Context.—

Autopsies can reveal clinically undiagnosed diseases. However, the frequency of first diagnoses at autopsy and their association with clinically known risk factors are not well understood because of lack of systematic analyses addressing this topic.

Objective.—

To perform a large retrospective cohort analysis on the frequency of clinically undiagnosed postmortem findings and correlate these with patients’ risk factors.

Design.—

Six hundred forty-eight consecutive and complete autopsies of adults (age >18 years), performed in the University Hospital Zurich, Switzerland, during a 3-year time period were retrospectively analyzed. Clinical diagnoses and postmortem findings were compared in order to identify clinically undiagnosed lesions and clarify their correlation with common risk factors.

Results.—

In 633 of 648 patients (98%), at least one clinically undiagnosed finding was identified at autopsy. The most common nonneoplastic entities were bronchopneumonia (198; 31%), coronary artery disease (155; 24%) and acute or subacute myocardial infarction (94; 15%), and the most common malignancies were prostate cancer in men (14; 2.2%), followed by kidney cancer (10; 1.5%), gastrointestinal stromal tumor (10; 1.5%), and lung carcinoma (9; 1.4%) in both sexes. Clinically undiagnosed cardiac amyloidosis was demonstrated in 8% (52 of 648) of patients and was significantly associated with age, hypertension, chronic kidney disease, coronary artery disease, and hypertensive cardiomyopathy.

Conclusions.—

Autopsy is a useful investigation for the detection of clinically undiagnosed entities. In our cohort, cardiac amyloidosis showed the highest number of underlying risk factors, but was clinically underdiagnosed. Our findings underline the necessity of improved clinical detection of cardiac amyloidosis, especially in light of emerging therapeutic options. Moreover, we characterize the most common entities prone to clinical underdiagnosis.

Autopsies are a valuable quality assurance tool for the assessment of medical care, in particular diagnostic and therapeutic accuracy, in hospitalized patients.1  Despite significant improvements in diagnostic imaging and laboratory investigations during the last decades, clinical and postmortem diagnoses can differ.2  Although the discrepancy rate has gradually decreased over time, it has remained stable for the past decade.3,4  Although many studies have characterized general discrepancy rates between clinical and postmortem diagnoses,3–7  there is a paucity of studies that examine unexpected findings at autopsy in detail (ie, lesions or diseases that are not clinically diagnosed or expected).8,9  Discrepancies and unexpected findings at autopsy are frequently reported in parallel in the literature, as they may represent two sides of the same coin in disease evaluation.10,11 

The Goldman-Battle classification delineates discrepancies into the following 6 classes, depending upon their clinical significance.1,12  Classes I and II include diagnostic discrepancies with potential major impact on cure and survival outcomes. On the other hand, classes III and IV concern discrepancies with important consequences on mid- to long-term management. Finally, class V includes undiagnosed diseases without discrepancies and class VI unclassifiable discrepancies (eg, patients who refused all diagnostic interventions and who died thereafter in hospital).

The Goldman-Battle classification is valuable, as it allows a simple grouping of diagnostic discrepancies and unexpected findings at autopsy based on their clinical relevance. Understandably, most of the available literature focuses on class I and II discrepancies.13  Only a few studies have addressed the general frequency of clinically undiagnosed findings detected at autopsy; however, these were limited to particular settings, such as deaths in a trauma center,14  clinically undiagnosed malignant tumors found at autopsy,15,16  or diseases in distinct organs or systems.17–19  To the best of our knowledge, no study has addressed the correlations between frequency of clinically undiagnosed diseases discovered at autopsy and clinically known risk factors and preexisting chronic diseases. Based on these premises, the aim of our study was to verify the existence of a correlation between certain known risk factors and the presence of clinically unknown lesions on autopsy examination in order to characterize the clinical entities most prone to underdiagnosis.

In this large retrospective study, we (1) investigated the frequencies of clinically undiagnosed findings (either missed or not investigated) demonstrated at autopsy; (2) characterized epidemiologic information on their prevalence in the study population; and (3) correlated clinically undiagnosed postmortem findings with biometric parameters, known risk factors, and chronic diseases as they were reported in the available medical charts when performing the autopsies.

All adult autopsies performed at the Department of Pathology and Molecular Pathology of the University Hospital of Zurich, Switzerland, between January 1, 2016 and December 31, 2018, were retrospectively evaluated. This time frame was chosen in order to exclude autopsies carried out during the COVID-19 pandemic. Only complete whole-body autopsies on patients older than 18 years at the time of death and with a natural cause of death clinically were included in this cohort. No forensic autopsies with unclear cause of death were included. Each autopsy was conducted by a pathology resident together with a board-certified staff pathologist. For this study, a board-certified pathologist screened all the clinical and autopsy reports of every case.

Consent to perform the autopsy was given in all cases, and this study was approved by the institutional review board (Department of Pathology and Molecular Pathology of the University Hospital Zurich, Switzerland). This study was carried out in accordance with the Swiss federal research regulations, and consisted solely of reevaluation of patient records. No additional tissue-based analyses were performed.

Data on biometric variables (age, sex, and body mass index), the presence of risk factors (such as hypertension, smoking, alcohol intake, adiposity, history of solid organ transplantation), chronic diseases reported (such as diabetes type 2, chronic kidney disease, cirrhosis, and systemic autoimmune disease), and other clinical and/or radiologic diagnoses were retrospectively collected from the internal electronic medical data bank of the University Hospital Zurich. For autopsies without a detailed clinical history (eg, for patients who died outside the hospital or in an external hospital), the relevant information for the study was obtained from external clinical records that were submitted at the time of the autopsy request.

Autopsy reports were screened with particular focus on the presence of findings that were not clinically or radiologically known. Each lesion evident macroscopically at autopsy with subsequent histologic confirmation (ie, acute myocardial ischemia, tumor entities, etc) that was not documented in the medical history was defined as clinically undiagnosed disease.

The presence or absence of a particular risk factor or disease (clinically previously known) and the presence of a clinically undiagnosed finding detected at autopsy were coded with a binary code (1 = presence, 0 = absence) in a table including all multiple binary variables for each patient. Age in years and total number of clinically undiagnosed findings demonstrated at autopsy for each patient were included in the table as discrete quantitative variables.

Statistical analyses were performed using SPSS V28.0.1.1 (IBM Corp, Armonk, New York).

The total number of clinically undiagnosed findings demonstrated at autopsy was correlated with patient demographics and the presence of clinically known risk factors and diseases through Spearman ρ and Kendall τ correlation.

Age was correlated using Spearman ρ and Kendall τ correlation with the following postmortem findings (ie, clinically not known): myocardial ischemia, coronary artery disease (defined as a coronary stenosis involving more than 50% of the lumen of one or more major coronary arteries), bronchopneumonia (histomorphologically defined as granulocytic inflammation destroying alveolar septa and bronchial wall), pulmonary embolism, cardiac amyloidosis, and cirrhosis.

The presence of clinically known risk factors and diseases was correlated with postmortem first diagnoses using the Fisher exact test and a likelihood ratio (LR), defined as the probability that a patient with a disease had a risk factor/probability that a patient without the disease had the same risk factor.

Given the exploratory nature of these analyses, no adjustment for multiple testing was performed. Results were considered statistically significant when the P value was less than .05.

Altogether, 648 autopsy cases were included in this study. Four hundred thirteen patients (64%) were male and 235 (36%) were female. Four hundred twenty-eight patients (66%) were hospitalized at the University Hospital Zurich prior to death. At this institution, autopsy rate (calculated as the number of autopsies performed divided by the number of patients who died in hospital) during the years of the study was 13%.

Of the remaining 220 patients included in the study (34%), 154 died in an external hospital (154 of 648; 24% of the total) and 66 were cases of unexpected/sudden death (66 of 648; 10% of the total). Autopsy rates of external hospitals were not available. The age of patients ranged from 19 to 96 years at the time of death (mean, 69.2 years; median, 69 years). Prevalence of clinical reported risk factors and known diseases (before death) are summarized in Supplemental Table 1 (see the supplemental digital content containing 2 tables at https://meridian.allenpress.com/aplm in the January 2025 table of contents.).

The most commonly reported risk factors of the 648 were hypertension (n = 462; 71%), smoking (n = 114; 18%), and adiposity (body mass index ≥30 kg/m2; n = 88; 14%). The most common chronic disorders reported by treating physicians were hypertrophic cardiomyopathy (n = 227; 35%), coronary artery disease (n = 183; 28%), and chronic kidney disease (n = 160; 25%). The most frequent reasons for hospitalization were advanced cancer (n = 131; 20%), pneumonia (n = 117; 18%), and acute myocardial infarction (n = 56; 9%). The most common malignant tumors were lung carcinoma (n = 38; 5.9%), non-Hodgkin lymphoma (n = 32; 4.9%), and acute leukemia (n = 31; 4.8%).

In 633 of the 648 patients (98%), at least one clinically undiagnosed finding was demonstrated at autopsy (range, 1–8; mode, 3; median, 3). Detailed information on the nontumoral entities, malignant tumors, and benign tumors that were first diagnosed at autopsy (clinically undiagnosed) are given in Table 1, Table 2, and Supplemental Table 2, respectively.

The most common nontumoral entities discovered at autopsy were bronchopneumonia (n = 198; 31%), followed by coronary artery disease (stenosis of >50% in a main coronary artery; n = 155; 24%), pulmonary embolism (n = 99; 15%), and acute or subacute myocardial infarction (n = 94; 15%).

The most common malignant tumor discovered at autopsy was prostate adenocarcinoma in male patients (n = 14 of 413 male patients; 3.4%), followed by renal cell carcinoma (n = 10 of 648; 1.5%), gastrointestinal stromal tumor (n = 10 of 648; 1.5%), and lung carcinoma (n = 9 of 648; 1.4%) in both sexes.

The number of clinically undiagnosed findings discovered at autopsy was significantly correlated with the age of patients (P < .001), the clinical diagnosis of hypertension (P < .001), and the presence of chronic kidney disease (P = .005). There was no statistically significant correlation with gender, risk factors other than hypertension, or presence of clinical diagnoses other than chronic kidney disease.

The age of patients was significantly correlated with autopsy-detected bronchopneumonia (P = .007) and cardiac amyloidosis (P < .001).

Hypertension was significantly correlated with autopsy-detected cardiac amyloid transthyretin (ATTR)-type amyloidosis (see Figure 1, A through C) (P = .02, LR = 6.9) but not with other unexpected postmortem findings. Smoking was significantly associated with coronary artery disease detected at autopsy (P = .04, LR = 4.2), and alcohol intake was significantly correlated with autopsy-detected liver cirrhosis (P = .003, LR = 8.5) but not with other findings. Chronic kidney disease was significantly associated with autopsy-detected bronchopneumonia (P = .048, LR = 3.9) and cardiac amyloidosis (P = .001, LR = 11.0). The presence of clinically diagnosed coronary artery disease was associated with autopsy-detected acute or subacute myocardial ischemia (P = .02, LR = 5.2) and cardiac amyloidosis (P = .001, LR = 10.7). The clinical diagnosis of hypertensive hypertrophic cardiomyopathy was associated with autopsy-detected coronary artery disease (P = .001, LR = 10.3), ischemia of the gastrointestinal tract (P = .03, LR = 4.8), and cardiac amyloidosis (P = .003, LR = 5.9). The clinical diagnosis of cancer in an advanced stage did not significantly correlate with any specific unexpected finding at autopsy. Graphic representation of correlations between risk factors and clinically undiagnosed diseases detected at autopsy is shown in Figure 2.

Figure 1.

Amyloid transthyretin (ATTR) myocardial amyloidosis. A, Myocardial tissue with diffuse deposition of amorphous eosinophilic material consistent with amyloid. B, Detail showing the interstitial localization and atrophy of the surrounding myocardiocytes. C, Amyloid shows positivity for ATTR (hematoxylin-eosin, original magnifications ×4 [A] and ×40 [B]; immunohistochemistry for ATTR, original magnification ×40 [C]).

Figure 1.

Amyloid transthyretin (ATTR) myocardial amyloidosis. A, Myocardial tissue with diffuse deposition of amorphous eosinophilic material consistent with amyloid. B, Detail showing the interstitial localization and atrophy of the surrounding myocardiocytes. C, Amyloid shows positivity for ATTR (hematoxylin-eosin, original magnifications ×4 [A] and ×40 [B]; immunohistochemistry for ATTR, original magnification ×40 [C]).

Close modal
Figure 2.

Matrix showing the correlations between clinically known risk factors and diseases and autopsy-discovered lesions/diseases. Statistically significant correlations (P < .05) are depicted with circles of different shades of red according to the strength of association (the darker, the stronger); green circles indicate no correlation (P > .05) between variables. Abbreviations: CAD, coronary artery disease; CKD, chronic kidney disease; DM, diabetes mellitus.

Figure 2.

Matrix showing the correlations between clinically known risk factors and diseases and autopsy-discovered lesions/diseases. Statistically significant correlations (P < .05) are depicted with circles of different shades of red according to the strength of association (the darker, the stronger); green circles indicate no correlation (P > .05) between variables. Abbreviations: CAD, coronary artery disease; CKD, chronic kidney disease; DM, diabetes mellitus.

Close modal

In this study, we reviewed all complete clinical autopsies of adult patients performed at a tertiary institute in Switzerland during a 3-year time period before the COVID-19 pandemic. Our results provide evidence that autopsy reveals at least one clinically undiagnosed finding in the majority of patients (98%). This phenomenon may be explained through different clinical and epidemiologic aspects. First, these diseases or lesions may not have been investigated because patients were asymptomatic, or they may have been missed clinically, radiologically, or because the chosen diagnostic workup was not sufficient to detect the lesion. Many of these clinically undiagnosed entities, even though asymptomatic in the patient’s lifetime, might have had clinical consequences in the short or long term if the patient had lived longer (eg, coronary artery disease, bronchopneumonia, pulmonary embolism, and myocardial infarction). Of note, in our cohort, a major discrepancy (ie, a class I discrepancy according to the Goldman-Battle classification) was demonstrated in 3.8% of cases in 2016 and 2.8% in 2017–2018, providing an indicative estimate of the number of cases in which a different treatment and/or patient management would have had a major impact on clinical outcome. In this regard, further retrospective studies investigating the reasons for these clinically missed diagnoses and their possible impact on morbidity are needed.

Moreover, we could demonstrate that many patients died with one or more clinically undiagnosed malignancies, in particular prostate cancer (3.4%), renal cell cancer (1.5%), gastrointestinal stromal tumor (1.5%), and lung cancer (1.4%). All these cases of autopsy-diagnosed malignancies were organ-localized and low-grade neoplasms (eg, adenocarcinoma of prostate Gleason score 3 + 4, microinvasive adenocarcinoma of the lung). Although these are clearly malignant neoplasms, it is difficult to establish the clinical significance in their stadium, as they were probably asymptomatic lesions. However, evolution of these neoplasms in a metastatic or locally aggressive direction would have been biologically possible if the patient had survived the underlying disease. Moreover, these data may be of interest for preventive and screening purposes in the future.

Our previous work published in 2015, based on the data from the Cancer Registry of Canton Zurich, demonstrated a reduction in autopsy-discovered malignancies from 1980 (when autopsies contributed to 15% of new cancer diagnoses, in particular of liver, biliary system, pancreas, prostate, thyroid, and kidney) to 2010 (when this number decreased to less than 3%).20  New data from the current study are concordant with our previous work in highlighting that improved diagnostic and therapeutic options for oncologic diseases has led to a reduction in postmortem discrepancies. However, only a few studies have focused on benign tumors or tumorlike lesions discovered at autopsy, and most of these are case reports of specific entities or case series limited to one organ.21–23  In the present study, we have collected data on all benign tumors and tumorlike lesions discovered at autopsy and can show that many patients died with one or more undiagnosed benign tumors or pseudotumoral lesions. Although many of these benign entities were not directly life-threatening, they may cause clinically relevant symptoms, undergo malignant transformation (eg, colorectal adenoma), or show similar radiologic appearances to malignancies (eg, adenoma of the kidney, Von Meyenburg complexes).

In our cohort, we showed that increasing age or the presence of hypertension and chronic kidney disease raised the probability of finding one or more clinically undiagnosed diseases at autopsy. Hypertension was associated with autopsy-discovered cardiac amyloidosis, smoking with coronary artery disease, alcohol intake with undiagnosed liver cirrhosis, chronic kidney disease with bronchopneumonia and cardiac amyloidosis, and age with bronchopneumonia and cardiac amyloidosis. These findings may be medically relevant. First, although the association between some risk factors and certain diseases is well known (eg, alcohol abuse and liver cirrhosis),24  the fact of demonstrating the same association between the clinically known risk factors and the autopsy-discovered disease may suggest that some entities are still underdiagnosed. In our study, this was the case in particular with liver cirrhosis and with coronary artery disease, both of which can be asymptomatic if no further complications occur.

The real consequences of clinically undiagnosed diseases (neoplastic or other) for clinicians (in terms of differential diagnosis and symptoms of potentially unknown disorders and their management) and for public health authorities (eg, in terms of screening programs) may be of great impact but require further exploration and delineation.

Most importantly, autopsy-discovered cardiac amyloidosis merits careful consideration. This entity was found in 52 patients (8% of all autopsies). Immunohistochemical analysis revealed an ATTR-associated amyloidosis in 37 cases (37 of 52; 71%) and an amyloid light chain amyloidosis in 2 cases (2 of 52; 4%), and 13 cases (13 of 52; 25%) were not typed. These results underline the fact that cardiac amyloidosis is an underdiagnosed disease,25  although it is an important cause of heart failure with preserved ejection fraction.26  Interestingly, our results are in line with those of a clinical study of 1235 patients that demonstrated that ATTR-associated cardiac amyloidosis is clinically recognized in only 1.3% of patients, whereas the prevalence was found to be 6.3% through specific and sensitive analyses (Tc99m pyrophosphate scintigraphy).27  Altogether, these results suggest the need for improved clinical detection of cardiac amyloidosis. However, the relationships between autopsy-detected cardiac amyloidosis, its severity in terms of percentage of involvement of myocardial tissue and/or myocardial vessels, and its symptomatology during the lifetime of patients still need to be investigated.

Of note, cardiac amyloidosis represents the most common type of infiltrative cardiomyopathy, followed by cardiac sarcoidosis, cardiac hemochromatosis, and Fabry disease.28  The results of the present study now support and extend upon previous findings that cardiac amyloidosis is a currently underdiagnosed cause of heart failure.29  In fact, prevalence of concealed cardiac amyloidosis has been reported in up to 25% of unselected octogenarians and 30% to 40% of patients older than 75 years with heart failure with preserved ejection fraction.30,31  Overall mean survival rates from the onset of heart failure in untreated patients are poor, highlighting the need for timely referral, diagnosis, and directed therapy, which critically depends on the type of amyloid.32 

Different cardiac amyloid types share similar clinical manifestations and cardiac imaging findings but differ substantially with regard to diagnosis, prognosis, and therapy, depending on the precursor protein (ie, immunoglobulin light chain–associated amyloid or transthyretin amyloid, with the latter divided into a hereditary form due to a transthyretin DNA mutation or wild-type ATTR). Of note, liver transplant in ATTR, bone marrow transplant in amyloid light chain, and gene silencers and orally available transthyretin stabilizers in transthyretin amyloidosis hold the potential to at least delay the progression of the disease.33,34 

Altogether, even though the number of patients in our cohort limits the power of our statistical analyses, our data suggest that increased age, hypertension, chronic kidney disease, hypertensive cardiomyopathy, and coronary artery disease may all represent possible risk factors for cardiac amyloidosis and may help to identify a subset of patients who could benefit from added surveillance. Eventually, further studies will be necessary to establish the existence of a pathogenetic link between these risk factors and cardiac amyloidosis.

The strength of this study is its recent and heterogeneous cohort that includes many hospitalized patients in different departments, thus reflecting a real-life scenario that provides important epidemiologic information on the frequency of undiagnosed diseases and explores their correlation with clinically known risk factors and disorders.

The weakness of this study lies in the possible biases that typically affect a postmortem cohort. There may be some interobserver variability among pathologists in reporting gross findings. The discovery of certain findings strongly depends on the extent of the sampling, which may vary from pathologist to pathologist (eg, prostate is not regularly examined histologically, unless the macroscopic appearance looks pathologic, there is a clinical suspicion of cancer, or the pathologist has a particular academic interest in sampling this organ). However, it should be added that the sampling for histology of most organs is standardized (eg, myocardial tissue, lungs, liver, spleen, pancreas, kidneys, thyroid, adrenal glands, hypophysis, brain cortex, hippocampus, cerebellum, and basal ganglia are standard parts of histology of an autopsy, and if some additional macroscopic findings are present, they are also examined independently from the organ). Although our institution’s electronic patient medical record system provided detailed information on clinical diagnoses and risk factors for each hospitalized patient, and these data were examined entirely for this study, the clinical information provided in the autopsy request form from external referrals may have been less comprehensive. However, interestingly, there was no statistically significant difference in the number of unexpected findings between patients hospitalized in our institution and external patients. In addition, it should be considered that both cases of patients who died in outpatient hospitals and those who died in university clinics are regularly discussed in an autopsy board involving pathologists, radiologists, and clinicians, so that any clinically unknown autopsy findings are reported in any case. Although some information may still be missed despite this careful method of quality control of clinical diagnoses, we are confident that each patient’s clinical history was examined in its entirety for our study and that isolated cases that escaped this thorough control do not represent a phenomenon that invalidates statistical analyses.

Patients dying in hospital or those who experience sudden death may not be representative of the general population but rather could reflect a higher frequency of disorders than the general population. Moreover, not all patients who die in hospital undergo an autopsy, only those who display an unclear clinical constellation or whose cause of death is not easily ascertained. In this regard, it should be considered that our institution’s autopsy rate was 13% during the years examined in our study. This may naturally have the effect of overestimating the number of previously undiagnosed diseases, as only the most clinically complex and least clear cases are clarified by autopsy examination. In addition, another critical issue is the consent to perform the autopsy. In Switzerland, for cases of natural death (ie, where there is no suggestion of a traumatic death or medical or surgical error), it is the family members of the deceased patient who give consent for the autopsy (unless the patient, while still alive, had explicitly expressed his or her will in this regard in a positive or negative sense). The obvious consequence of this system is that autopsy is not performed in all cases that the attending physician deems appropriate to clarify by this means. Therefore, it may be important that the statistics reported here be confirmed by studies in countries where autopsy rates are higher and consent to autopsy works differently. Another crucial point to consider is that the duration of hospitalization, the frequency with which the patient visited the family doctor, and/or adherence to recommended screening programs was not known for every patient of this study, and this may represent a factor potentially influencing statistical analysis.

To conclude, our study provides important epidemiologic information on the frequency of undiagnosed diseases in a hospitalized patient population. Age, hypertension, and chronic kidney disease increase the risk of having one or more clinically unrecognized diseases. In particular, hypertension is associated with autopsy-discovered cardiac amyloidosis, smoking with coronary artery disease, alcohol with liver cirrhosis, chronic kidney disease with bronchopneumonia and amyloidosis, hypertensive cardiomyopathy with coronary artery disease and gastrointestinal ischemia, and age with bronchopneumonia and amyloidosis. This information may help treating physicians to identify specific subsets of patients at risk for such disorders. However, the impact and consequences of our findings on the clinical management of patients need to be determined.

The authors thank Catherine Connolly, MD, for assisting with the revision of the manuscript.

1.
Goldman
L,
Sayson
R,
Robbins
S,
Cohn
LH,
Bettmann
M,
Weisberg
M.
The value of the autopsy in three medical eras
.
N Engl J Med
.
1983
;
308
(
17
):
1000
1005
.
2.
Issa
VS,
Dinardi
LFL,
Pereira
TV,
et al.
Diagnostic discrepancies in clinical practice: an autopsy study in patients with heart failure
.
Medicine (Baltimore)
.
2017
;
96
(
4
):
e5978
.
3.
Kurz
SD,
Sido
V,
Herbst
H,
et al.
Discrepancies between clinical diagnosis and hospital autopsy: a comparative retrospective analysis of 1,112 cases
.
PLoS One
.
2021
;
16
(
8
):
e0255490
.
4.
Schwanda-Burger
S,
Moch
H,
Muntwyler
J,
Salomon
F.
Diagnostic errors in the new millennium: a follow-up autopsy study
.
Mod Pathol
.
2012
;
25
(
6
):
777
783
.
5.
Tavora
F,
Crowder
CD,
Sun
CC,
Burke
AP.
Discrepancies between clinical and autopsy diagnoses: a comparison of university, community, and private autopsy practices
.
Am J Clin Pathol
.
2008
;
129
(
1
):
102
109
.
6.
Perkins
GD,
McAuley
DF,
Davies
S,
Gao
F.
Discrepancies between clinical and postmortem diagnoses in critically ill patients: an observational study
.
Crit Care
.
2003
;
7
(
6
):
R129
R132
.
7.
Sarode
VR,
Datta
BN,
Banerjee
AK,
et al.
Autopsy findings and clinical diagnoses: a review of 1,000 cases
.
Hum Pathol
.
1993
;
24
(
2
):
194
198
.
8.
Bedell
SE,
Fulton
EJ.
Unexpected findings and complications at autopsy after cardiopulmonary resuscitation (CPR)
.
Arch Intern Med
.
1986
;
146
(
9
):
1725
1728
.
9.
Mentink
MG,
Latten
BGH,
Bakers
FCH,
et al.
Clinical relevance of unexpected findings of post-mortem computed tomography in hospitalized patients: an observational study
.
Int J Environ Res Public Health
.
2020
;
17
(
20
):
7572
.
10.
Tejerina
E,
Esteban
A,
Fernandez-Segoviano
P,
et al.
Clinical diagnoses and autopsy findings: discrepancies in critically ill patients
.
Crit Care Med
.
2012
;
40
(
3
):
842
846
.
11.
Pastores
SM,
Dulu
A,
Voigt
L,
Raoof
N,
Alicea
M,
Halpern
NA.
Premortem clinical diagnoses and postmortem autopsy findings: discrepancies in critically ill cancer patients
.
Crit Care
.
2007
;
11
(
2
):
R48
.
12.
Battle
RM,
Pathak
D,
Humble
CG,
et al.
Factors influencing discrepancies between premortem and postmortem diagnoses
.
JAMA
.
1987
;
258
(
3
):
339
344
.
13.
Rodewald
AK,
Bode
P,
Cathomas
G,
Moch
H.
Clinical autopsies in Switzerland: a status report [in German
]. Pathologe
.
2017
;
38
(
5
):
416
421
.
14.
Neblett
ACG,
Gibson
TN,
Escoffery
CT.
Unexpected findings and misdiagnoses in coroner’s autopsies performed for trauma at the University of the West Indies, Kingston, Jamaica
.
Forensic Sci Med Pathol
.
2018
;
14
(
3
):
314
321
.
15.
Karwinski
B,
Svendsen
E,
Hartveit
F.
Clinically undiagnosed malignant tumours found at autopsy
.
APMIS
.
1990
;
98
(
6
):
496
500
.
16.
Javed
N,
Rueckert
J,
Mount
S.
Undiagnosed malignancy and therapeutic complications in oncology patients
.
Arch Pathol Lab Med
.
2022
;
146
(
1
):
101
106
.
17.
Thomas
ET,
Del Mar
C,
Glasziou
P,
Wright
G,
Barratt
A,
Bell
KJL.
Prevalence of incidental breast cancer and precursor lesions in autopsy studies: a systematic review and meta-analysis
.
BMC Cancer
.
2017
;
17
(
1
):
808
.
18.
Khare
P,
Gupta
R,
Ahuja
M,
Khare
N,
Agarwal
S,
Bansal
D.
Prevalence of lung lesions at autopsy: a histopathological study
.
J Clin Diagn Res
.
2017
;
11
(
5
):
EC13
EC16
.
19.
Khare
P,
Gupta
R,
Agarwal
S,
Bhatnagar
A,
Anand
R.
Spectrum of renal lesions on autopsy: experience of a tertiary level institute based on retrospective histopathological analysis
.
Cureus
.
2021
;
13
(
8
):
e17064
.
20.
Bieri
U,
Moch
H,
Dehler
S,
Korol
D,
Rohrmann
S.
Changes in autopsy rates among cancer patients and their impact on cancer statistics from a public health point of view: a longitudinal study from 1980 to 2010 with data from Cancer Registry Zurich
.
Virchows Arch
.
2015
;
466
(
6
):
637
643
.
21.
Jain
D,
Maleszewski
JJ,
Halushka
MK.
Benign cardiac tumors and tumorlike conditions
.
Ann Diagn Pathol
.
2010
;
14
(
3
):
215
230
.
22.
Tamboli
P,
Ro
JY,
Amin
MB,
Ligato
S,
Ayala
AG.
Benign tumors and tumor-like lesions of the adult kidney, part II: benign mesenchymal and mixed neoplasms, and tumor-like lesions
.
Adv Anat Pathol
.
2000
;
7
(
1
):
47
66
.
23.
Nielsen
M.
Autopsy studies of the occurrence of cancerous, atypical and benign epithelial lesions in the female breast
.
APMIS Suppl
.
1989
;
10
:
1
56
.
24.
Singal
AK,
Mathurin
P.
Diagnosis and treatment of alcohol-associated liver disease: a review
.
JAMA
.
2021
;
326
(
2
):
165
176
.
25.
Gilstrap
LG,
Dominici
F,
Wang
Y,
et al.
Epidemiology of cardiac amyloidosis-associated heart failure hospitalizations among fee-for-service Medicare beneficiaries in the United States
.
Circ Heart Fail
.
2019
;
12
(
6
):
e005407
.
26.
Ruberg
FL,
Grogan
M,
Hanna
M,
Kelly
JW,
Maurer
MS.
Transthyretin amyloid cardiomyopathy: JACC State
-
of-the-Art Review. J Am Coll Cardiol
.
2019
;
73
(
22
):
2872
2891
.
27.
AbouEzzeddine
OF,
Davies
DR,
Scott
CG,
et al.
Prevalence of transthyretin amyloid cardiomyopathy in heart failure with preserved ejection fraction
.
JAMA Cardiol
.
2021
;
6
(
11
):
1267
1274
.
28.
Madan
N,
Kalra
D.
Clinical evaluation of infiltrative cardiomyopathies resulting in heart failure with preserved ejection fraction
.
Rev Cardiovasc Med
.
2020
;
21
(
2
):
181
190
.
29.
Alexander
KM,
Orav
J,
Singh
A,
et al.
Geographic disparities in reported US amyloidosis mortality from 1979 to 2015: potential underdetection of cardiac amyloidosis
.
JAMA Cardiol
.
2018
;
3
(
9
):
865
870
.
30.
Tanskanen
M,
Peuralinna
T,
Polvikoski
T,
et al.
Senile systemic amyloidosis affects 25% of the very aged and associates with genetic variation in alpha2-macroglobulin and tau: a population-based autopsy study
.
Ann Med
.
2008
;
40
(
3
):
232
239
.
31.
Porcari
A,
Bussani
R,
Merlo
M,
et al.
Incidence and characterization of concealed cardiac amyloidosis among unselected elderly patients undergoing post-mortem examination
.
Front Cardiovasc Med
.
2021
;
8
:
749523
.
32.
Martinez-Naharro
A,
Hawkins
PN,
Fontana
M.
Cardiac amyloidosis
.
Clin Med (Lond)
.
2018
;
18
(
suppl 2
):
s30
s35
.
33.
Garcia-Pavia
P,
Rapezzi
C,
Adler
Y,
et al.
Diagnosis and treatment of cardiac amyloidosis: a position statement of the European Society of Cardiology Working Group on Myocardial and Pericardial Diseases
.
Eur J Heart Fail
.
2021
;
23
(
4
):
512
526
.
34.
Kittleson
MM,
Maurer
MS,
Ambardekar
AV,
et al.
Cardiac amyloidosis: evolving diagnosis and management: a scientific statement from the American Heart Association
.
Circulation
.
2020
;
142
(
1
):
e7
e22
.
35.
Vanhaebost
J,
Faouzi
M,
Mangin
P,
Michaud
K.
New reference tables and user-friendly Internet application for predicted heart weights
.
Int J Legal Med
.
2014
;
128
(
4
):
615
620
.
36.
Takebayashi
S,
Kiyoshi
Y,
Hisano
S,
et al.
Benign nephrosclerosis: incidence, morphology and prognosis
.
Clin Nephrol
.
2001
;
55
(
5
):
349
356
.

Author notes

Supplemental digital content is available for this article at https://meridian.allenpress.com/aplm in the January 2025 table of contents.

Competing Interests

The authors have no relevant financial interest in the products or companies described in this article.

Supplementary data