Scholar] [CrossRef]
  65. Almulhim, A.M.; Menezes, R.G. Evaluation of Postmortem Changes; StatPearls Publishing: Treasure Island, FL, USA, 2020. [Google Scholar]
  66. O’Keefe, H.; Shenfine, R.; Brown, M.; Beyer, F.; Rankin, J. Are non-invasive or minimally invasive autopsy techniques for detecting cause of death in prenates, neonates and infants accurate? A systematic review of diagnostic test accuracy. BMJ Open 2023, 13, e064774. [Google Scholar] [CrossRef]
  67. Ricard, N.; Bailly, S.; Guignabert, C.; Simons, M. The quiescent endothelium: Signalling pathways regulating organ-specific endothelial normalcy. Nat. Rev. Cardiol. 2021, 18, 565–580. [Google Scholar] [CrossRef]
  68. Schlereth, K.; Weichenhan, D.; Bauer, T.; Heumann, T.; Giannakouri, E.; Lipka, D.; Jaeger, S.; Schlesner, M.; Aloy, P.; Eils, R.; et al. The transcriptomic and epigenetic map of vascular quiescence in the continuous lung endothelium. Elife 2018, 7, e34423. [Google Scholar] [CrossRef] [PubMed]
  69. Qian, G.; Adeyanju, O.; Olajuyin, A.; Guo, X. Abdominal Aortic Aneurysm Formation with a Focus on Vascular Smooth Muscle Cells. Life 2022, 12, 191. [Google Scholar] [CrossRef]
  70. Pal, D.; Szilagyi, B.; Berczeli, M.; Szalay, C.I.; Sardy, B.; Olah, Z.; Szekely, T.; Racz, G.; Banga, P.; Czinege, Z.; et al. Ruptured Aortic Aneurysm and Dissection Related Death: An Autopsy Database Analysis. Pathol. Oncol. Res. 2020, 26, 2391–2399. [Google Scholar] [CrossRef] [PubMed]
  71. Takada, M.; Yamagishi, K.; Tamakoshi, A.; Iso, H. Height and Mortality from Aortic Aneurysm and Dissection. J. Atheroscler. Thromb. 2022, 29, 1166–1175. [Google Scholar] [CrossRef] [PubMed]
  72. Levy, D.; Goyal, A.; Grigorova, Y.; Farci, F.; Le, J.K. Aortic Dissection. In StatPearls; StatPearls Publishing LLC.: Treasure Island, FL, USA, 2023. [Google Scholar]
  73. La Russa, R.; Maiese, A.; Viola, R.V.; De Matteis, A.; Pinchi, E.; Frati, P.; Fineschi, V. Searching for highly sensitive and specific biomarkers for sepsis: State-of-the-art in post-mortem diagnosis of sepsis through immunohistochemical analysis. Int. J. Immunopathol. Pharmacol. 2019, 33, 2058738419855226. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Imanaka-Yoshida, K.; Matsumoto, K.I. Multiple Roles of Tenascins in Homeostasis and Pathophysiology of Aorta. Ann. Vasc. Dis. 2018, 11, 169–180. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Brady, A.R.; Thompson, S.G.; Fowkes, F.G.; Greenhalgh, R.M.; Powell, J.T.; Participants, U.K.S.A.T. Abdominal aortic aneurysm expansion: Risk factors and time intervals for surveillance. Circulation 2004, 110, 16–21. [Google Scholar] [CrossRef] [Green Version]
  76. Pierrakos, C.; Velissaris, D.; Bisdorff, M.; Marshall, J.C.; Vincent, J.L. Biomarkers of sepsis: Time for a reappraisal. Crit. Care 2020, 24, 287. [Google Scholar] [CrossRef]
  77. Bown, M.J.; Sutton, A.J.; Bell, P.R.; Sayers, R.D. A meta-analysis of 50 years of ruptured abdominal aortic aneurysm repair. Br. J. Surg. 2002, 89, 714–730. [Google Scholar] [CrossRef]
  78. Rastogi, V.; Stefens, S.J.M.; Houwaart, J.; Verhagen, H.J.M.; de Bruin, J.L.; van der Pluijm, I.; Essers, J. Molecular Imaging of Aortic Aneurysm and Its Translational Power for Clinical Risk Assessment. Front. Med. 2022, 9, 814123. [Google Scholar] [CrossRef]
  79. Li, T.; Jiang, B.; Li, X.; Sun, H.Y.; Li, X.T.; Jing, J.J.; Yang, J. Serum matrix metalloproteinase-9 is a valuable biomarker for identification of abdominal and thoracic aortic aneurysm: A case-control study. BMC Cardiovasc. Disord. 2018, 18, 202. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  80. Bihlet, A.R.; Karsdal, M.A.; Sand, J.M.; Leeming, D.J.; Roberts, M.; White, W.; Bowler, R. Biomarkers of extracellular matrix turnover are associated with emphysema and eosinophilic-bronchitis in COPD. Respir. Res. 2017, 18, 22. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  81. Kristensen, J.H.; Karsdal, M.A.; Sand, J.M.; Willumsen, N.; Diefenbach, C.; Svensson, B.; Hagglund, P.; Oersnes-Leeming, D.J. Serological assessment of neutrophil elastase activity on elastin during lung ECM remodeling. BMC Pulm. Med. 2015, 15, 53. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Aragon-Vela, J.; Alcala-Bejarano Carrillo, J.; Moreno-Racero, A.; Plaza-Diaz, J. The Role of Molecular and Hormonal Factors in Obesity and the Effects of Physical Activity in Children. Int. J. Mol. Sci. 2022, 23, 15413. [Google Scholar] [CrossRef]
  83. Demestre, M.; Parkin-Smith, G.; Petzold, A.; Pullen, A.H. The pro and the active form of matrix metalloproteinase-9 is increased in serum of patients with amyotrophic lateral sclerosis. J. Neuroimmunol. 2005, 159, 146–154. [Google Scholar] [CrossRef]
  84. Silvello, D.; Narvaes, L.B.; Albuquerque, L.C.; Forgiarini, L.F.; Meurer, L.; Martinelli, N.C.; Andrades, M.E.; Clausell, N.; dos Santos, K.G.; Rohde, L.E. Serum levels and polymorphisms of matrix metalloproteinases (MMPs) in carotid artery atherosclerosis: Higher MMP-9 levels are associated with plaque vulnerability. Biomarkers 2014, 19, 49–55. [Google Scholar] [CrossRef]
  85. Beck-Joseph, J.; Lehoux, S. Molecular Interactions Between Vascular Smooth Muscle Cells and Macrophages in Atherosclerosis. Front. Cardiovasc. Med. 2021, 8, 737934. [Google Scholar] [CrossRef]
  86. Makita, S.; Nakamura, M.; Hiramori, K. The association of C-reactive protein levels with carotid intima-media complex thickness and plaque formation in the general population. Stroke 2005, 36, 2138–2142. [Google Scholar] [CrossRef] [Green Version]
  87. Andrade, C.; Bosco, A.; Sandrim, V.; Silva, F. MMP-9 Levels and IMT of Carotid Arteries are Elevated in Obese Children and Adolescents Compared to Non-Obese. Arq. Bras. Cardiol. 2017, 108, 198–203. [Google Scholar] [CrossRef]
  88. Antoniou, G.A.; Georgiadis, G.S.; Antoniou, S.A.; Murray, D.; Smyth, J.V.; Serracino-Inglott, F.; Paraskevas, K.I. Plasma matrix metalloproteinase 9 levels may predict endoleaks after endovascular aortic aneurysm repair. Angiology 2013, 64, 49–56. [Google Scholar] [CrossRef]
  89. Maguire, E.M.; Pearce, S.W.A.; Xiao, R.; Oo, A.Y.; Xiao, Q. Matrix Metalloproteinase in Abdominal Aortic Aneurysm and Aortic Dissection. Pharmaceuticals 2019, 12, 118. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  90. Kumarasamy, G.; Ismail, M.N.; Tuan, S.E.; Sharif, C.D.; Mittal, P.; Hoffmann, P.; Kaur, G. Conference Proceedings–6th International Conference on Molecular Diagnostics and Biomarker Discovery (MDBD 2022): Building Resilience in Biomedical Research. In Proceedings of the BMC Proceedings, Penang, Malaysia, 11–13 October 2022; p. 1. [Google Scholar]
  91. Palstrom, N.B.; Matthiesen, R.; Rasmussen, L.M.; Beck, H.C. Recent Developments in Clinical Plasma Proteomics-Applied to Cardiovascular Research. Biomedicines 2022, 10, 162. [Google Scholar] [CrossRef] [PubMed]
  92. Hong, L.Z.; Xue, Q.; Shao, H. Inflammatory Markers Related to Innate and Adaptive Immunity in Atherosclerosis: Implications for Disease Prediction and Prospective Therapeutics. J. Inflamm. Res. 2021, 14, 379–392. [Google Scholar] [CrossRef]
  93. Soleimani, Z.; Amighi, F.; Vakili, Z.; Momen-Heravi, M.; Moravveji, S.A. Diagnostic value of procalcitonin, erythrocyte sedimentation rate (ESR), quantitative C-reactive protein (CRP) and clinical findings associated with osteomyelitis in patients with diabetic foot. Hum. Antibodies 2021, 29, 115–121. [Google Scholar] [CrossRef] [PubMed]
  94. Albu, E.; Filip, C.; Zamosteanu, N.; Jaba, I.M.; Linic, I.S.; Sosa, I. Hyperhomocysteinemia is an indicator of oxidant stress. Med. Hypotheses 2012, 78, 554–555. [Google Scholar] [CrossRef] [PubMed]
  95. Atre, A.S.; CR, W.D.S.; Suresh, V.; Nagaraja, M.; Madhuvan, H. Evaluation of Plasma Total Antioxidant Capacity Levels and Osteocalcin in Prediabetes and Healthy Subjects. RGUHS J. Med. Sci. 2020, 10, 20–26. [Google Scholar] [CrossRef]
  96. Hirano, T. IL-6 in inflammation, autoimmunity and cancer. Int. Immunol. 2021, 33, 127–148. [Google Scholar] [CrossRef]
  97. Ridker, P.M.; MacFadyen, J.G.; Glynn, R.J.; Bradwin, G.; Hasan, A.A.; Rifai, N. Comparison of interleukin-6, C-reactive protein, and low-density lipoprotein cholesterol as biomarkers of residual risk in contemporary practice: Secondary analyses from the Cardiovascular Inflammation Reduction Trial. Eur. Heart J. 2020, 41, 2952–2961. [Google Scholar] [CrossRef]
  98. Holcomb, D.; Alexaki, A.; Hernandez, N.; Hunt, R.; Laurie, K.; Kames, J.; Hamasaki-Katagiri, N.; Komar, A.A.; DiCuccio, M.; Kimchi-Sarfaty, C. Gene variants of coagulation related proteins that interact with SARS-CoV-2. PLoS Comput. Biol. 2021, 17, e1008805. [Google Scholar] [CrossRef]
  99. Petel, D.; Winters, N.; Gore, G.C.; Papenburg, J.; Beltempo, M.; Lacroix, J.; Fontela, P.S. Use of C-reactive protein to tailor antibiotic use: A systematic review and meta-analysis. BMJ Open 2018, 8, e022133. [Google Scholar] [CrossRef] [Green Version]
  100. Sproston, N.R.; Ashworth, J.J. Role of C-Reactive Protein at Sites of Inflammation and Infection. Front. Immunol. 2018, 9, 754. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  101. Dawson, J.; Cockerill, G.W.; Choke, E.; Belli, A.M.; Loftus, I.; Thompson, M.M. Aortic aneurysms secrete interleukin-6 into the circulation. J. Vasc. Surg. 2007, 45, 350–356. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Artemiou, P.; Charokopos, N.; Rouska, E.; Sabol, F.; Chrysogonidis, I.; Tsavdaridou, V.; Paschalidis, G. C-reactive protein/interleukin-6 ratio as marker of the size of the uncomplicated thoracic aortic aneurysms. Interact. Cardiovasc. Thorac. Surg. 2012, 15, 871–877. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  103. Cui, N.; Zhang, H.; Chen, Z.; Yu, Z. Prognostic significance of PCT and CRP evaluation for adult ICU patients with sepsis and septic shock: Retrospective analysis of 59 cases. J. Int. Med. Res. 2019, 47, 1573–1579. [Google Scholar] [CrossRef] [Green Version]
  104. Tan, M.; Lu, Y.; Jiang, H.; Zhang, L. The diagnostic accuracy of procalcitonin and C-reactive protein for sepsis: A systematic review and meta-analysis. J. Cell. Biochem. 2019, 120, 5852–5859. [Google Scholar] [CrossRef]
  105. Hung, S.K.; Lan, H.M.; Han, S.T.; Wu, C.C.; Chen, K.F. Current Evidence and Limitation of Biomarkers for Detecting Sepsis and Systemic Infection. Biomedicines 2020, 8, 494. [Google Scholar] [CrossRef]
  106. Al-Barjas, H.S.; Ariens, R.; Grant, P.; Scott, J.A. Raised plasma fibrinogen concentration in patients with abdominal aortic aneurysm. Angiology 2006, 57, 607–614. [Google Scholar] [CrossRef]
  107. Menekşe, E.; Düz, M.E. Changes in D-dimer, Ferritin, and Fibrinogen in Healthy Smokers and Nonsmokers during the COVID-19 Outbreak. J. Surg. Res. 2023, 6, 94–99. [Google Scholar] [CrossRef]
  108. Ezaki, M.; Wada, H.; Ichikawa, Y.; Ikeda, N.; Shiraki, K.; Yamamoto, A.; Moritani, I.; Shimaoka, M.; Shimpo, H. Plasma Soluble Fibrin Is Useful for the Diagnosis of Thrombotic Diseases. J. Clin. Med. 2023, 12, 2597. [Google Scholar] [CrossRef]
  109. Di Castelnuovo, A.; de Curtis, A.; Costanzo, S.; Persichillo, M.; Olivieri, M.; Zito, F.; Donati, M.B.; de Gaetano, G.; Iacoviello, L.; Investigators, M.-S.P. Association of D-dimer levels with all-cause mortality in a healthy adult population: Findings from the MOLI-SANI study. Haematologica 2013, 98, 1476–1480. [Google Scholar] [CrossRef]
  110. Takagi, H.; Manabe, H.; Kawai, N.; Goto, S.; Umemoto, T. Plasma fibrinogen and D-dimer concentrations are associated with the presence of abdominal aortic aneurysm: A systematic review and meta-analysis. Eur. J. Vasc. Endovasc. Surg. 2009, 38, 273–277. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  111. Couturaud, F.; Kearon, C.; Bates, S.M.; Ginsberg, J.S. Decrease in sensitivity of D-dimer for acute venous thromboembolism after starting anticoagulant therapy. Blood Coagul. Fibrinolysis 2002, 13, 241–246. [Google Scholar] [CrossRef] [PubMed]
  112. Sadanaga, T.; Sadanaga, M.; Ogawa, S. Evidence that D-dimer levels predict subsequent thromboembolic and cardiovascular events in patients with atrial fibrillation during oral anticoagulant therapy. J. Am. Coll. Cardiol. 2010, 55, 2225–2231. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Crawford, F.; Andras, A.; Welch, K.; Sheares, K.; Keeling, D.; Chappell, F.M. D-dimer test for excluding the diagnosis of pulmonary embolism. Cochrane Database Syst. Rev. 2016, 2016, CD010864. [Google Scholar] [CrossRef] [Green Version]
  114. Wang, H. Evaluation of D-Dimer in Postmortem Blood Using the SERATEC PMB Test; Boston University: Boston, MA, USA, 2019. [Google Scholar]
  115. Gevsemezoglu, O.F.; Karadayi, B.; Koca, Y.; Cetin, G. Investigation of the use of seratec pmb test on postmortem peripheral blood samples for forensic purposes. Medicine 2022, 11, 159–165. [Google Scholar] [CrossRef]
  116. Goncalves, F.A.R.; Besen, B.; Lima, C.A.; Cora, A.P.; Pereira, A.J.R.; Perazzio, S.F.; Gouvea, C.P.; Fonseca, L.A.M.; Trindade, E.M.; Sumita, N.M.; et al. Use and misuse of biomarkers and the role of D-dimer and C-reactive protein in the management of COVID-19: A post-hoc analysis of a prospective cohort study. Clinics 2021, 76, e3547. [Google Scholar] [CrossRef]
  117. Gorelick, P.B.; Scuteri, A.; Black, S.E.; Decarli, C.; Greenberg, S.M.; Iadecola, C.; Launer, L.J.; Laurent, S.; Lopez, O.L.; Nyenhuis, D.; et al. Vascular contributions to cognitive impairment and dementia: A statement for healthcare professionals from the american heart association/american stroke association. Stroke 2011, 42, 2672–2713. [Google Scholar] [CrossRef]
  118. Han, X.; Wang, W.; He, J.; Jiang, L.; Li, X. Osteopontin as a biomarker for osteosarcoma therapy and prognosis. Oncol. Lett. 2019, 17, 2592–2598. [Google Scholar] [CrossRef] [Green Version]
  119. Chai, Y.L.; Chong, J.R.; Raquib, A.R.; Xu, X.; Hilal, S.; Venketasubramanian, N.; Tan, B.Y.; Kumar, A.P.; Sethi, G.; Chen, C.P.; et al. Plasma osteopontin as a biomarker of Alzheimer’s disease and vascular cognitive impairment. Sci. Rep. 2021, 11, 4010. [Google Scholar] [CrossRef]
  120. Wei, R.; Wong, J.P.C.; Kwok, H.F. Osteopontin—A promising biomarker for cancer therapy. J. Cancer 2017, 8, 2173–2183. [Google Scholar] [CrossRef] [Green Version]
  121. Bruha, R.; Vitek, L.; Smid, V. Osteopontin—A potential biomarker of advanced liver disease. Ann. Hepatol. 2020, 19, 344–352. [Google Scholar] [CrossRef] [PubMed]
  122. Farrokhi, V.; Chabot, J.R.; Neubert, H.; Yang, Z. Assessing the Feasibility of Neutralizing Osteopontin with Various Therapeutic Antibody Modalities. Sci. Rep. 2018, 8, 7781. [Google Scholar] [CrossRef] [PubMed]
  123. Bhatt, M.; MovaseghiGargari, M.; Chand, M.T. The importance of autopsies despite the declining number amidst the COVID-19 pandemic. Autops. Case Rep. 2022, 12, e2021371. [Google Scholar] [CrossRef]
  124. Elmsjo, A.; Vikingsson, S.; Soderberg, C.; Kugelberg, F.C.; Green, H. Post-Mortem Metabolomics: A Novel Approach in Clinical Biomarker Discovery and a Potential Tool in Death Investigations. Chem. Res. Toxicol. 2021, 34, 1496–1502. [Google Scholar] [CrossRef]
  125. Hudak, L.; Nagy, A.C.; Molnar, S.; Mehes, G.; Nagy, K.E.; Olah, L.; Csiba, L. Discrepancies between clinical and autopsy findings in patients who had an acute stroke. Stroke Vasc. Neurol. 2022, 7, 215–221. [Google Scholar] [CrossRef] [PubMed]
  126. Lilla, H.; (Penang, Malaysia). Personal communication, 2023.
  127. Goldman, L. Autopsy 2018: Still necessary, even if occasionally not sufficient. Circulation 2018, 137, 2686–2688. [Google Scholar] [CrossRef]
  128. Lunetta, P.; Lounamaa, A.; Sihvonen, S. Surveillance of injury-related deaths: Medicolegal autopsy rates and trends in Finland. Inj. Prev. 2007, 13, 282–284. [Google Scholar] [CrossRef] [Green Version]
  129. Perkins, G.D.; McAuley, D.F.; Davies, S.; Gao, F. Discrepancies between clinical and postmortem diagnoses in critically ill patients: An observational study. Crit. Care 2003, 7, R129–R132. [Google Scholar] [CrossRef] [Green Version]
  130. Nehring, S.; Goyal, A.; Patel, B. C Reactive Protein. 2021 Dec 28. In StatPearls [Internet]; StatPearls Publishing: Treasure Island, FL, USA, 2022. [Google Scholar]
  131. Nourkami-Tutdibi, N.; Graf, N.; Beier, R.; Zemlin, M.; Tutdibi, E. Plasma levels of osteopontin from birth to adulthood. Pediatr. Blood Cancer 2020, 67, e28272. [Google Scholar] [CrossRef] [Green Version]
  132. Sikora-Skrabaka, M.; Skrabaka, D.; Ruggeri, P.; Caramori, G.; Skoczynski, S.; Barczyk, A. D-dimer value in the diagnosis of pulmonary embolism-may it exclude only? J. Thorac. Dis. 2019, 11, 664–672. [Google Scholar] [CrossRef]
  133. Alvarez, B.; Ruiz, C.; Chacon, P.; Alvarez-Sabin, J.; Matas, M. Serum values of metalloproteinase-2 and metalloproteinase-9 as related to unstable plaque and inflammatory cells in patients with greater than 70% carotid artery stenosis. J. Vasc. Surg. 2004, 40, 469–475. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Five-year autopsy rate for all-death mortality worldwide; 2016–2020, slight decline in the overall autopsy rate, and a more evident decrease in the hospital death/autopsy rate (for more than 4% for the year 2020 compared to 2019).
Figure 1. Five-year autopsy rate for all-death mortality worldwide; 2016–2020, slight decline in the overall autopsy rate, and a more evident decrease in the hospital death/autopsy rate (for more than 4% for the year 2020 compared to 2019).
Forensicsci 03 00028 g001
Figure 2. Schematic of a provisional post mortem protocol created by the author, with biomarkers included; TA—traditional autopsy; VA—verbal autopsy.
Figure 2. Schematic of a provisional post mortem protocol created by the author, with biomarkers included; TA—traditional autopsy; VA—verbal autopsy.
Forensicsci 03 00028 g002
Table 1. Possible blood-based biomarkers of vascular disease.
Table 1. Possible blood-based biomarkers of vascular disease.
Related ProcessBiomarkerMediumReference ValuesHalf-Life
InflammationCRPS<0.3 mg/dL: normal
0.3 to 1.0 mg/dL: normal to minor elevation (can be seen in obesity, pregnancy, diabetes, common cold, gingivitis, periodontitis, sedentary lifestyle, cigarette smoking, and genetic polymorphisms) [130].
~19 h [99]
OPTS122.3 ± 39.2 ng/mL5 to 15 h [122]
P463.7 ng/mL–587.0 ng/mL [131].
Related to thrombusD-dimerS<2152 ng/mL [132].4 to 6 h [111]
Matrix-degrading enzymesMMP-9S436 ng/mL (range, 169–705 ng/mL) [133].Short [83]
S—serum; P—plasma; CRP—C-reactive protein; OPT—osteopontin; MMP—matrix metalloproteinases.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Šoša, I. Improving Traditional Post Mortem Healthcare—The Cross-Sectional Use of Blood-Based Biomarkers. Forensic Sci. 2023, 3, 368-380. https://doi.org/10.3390/forensicsci3030028

AMA Style

Šoša I. Improving Traditional Post Mortem Healthcare—The Cross-Sectional Use of Blood-Based Biomarkers. Forensic Sciences. 2023; 3(3):368-380. https://doi.org/10.3390/forensicsci3030028

Chicago/Turabian Style

Šoša, Ivan. 2023. "Improving Traditional Post Mortem Healthcare—The Cross-Sectional Use of Blood-Based Biomarkers" Forensic Sciences 3, no. 3: 368-380. https://doi.org/10.3390/forensicsci3030028

Article Metrics

Back to TopTop