Casali et al developed mathematical models for predicting height of a fall from the autopsy findings. One model uses injuries to a range of organs to reach an estimate. The authors are from Universita degli Studi di Milano.
Patient selection: death after fall from height
Parameters for linear regression model:
(1) age in years
(2) weight in kilograms
(3) severe lesion in neurocranium
(4) severe injury in facial skeleton
(5) severe injury in cerebrum
(6) severe injury in cerebellum
(7) severe injury in brainstem
(8) severe injury in lungs
(9) severe injury trachea and/or bronchi
(10) severe injury to heart
(11) severe injury to thoracic aorta
(12) severe injury to diaphragm
(13) severe injury to liver
(14) severe injury to spleen
(15) severe injury to abdominal aorta
(16) severe injury to kidneys
(17) severe injury to the mesentery
(18) severe injury to cervical spine
(19) severe injury to thoracic spine
(20) severe injury to lumbar spine
(21) severe injury to pelvis
(22) severe injury to sternum, clavicle and rib complex
|
Parameter |
Finding |
Points |
|
age in years |
|
-0.097 * age |
|
weight |
|
-0.038 * (weight) |
|
neurocranium |
no |
0 |
|
|
yes |
0.17 |
|
facial skeleton |
no |
0 |
|
|
yes |
1.073 |
|
cerebrum |
no |
0 |
|
|
yes |
-0.53 |
|
cerebellum |
no |
0 |
|
|
yes |
0.604 |
|
brainstem |
no |
0 |
|
|
yes |
1.711 |
|
lungs |
no |
0 |
|
|
yes |
1.21 |
|
trachea and bronchi |
no |
0 |
|
|
yes |
1.492 |
|
heart |
no |
0 |
|
|
yes |
0.674 |
|
thoracic aorta |
no |
0 |
|
|
yes |
1.613 |
|
diaphragm |
no |
0 |
|
|
yes |
2.223 |
|
liver |
no |
0 |
|
|
yes |
2.789 |
|
spleen |
no |
0 |
|
|
yes |
1.306 |
|
abdominal aorta |
no |
0 |
|
|
yes |
4.002 |
|
kidneys |
no |
0 |
|
|
yes |
0.302 |
|
mesentery |
no |
0 |
|
|
yes |
2.49 |
|
cervical spine |
no |
0 |
|
|
yes |
1.086 |
|
thoracic spine |
no |
0 |
|
|
yes |
0.735 |
|
lumbar spine |
no |
0 |
|
|
yes |
1.607 |
|
pelvis |
no |
0 |
|
|
yes |
1.921 |
|
sternum, clavicle, ribs |
no |
0 |
|
|
yes |
3.133 |
height of fall in meters =
= SUM(points for all of the parameters) + 15.630
Performance:
• The standard error in height prediction is 5.2 meters.
Specialty: Clinical Laboratory
