Differential diagnosis

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Differential diagnosis_table_infobox_0

Differential diagnosisDifferential diagnosis_header_cell_0_0_0
MeSHDifferential diagnosis_header_cell_0_1_0 Differential diagnosis_cell_0_1_1

In medicine, a differential diagnosis is the distinguishing of a particular disease or condition from others that present similar clinical features. Differential diagnosis_sentence_0

Differential diagnostic procedures are used by physicians to diagnose the specific disease in a patient, or, at least, to eliminate any imminently life-threatening conditions. Differential diagnosis_sentence_1

Often, each individual option of a possible disease is called a differential diagnosis (e.g., acute bronchitis could be a differential diagnosis in the evaluation of a cough, even if the final diagnosis is common cold). Differential diagnosis_sentence_2

More generally, a differential diagnostic procedure is a systematic diagnostic method used to identify the presence of a disease entity where multiple alternatives are possible. Differential diagnosis_sentence_3

This method may employ algorithms, akin to the process of elimination, or at least a process of obtaining information that shrinks the "probabilities" of candidate conditions to negligible levels, by using evidence such as symptoms, patient history, and medical knowledge to adjust epistemic confidences in the mind of the diagnostician (or, for computerized or computer-assisted diagnosis, the software of the system). Differential diagnosis_sentence_4

Differential diagnosis can be regarded as implementing aspects of the hypothetico-deductive method, in the sense that the potential presence of candidate diseases or conditions can be viewed as hypotheses that physicians further determine as being true or false. Differential diagnosis_sentence_5

A differential diagnosis is also commonly used within the field of psychiatry/psychology, where two different diagnoses can be attached to a patient who is exhibiting symptoms which could fit into either diagnosis. Differential diagnosis_sentence_6

For example, a patient who has been diagnosed with bipolar disorder may also be given a differential diagnosis of borderline personality disorder, given the similarity in the symptoms of both conditions. Differential diagnosis_sentence_7

Strategies used in preparing a differential diagnosis list vary with experience of the healthcare provider. Differential diagnosis_sentence_8

While novice providers may work systemically to assess all possible explanations for a patients concerns, those with more experience often draw on clinical experience and pattern recognition to protect the patient from delays, risks, and cost of inefficient strategies or tests. Differential diagnosis_sentence_9

Effective providers utilize an evidence-based approach, complementing their clinical experience with knowledge from clinical research. Differential diagnosis_sentence_10

General components Differential diagnosis_section_0

Specific methods Differential diagnosis_section_1

There are several methods for differential diagnostic procedures, and several variants among those. Differential diagnosis_sentence_11

Furthermore, a differential diagnostic procedure can be used concomitantly or alternately with protocols, guidelines, or other diagnostic procedures (such as pattern-recognition or using medical algorithms). Differential diagnosis_sentence_12

For example, in case of medical emergency, there may not be enough time to do any detailed calculations or estimations of different probabilities, in which case the ABC protocol (Airway, Breathing and Circulation) may be more appropriate. Differential diagnosis_sentence_13

Later, when the situation is less acute, a more comprehensive differential diagnostic procedure may be adopted. Differential diagnosis_sentence_14

The differential diagnostic procedure may be simplified if a "pathognomonic" sign or symptom is found (in which case it is almost certain that the target condition is present) or in the absence of a 'sine qua non sign or symptom (in which case it is almost certain that the target condition is absent). Differential diagnosis_sentence_15

A diagnostician can be selective, considering first those disorders that are more likely (a probabilistic approach), more serious if left undiagnosed and untreated (a prognostic approach), or more responsive to treatment if offered (a pragmatic approach). Differential diagnosis_sentence_16

Since the subjective probability of the presence of a condition is never exactly 100% or 0%, the differential diagnostic procedure may aim at specifying these various probabilities to form indications for further action. Differential diagnosis_sentence_17

The following are two methods of differential diagnosis, being based on epidemiology and likelihood ratios, respectively. Differential diagnosis_sentence_18

Epidemiology-based method Differential diagnosis_section_2

One method of performing a differential diagnosis by epidemiology aims to estimate the probability of each candidate condition by comparing their probabilities to have occurred in the first place in the individual. Differential diagnosis_sentence_19

It is based on probabilities related both to the presentation (such as pain) and probabilities of the various candidate conditions (such as diseases). Differential diagnosis_sentence_20

Theory Differential diagnosis_section_3

The statistical basis for differential diagnosis is Bayes' theorem. Differential diagnosis_sentence_21

As an analogy, when a die has landed the outcome is certain by 100%, but the probability that it Would Have Occurred in the First Place (hereafter abbreviated WHOIFP) is still 1/6. Differential diagnosis_sentence_22

In the same way, the probability that a presentation or condition would have occurred in the first place in an individual (WHOIFPI) is not same as the probability that the presentation or condition has occurred in the individual, because the presentation has occurred by 100% certainty in the individual. Differential diagnosis_sentence_23

Yet, the contributive probability fractions of each condition are assumed the same, relatively: Differential diagnosis_sentence_24

where: Differential diagnosis_sentence_25

Differential diagnosis_unordered_list_0

  • Pr(Presentation is caused by condition in individual) is the probability that the presentation is caused by condition in the individual condition without further specification refers to any candidate conditionDifferential diagnosis_item_0_0
  • Pr(Presentation has occurred in individual) is the probability that the presentation has occurred in the individual, which can be perceived and thereby set at 100%Differential diagnosis_item_0_1
  • Pr(Presentation WHOIFPI by condition) is the probability that the presentation Would Have Occurred in the First Place in the Individual by conditionDifferential diagnosis_item_0_2
  • Pr(Presentation WHOIFPI) is the probability that the presentation Would Have Occurred in the First Place in the IndividualDifferential diagnosis_item_0_3

When an individual presents with a symptom or sign, Pr(Presentation has occurred in individual) is 100% and can therefore be replaced by 1, and can be ignored since division by 1 does not make any difference: Differential diagnosis_sentence_26

The total probability of the presentation to have occurred in the individual can be approximated as the sum of the individual candidate conditions: Differential diagnosis_sentence_27

Also, the probability of the presentation to have been caused by any candidate condition is proportional to the probability of the condition, depending on what rate it causes the presentation: Differential diagnosis_sentence_28

where: Differential diagnosis_sentence_29

Differential diagnosis_unordered_list_1

  • Pr(Presentation WHOIFPI by condition) is the probability that the presentation Would Have Occurred in the First Place in the Individual by conditionDifferential diagnosis_item_1_4
  • Pr(Condition WHOIFPI) is the probability that the condition Would Have Occurred in the First Place in the IndividualDifferential diagnosis_item_1_5
  • rCondition → presentation is the rate for which a condition causes the presentation, that is, the fraction of people with condition that manifest with the presentation.Differential diagnosis_item_1_6

The probability that a condition would have occurred in the first place in an individual is approximately equal to that of a population that is as similar to the individual as possible except for the current presentation, compensated where possible by relative risks given by known risk factor that distinguish the individual from the population: Differential diagnosis_sentence_30

where: Differential diagnosis_sentence_31

Differential diagnosis_unordered_list_2

  • Pr(Condition WHOIFPI) is the probability that the condition Would Have Occurred in the First Place in the IndividualDifferential diagnosis_item_2_7
  • RRcondition is the relative risk for condition conferred by known risk factors in the individual that are not present in the populationDifferential diagnosis_item_2_8
  • Pr(Condition in population) is the probability that the condition occurs in a population that is as similar to the individual as possible except for the presentationDifferential diagnosis_item_2_9

The following table demonstrates how these relations can be made for a series of candidate conditions: Differential diagnosis_sentence_32

Differential diagnosis_table_general_1

Differential diagnosis_cell_1_0_0 Candidate condition 1Differential diagnosis_cell_1_0_1 Candidate condition 2Differential diagnosis_cell_1_0_2 Candidate condition 3Differential diagnosis_cell_1_0_3
Pr(Condition in population)Differential diagnosis_cell_1_1_0 Pr(Condition 1 in population)Differential diagnosis_cell_1_1_1 Pr(Condition 2 in population)Differential diagnosis_cell_1_1_2 Pr(Condition 3 in population)Differential diagnosis_cell_1_1_3
RRconditionDifferential diagnosis_cell_1_2_0 RR 1Differential diagnosis_cell_1_2_1 RR 2Differential diagnosis_cell_1_2_2 RR 3Differential diagnosis_cell_1_2_3
Pr(Condition WHOIFPI)Differential diagnosis_cell_1_3_0 Pr(Condition 1 WHOIFPI)Differential diagnosis_cell_1_3_1 Pr(Condition 2 WHOIFPI)Differential diagnosis_cell_1_3_2 P(Condition 3 WHOIFPI)Differential diagnosis_cell_1_3_3
rCondition → presentationDifferential diagnosis_cell_1_4_0 rCondition 1 → presentationDifferential diagnosis_cell_1_4_1 rCondition 2 → presentationDifferential diagnosis_cell_1_4_2 rCondition 3 → presentationDifferential diagnosis_cell_1_4_3
Pr(Presentation WHOIFPI by condition)Differential diagnosis_cell_1_5_0 Pr(Presentation WHOIFPI by condition 1)Differential diagnosis_cell_1_5_1 Pr(Presentation WHOIFPI by condition 2)Differential diagnosis_cell_1_5_2 Pr(Presentation WHOIFPI by condition 3)Differential diagnosis_cell_1_5_3
Pr(Presentation WHOIFPI) = the sum of the probabilities in row just aboveDifferential diagnosis_cell_1_6_0
Pr(Presentation is caused by condition in individual)Differential diagnosis_cell_1_7_0 Pr(Presentation is caused by condition 1 in individual)Differential diagnosis_cell_1_7_1 Pr(Presentation is caused by condition 2 in individual)Differential diagnosis_cell_1_7_2 Pr(Presentation is caused by condition 3 in individual)Differential diagnosis_cell_1_7_3

One additional "candidate condition" is the instance of there being no abnormality, and the presentation is only a (usually relatively unlikely) appearance of a basically normal state. Differential diagnosis_sentence_33

Its probability in the population (P(No abnormality in population)) is complementary to the sum of probabilities of "abnormal" candidate conditions. Differential diagnosis_sentence_34

Example Differential diagnosis_section_4

This example case demonstrates how this method is applied, but does not represent a guideline for handling similar real-world cases. Differential diagnosis_sentence_35

Also, the example uses relatively specified numbers with sometimes several decimals, while in reality, there are often simply rough estimations, such as of likelihoods being very high, high, low or very low, but still using the general principles of the method. Differential diagnosis_sentence_36

For an individual (who becomes the "patient" in this example), a blood test of, for example, serum calcium shows a result above the standard reference range, which, by most definitions, classifies as hypercalcemia, which becomes the "presentation" in this case. Differential diagnosis_sentence_37

A physician (who becomes the "diagnostician" in this example), who does not currently see the patient, gets to know about his finding. Differential diagnosis_sentence_38

By practical reasons, the physician considers that there is enough test indication to have a look at the patient's medical records. Differential diagnosis_sentence_39

For simplicity, let's say that the only information given in the medical records is a family history of primary hyperparathyroidism (here abbreviated as PH), which may explain the finding of hypercalcemia. Differential diagnosis_sentence_40

For this patient, let's say that the resultant hereditary risk factor is estimated to confer a relative risk of 10 (RRPH = 10). Differential diagnosis_sentence_41

The physician considers that there is enough motivation to perform a differential diagnostic procedure for the finding of hypercalcemia. Differential diagnosis_sentence_42

The main causes of hypercalcemia are primary hyperparathyroidism (PH) and cancer, so for simplicity, the list of candidate conditions that the physician could think of can be given as: Differential diagnosis_sentence_43

Differential diagnosis_unordered_list_3

  • Primary hyperparathyroidism (PH)Differential diagnosis_item_3_10
  • CancerDifferential diagnosis_item_3_11
  • Other diseases that the physician could think of (which is simply termed "other conditions" for the rest of this example)Differential diagnosis_item_3_12
  • No disease (or no abnormality), and the finding is caused entirely by statistical variabilityDifferential diagnosis_item_3_13

The probability that 'primary hyperparathyroidism' (PH) would have occurred in the first place in the individual (P(PH WHOIFPI)) can be calculated as follows: Differential diagnosis_sentence_44

Let's say that the last blood test taken by the patient was half a year ago and was normal, and that the incidence of primary hyperparathyroidism in a general population that appropriately matches the individual (except for the presentation and mentioned heredity) is 1 in 4000 per year. Differential diagnosis_sentence_45

Ignoring more detailed retrospective analyses (such as including speed of disease progress and lag time of medical diagnosis), the time-at-risk for having developed primary hyperparathyroidism can roughly be regarded as being the last half-year, because a previously developed hypercalcemia would probably have been caught up by the previous blood test. Differential diagnosis_sentence_46

This corresponds to a probability of primary hyperparathyroidism (PH) in the population of: Differential diagnosis_sentence_47

With the relative risk conferred from the family history, the probability that primary hyperparathyroidism (PH) would have occurred in the first place in the individual given from the currently available information becomes: Differential diagnosis_sentence_48

Primary hyperparathyroidism can be assumed to cause hypercalcemia essentially 100% of the time (rPH → hypercalcemia = 1), so this independently calculated probability of primary hyperparathyroidism (PH) can be assumed to be the same as the probability of being a cause of the presentation: Differential diagnosis_sentence_49

For cancer, the same time-at-risk is assumed for simplicity, and let's say that the incidence of cancer in the area is estimated at 1 in 250 per year, giving a population probability of cancer of: Differential diagnosis_sentence_50

For simplicity, let's say that any association between a family history of primary hyperparathyroidism and risk of cancer is ignored, so the relative risk for the individual to have contracted cancer in the first place is similar to that of the population (RRcancer = 1): Differential diagnosis_sentence_51

However, hypercalcemia only occurs in, very approximately, 10% of cancers, (rcancer → hypercalcemia = 0.1), so: Differential diagnosis_sentence_52

The probabilities that hypercalcemia would have occurred in the first place by other candidate conditions can be calculated in a similar manner. Differential diagnosis_sentence_53

However, for simplicity, let's say that the probability that any of these would have occurred in the first place is calculated at 0.0005 in this example. Differential diagnosis_sentence_54

For the instance of there being no disease, the corresponding probability in the population is complementary to the sum of probabilities for other conditions: Differential diagnosis_sentence_55

The probability that the individual would be healthy in the first place can be assumed to be the same: Differential diagnosis_sentence_56

The rate at which the case of no abnormal condition still ends up in a measurement of serum calcium of being above the standard reference range (thereby classifying as hypercalcemia) is, by the definition of standard reference range, less than 2.5%. Differential diagnosis_sentence_57

However, this probability can be further specified by considering how much the measurement deviates from the mean in the standard reference range. Differential diagnosis_sentence_58

Let's say that the serum calcium measurement was 1.30 mmol/L, which, with a standard reference range established at 1.05 to 1.25 mmol/L, corresponds to a standard score of 3 and a corresponding probability of 0.14% that such degree of hypercalcemia would have occurred in the first place in the case of no abnormality: Differential diagnosis_sentence_59

Subsequently, the probability that hypercalcemia would have resulted from no disease can be calculated as: Differential diagnosis_sentence_60

The probability that hypercalcemia would have occurred in the first place in the individual can thus be calculated as: Differential diagnosis_sentence_61

Subsequently, the probability that hypercalcemia is caused by primary hyperparathyroidism (PH) in the individual can be calculated as: Differential diagnosis_sentence_62

Similarly, the probability that hypercalcemia is caused by cancer in the individual can be calculated as: Differential diagnosis_sentence_63

and for other candidate conditions: Differential diagnosis_sentence_64

and the probability that there actually is no disease: Differential diagnosis_sentence_65

For clarification, these calculations are given as the table in the method description: Differential diagnosis_sentence_66

Differential diagnosis_table_general_2

Differential diagnosis_cell_2_0_0 PHDifferential diagnosis_cell_2_0_1 CancerDifferential diagnosis_cell_2_0_2 Other conditionsDifferential diagnosis_cell_2_0_3 No diseaseDifferential diagnosis_cell_2_0_4
P(Condition in population)Differential diagnosis_cell_2_1_0 0.000125Differential diagnosis_cell_2_1_1 0.002Differential diagnosis_cell_2_1_2 -Differential diagnosis_cell_2_1_3 0.997Differential diagnosis_cell_2_1_4
RRxDifferential diagnosis_cell_2_2_0 10Differential diagnosis_cell_2_2_1 1Differential diagnosis_cell_2_2_2 -Differential diagnosis_cell_2_2_3 -Differential diagnosis_cell_2_2_4
P(Condition WHOIFPI)Differential diagnosis_cell_2_3_0 0.00125Differential diagnosis_cell_2_3_1 0.002Differential diagnosis_cell_2_3_2 -Differential diagnosis_cell_2_3_3 -Differential diagnosis_cell_2_3_4
rCondition →hypercalcemiaDifferential diagnosis_cell_2_4_0 1Differential diagnosis_cell_2_4_1 0.1Differential diagnosis_cell_2_4_2 -Differential diagnosis_cell_2_4_3 0.0014Differential diagnosis_cell_2_4_4
P(hypercalcemia WHOIFPI by condition)Differential diagnosis_cell_2_5_0 0.00125Differential diagnosis_cell_2_5_1 0.0002Differential diagnosis_cell_2_5_2 0.0005Differential diagnosis_cell_2_5_3 0.0014Differential diagnosis_cell_2_5_4
P(hypercalcemia WHOIFPI) = 0.00335Differential diagnosis_cell_2_6_0
P(hypercalcemia is caused by condition in individual)Differential diagnosis_cell_2_7_0 37.3%Differential diagnosis_cell_2_7_1 6.0%Differential diagnosis_cell_2_7_2 14.9%Differential diagnosis_cell_2_7_3 41.8%Differential diagnosis_cell_2_7_4

Thus, this method estimates that the probabilities that the hypercalcemia is caused by primary hyperparathyroidism, cancer, other conditions or no disease at all are 37.3%, 6.0%, 14.9% and 41.8%, respectively, which may be used in estimating further test indications. Differential diagnosis_sentence_67

This case is continued in the example of the method described in the next section. Differential diagnosis_sentence_68

Likelihood ratio-based method Differential diagnosis_section_5

The procedure of differential diagnosis can become extremely complex when fully taking additional tests and treatments into consideration. Differential diagnosis_sentence_69

One method that is somewhat a tradeoff between being clinically perfect and being relatively simple to calculate is one that uses likelihood ratios to derive subsequent post-test likelihoods. Differential diagnosis_sentence_70

Theory Differential diagnosis_section_6

The initial likelihoods for each candidate condition can be estimated by various methods, such as: Differential diagnosis_sentence_71

Differential diagnosis_unordered_list_4

  • By epidemiology as described in previous section.Differential diagnosis_item_4_14
  • By clinic-specific pattern recognition, such as statistically knowing that patients coming into a particular clinic with a particular complaint statistically has a particular likelihood of each candidate condition.Differential diagnosis_item_4_15

One method of estimating likelihoods even after further tests uses likelihood ratios (which is derived from sensitivities and specificities) as a multiplication factor after each test or procedure. Differential diagnosis_sentence_72

In an ideal world, sensitivities and specificities would be established for all tests for all possible pathological conditions. Differential diagnosis_sentence_73

In reality, however, these parameters may only be established for one of the candidate conditions. Differential diagnosis_sentence_74

Multiplying with likelihood ratios necessitates conversion of likelihoods from probabilities to odds in favor (hereafter simply termed "odds") by: Differential diagnosis_sentence_75

However, only the candidate conditions with known likelihood ratio need this conversion. Differential diagnosis_sentence_76

After multiplication, conversion back to probability is calculated by: Differential diagnosis_sentence_77

The rest of the candidate conditions (for which there is no established likelihood ratio for the test at hand) can, for simplicity, be adjusted by subsequently multiplying all candidate conditions with a common factor to again yield a sum of 100%. Differential diagnosis_sentence_78

The resulting probabilities are used for estimating the indications for further medical tests, treatments or other actions. Differential diagnosis_sentence_79

If there is an indication for an additional test, and it returns with a result, then the procedure is repeated using the likelihood ratio of the additional test. Differential diagnosis_sentence_80

With updated probabilities for each of the candidate conditions, the indications for further tests, treatments or other actions changes as well, and so the procedure can be repeated until an end point where there no longer is any indication for currently performing further actions. Differential diagnosis_sentence_81

Such an end point mainly occurs when one candidate condition becomes so certain that no test can be found that is powerful enough to change the relative probability-profile enough to motivate any change in further actions. Differential diagnosis_sentence_82

Tactics for reaching such an end point with as few tests as possible includes making tests with high specificity for conditions of already outstandingly high-profile-relative probability, because the high likelihood ratio positive for such tests is very high, bringing all less likely conditions to relatively lower probabilities. Differential diagnosis_sentence_83

Alternatively, tests with high sensitivity for competing candidate conditions have a high likelihood ratio negative, potentially bringing the probabilities for competing candidate conditions to negligible levels. Differential diagnosis_sentence_84

If such negligible probabilities are achieved, the physician can rule out these conditions, and continue the differential diagnostic procedure with only the remaining candidate conditions. Differential diagnosis_sentence_85

Example Differential diagnosis_section_7

This example continues for the same patient as in the example for the epidemiology-based method. Differential diagnosis_sentence_86

As with the previous example of epidemiology-based method, this example case is made to demonstrate how this method is applied, but does not represent a guideline for handling similar real-world cases. Differential diagnosis_sentence_87

Also, the example uses relatively specified numbers, while in reality, there are often just rough estimations. Differential diagnosis_sentence_88

In this example, the probabilities for each candidate condition were established by an epidemiology-based method to be as follows: Differential diagnosis_sentence_89

Differential diagnosis_table_general_3

Differential diagnosis_cell_3_0_0 PHDifferential diagnosis_cell_3_0_1 CancerDifferential diagnosis_cell_3_0_2 Other conditionsDifferential diagnosis_cell_3_0_3 No diseaseDifferential diagnosis_cell_3_0_4
ProbabilityDifferential diagnosis_cell_3_1_0 37.3%Differential diagnosis_cell_3_1_1 6.0%Differential diagnosis_cell_3_1_2 14.9%Differential diagnosis_cell_3_1_3 41.8%Differential diagnosis_cell_3_1_4

These percentages could also have been established by experience at the particular clinic by knowing that these are the percentages for final diagnosis for people presenting to the clinic with hypercalcemia and having a family history of primary hyperparathyroidism. Differential diagnosis_sentence_90

The condition of highest profile-relative probability (except "no disease") is primary hyperparathyroidism (PH), but cancer is still of major concern, because if it is the actual causative condition for the hypercalcemia, then the choice of whether to treat or not likely means life or death for the patient, in effect potentially putting the indication at a similar level for further tests for both of these conditions. Differential diagnosis_sentence_91

Here, let's say that the physician considers the profile-relative probabilities of being of enough concern to indicate sending the patient a call for a doctor's visit, with an additional visit to the medical laboratory for an additional blood test complemented with further analyses, including parathyroid hormone for the suspicion of primary hyperparathyroidism. Differential diagnosis_sentence_92

For simplicity, let's say that the doctor first receives the blood test (in formulas abbreviated as "BT") result for the parathyroid hormone analysis, and that it showed a parathyroid hormone level that is elevated relatively to what would be expected by the calcium level. Differential diagnosis_sentence_93

Such a constellation can be estimated to have a sensitivity of approximately 70% and a specificity of approximately 90% for primary hyperparathyroidism. Differential diagnosis_sentence_94

This confers a likelihood ratio positive of 7 for primary hyperparathyroidism. Differential diagnosis_sentence_95

The probability of primary hyperparathyroidism is now termed Pre-BTPH because it corresponds to before the blood test (Latin preposition prae means before). Differential diagnosis_sentence_96

It was estimated at 37.3%, corresponding to an odds of 0.595. Differential diagnosis_sentence_97

With the likelihood ratio positive of 7 for the blood test, the test odds is calculated as: Differential diagnosis_sentence_98

where: Differential diagnosis_sentence_99

Differential diagnosis_unordered_list_5

  • Odds(PostBTPH) is the odds for primary hyperparathyroidism after the blood test for parathyroid hormoneDifferential diagnosis_item_5_16
  • Odds(PreBTPH is the odds in favor of primary hyperparathyroidism before the blood test for parathyroid hormoneDifferential diagnosis_item_5_17
  • LH(BT) is the likelihood ratio positive for the blood test for parathyroid hormoneDifferential diagnosis_item_5_18

An Odds(PostBTPH) of 4.16 is again converted to the corresponding probability by: Differential diagnosis_sentence_100

The sum of the probabilities for the rest of the candidate conditions should therefore be: Differential diagnosis_sentence_101

Before the blood test for parathyroid hormone, the sum of their probabilities were: Differential diagnosis_sentence_102

Therefore, to conform to a sum of 100% for all candidate conditions, each of the other candidates must be multiplied by a correcting factor: Differential diagnosis_sentence_103

For example, the probability of cancer after the test is calculated as: Differential diagnosis_sentence_104

The probabilities for each candidate conditions before and after the blood test are given in following table: Differential diagnosis_sentence_105

Differential diagnosis_table_general_4

Differential diagnosis_cell_4_0_0 PHDifferential diagnosis_cell_4_0_1 CancerDifferential diagnosis_cell_4_0_2 Other conditionsDifferential diagnosis_cell_4_0_3 No diseaseDifferential diagnosis_cell_4_0_4
P(PreBT)Differential diagnosis_cell_4_1_0 37.3%Differential diagnosis_cell_4_1_1 6.0%Differential diagnosis_cell_4_1_2 14.9%Differential diagnosis_cell_4_1_3 41.8%Differential diagnosis_cell_4_1_4
P(PostBT)Differential diagnosis_cell_4_2_0 80.6%Differential diagnosis_cell_4_2_1 1.9%Differential diagnosis_cell_4_2_2 4.6%Differential diagnosis_cell_4_2_3 12.9%Differential diagnosis_cell_4_2_4

These "new" percentages, including a profile-relative probability of 80% for primary hyperparathyroidism, underlie any indications for further tests, treatments or other actions. Differential diagnosis_sentence_106

In this case, let's say that the physician continues the plan for the patient to attend a doctor's visit for further checkup, especially focused at primary hyperparathyroidism. Differential diagnosis_sentence_107

A doctor's visit can, theoretically, be regarded as a series of tests, including both questions in a medical history as well as components of a physical examination, where the post-test probability of a previous test can be used as the pre-test probability of the next. Differential diagnosis_sentence_108

The indications for choosing the next test is dynamically influenced by the results of previous tests. Differential diagnosis_sentence_109

Let's say that the patient in this example is revealed to have at least some of the symptoms and signs of depression, bone pain, joint pain or constipation of more severity than what would be expected by the hypercalcemia itself, supporting the suspicion of primary hyperparathyroidism, and let's say that the likelihood ratios for the tests, when multiplied together, roughly results in a product of 6 for primary hyperparathyroidism. Differential diagnosis_sentence_110

The presence of unspecific pathologic symptoms and signs in the history and examination are often concurrently indicative of cancer as well, and let's say that the tests gave an overall likelihood ratio estimated at 1.5 for cancer. Differential diagnosis_sentence_111

For other conditions, as well as the instance of not having any disease at all, let's say that it's unknown how they are affected by the tests at hand, as often happens in reality. Differential diagnosis_sentence_112

This gives the following results for the history and physical examination (abbreviated as P&E): Differential diagnosis_sentence_113

Differential diagnosis_table_general_5

Differential diagnosis_cell_5_0_0 PHDifferential diagnosis_cell_5_0_1 CancerDifferential diagnosis_cell_5_0_2 Other conditionsDifferential diagnosis_cell_5_0_3 No diseaseDifferential diagnosis_cell_5_0_4
P(PreH&E)Differential diagnosis_cell_5_1_0 80.6%Differential diagnosis_cell_5_1_1 1.9%Differential diagnosis_cell_5_1_2 4.6%Differential diagnosis_cell_5_1_3 12.9%Differential diagnosis_cell_5_1_4
Odds(PreH&E)Differential diagnosis_cell_5_2_0 4.15Differential diagnosis_cell_5_2_1 0.019Differential diagnosis_cell_5_2_2 0.048Differential diagnosis_cell_5_2_3 0.148Differential diagnosis_cell_5_2_4
Likelihood ratio by H&EDifferential diagnosis_cell_5_3_0 6Differential diagnosis_cell_5_3_1 1.5Differential diagnosis_cell_5_3_2 -Differential diagnosis_cell_5_3_3 -Differential diagnosis_cell_5_3_4
Odds(PostH&E)Differential diagnosis_cell_5_4_0 24.9Differential diagnosis_cell_5_4_1 0.0285Differential diagnosis_cell_5_4_2 -Differential diagnosis_cell_5_4_3 -Differential diagnosis_cell_5_4_4
P(PostH&E)Differential diagnosis_cell_5_5_0 96.1%Differential diagnosis_cell_5_5_1 2.8%Differential diagnosis_cell_5_5_2 -Differential diagnosis_cell_5_5_3 -Differential diagnosis_cell_5_5_4
Sum of known P(PostH&E)Differential diagnosis_cell_5_6_0 98.9%Differential diagnosis_cell_5_6_1
Sum of the rest P(PostH&E)Differential diagnosis_cell_5_7_0 1.1%Differential diagnosis_cell_5_7_1
Sum of the rest P(PreH&E)Differential diagnosis_cell_5_8_0 4.6% + 12.9% = 17.5%Differential diagnosis_cell_5_8_1
Correcting factorDifferential diagnosis_cell_5_9_0 1.1% / 17.5% = 0.063Differential diagnosis_cell_5_9_1
After correctionDifferential diagnosis_cell_5_10_0 -Differential diagnosis_cell_5_10_1 -Differential diagnosis_cell_5_10_2 0.3%Differential diagnosis_cell_5_10_3 0.8%Differential diagnosis_cell_5_10_4
P(PostH&E)Differential diagnosis_cell_5_11_0 96.1%Differential diagnosis_cell_5_11_1 2.8%Differential diagnosis_cell_5_11_2 0.3%Differential diagnosis_cell_5_11_3 0.8%Differential diagnosis_cell_5_11_4

These probabilities after the history and examination may make the physician confident enough to plan the patient for surgery for a parathyroidectomy to resect the affected tissue. Differential diagnosis_sentence_114

At this point, the probability of "other conditions" is so low that the physician cannot think of any test for them that could make a difference that would be substantial enough to form an indication for such a test, and the physician thereby practically regards "other conditions" as ruled out, in this case not primarily by any specific test for such other conditions that were negative, but rather by the absence of positive tests so far. Differential diagnosis_sentence_115

For "cancer", the cutoff at which to confidently regard it as ruled out may be more stringent because of severe consequences of missing it, so the physician may consider that at least a histopathologic examination of the resected tissue is indicated. Differential diagnosis_sentence_116

This case is continued in the example of Combinations in corresponding section below. Differential diagnosis_sentence_117

Coverage of candidate conditions Differential diagnosis_section_8

The validity of both the initial estimation of probabilities by epidemiology and further workup by likelihood ratios are dependent of inclusion of candidate conditions that are responsible for as large part as possible of the probability of having developed the condition, and it is clinically important to include those where relatively fast initiation of therapy is most likely to result in greatest benefit. Differential diagnosis_sentence_118

If an important candidate condition is missed, no method of differential diagnosis will supply the correct conclusion. Differential diagnosis_sentence_119

The need to find more candidate conditions for inclusion increases with increasing severity of the presentation itself. Differential diagnosis_sentence_120

For example, if the only presentation is a deviating laboratory parameter and all common harmful underlying conditions have been ruled out, then it may be acceptable to stop finding more candidate conditions, but this would much more likely be unacceptable if the presentation would have been severe pain. Differential diagnosis_sentence_121

Combinations Differential diagnosis_section_9

If two conditions get high post-test probabilities, especially if the sum of the probabilities for conditions with known likelihood ratios become higher than 100%, then the actual condition is a combination of the two. Differential diagnosis_sentence_122

In such cases, that combined condition can be added to the list of candidate conditions, and the calculations should start over from the beginning. Differential diagnosis_sentence_123

To continue the example used above, let's say that the history and physical examination was indicative of cancer as well, with a likelihood ratio of 3, giving an Odds(PostH&E) of 0.057, corresponding to a P(PostH&E) of 5.4%. Differential diagnosis_sentence_124

This would correspond to a "Sum of known P(PostH&E)” of 101.5%. Differential diagnosis_sentence_125

This is an indication for considering a combination of primary hyperparathyroidism and cancer, such as, in this case, a parathyroid hormone-producing parathyroid carcinoma. Differential diagnosis_sentence_126

A recalculation may therefore be needed, with the first two conditions being separated into "primary hyperparathyroidism without cancer", "cancer without primary hyperparathyroidism" as well as "combined primary hyperparathyroidism and cancer", and likelihood ratios being applied to each condition separately. Differential diagnosis_sentence_127

In this case, however, tissue has already been resected, wherein a histopathologic examination can be performed that includes the possibility of parathyroid carcinoma in the examination (which may entail appropriate sample staining). Differential diagnosis_sentence_128

Let's say that the histopathologic examination confirms primary hyperparathyroidism, but also showed a malignant pattern. Differential diagnosis_sentence_129

By an initial method by epidemiology, the incidence of parathyroid carcinoma is estimated at about 1 in 6 million people per year, giving a very low probability before taking any tests into consideration. Differential diagnosis_sentence_130

In comparison, the probability that a non-malignant primary hyperparathyroidism would have occurred at the same time as an unrelated non-carcinoma cancer that presents with malignant cells in the parathyroid gland is calculated by multiplying the probabilities of the two. Differential diagnosis_sentence_131

The resultant probability is, however, much smaller than the 1 in 6 million. Differential diagnosis_sentence_132

Therefore, the probability of parathyroid carcinoma may still be close to 100% after histopathologic examination despite the low probability of occurring in the first place. Differential diagnosis_sentence_133

Machine differential diagnosis Differential diagnosis_section_10

Further information: Clinical decision support system Differential diagnosis_sentence_134

Machine differential diagnosis is the use of computer software to partly or fully make a differential diagnosis. Differential diagnosis_sentence_135

It may be regarded as an application of artificial intelligence. Differential diagnosis_sentence_136

Many studies demonstrate improvement of quality of care and reduction of medical errors by using such decision support systems. Differential diagnosis_sentence_137

Some of these systems are designed for a specific medical problem such as schizophrenia, Lyme disease or ventilator-associated pneumonia. Differential diagnosis_sentence_138

Others such as ESAGIL, Iliad, QMR, DiagnosisPro, VisualDx, Isabel, ZeroMD, DxMate, , and Physician Cognition are designed to cover all major clinical and diagnostic findings to assist physicians with faster and more accurate diagnosis. Differential diagnosis_sentence_139

However, these tools all still require advanced medical skills to rate symptoms and choose additional tests to deduce the probabilities of different diagnoses. Differential diagnosis_sentence_140

Machine differential diagnosis is also currently unable to diagnose multiple concurrent disorders. Differential diagnosis_sentence_141

Thus, non-professionals should still see a health care provider for a proper diagnosis. Differential diagnosis_sentence_142

History Differential diagnosis_section_11

The method of differential diagnosis was first suggested for use in the diagnosis of mental disorders by Emil Kraepelin. Differential diagnosis_sentence_143

It is more systematic than the old-fashioned method of diagnosis by gestalt (impression). Differential diagnosis_sentence_144

Alternative medical meanings Differential diagnosis_section_12

'Differential diagnosis' is also used more loosely, to refer simply to a list of the most common causes of a given symptom, to a list of disorders similar to a given disorder, or to such lists when they are annotated with advice on how to narrow the list down (French's Index of Differential Diagnosis is an example). Differential diagnosis_sentence_145

Thus, a differential diagnosis in this sense is medical information specially organized to aid in diagnosis. Differential diagnosis_sentence_146

Usage apart from in medicine Differential diagnosis_section_13

Methods similar to those of differential diagnostic processes in medicine are also used by biological taxonomists to identify and classify organisms, living and extinct. Differential diagnosis_sentence_147

For example, after finding an unknown species, there can first be a listing of all potential species, followed by ruling out of one by one until, optimally, only one potential choice remains. Differential diagnosis_sentence_148

Similar procedures may be used by plant and maintenance engineers and automotive mechanics, and used to be used in diagnosing faulty electronic circuitry. Differential diagnosis_sentence_149

In art Differential diagnosis_section_14

The American television medical drama House featuring Hugh Laurie as the main protagonist Dr. Differential diagnosis_sentence_150 Gregory House who leads a team of diagnosticians at the fictional Princeton–Plainsboro Teaching Hospital in New Jersey revolves around using differential diagnostics procedures in a bid to come up with the right diagnosis. Differential diagnosis_sentence_151

Throughout the series, the doctors have diagnosed such diseases as mastocytosis, Plummer's disease, rabies, Kawasaki's syndrome, smallpox, Rickettsialpox, and dozens of others. Differential diagnosis_sentence_152

See also Differential diagnosis_section_15

Differential diagnosis_unordered_list_6

Credits to the contents of this page go to the authors of the corresponding Wikipedia page: en.wikipedia.org/wiki/Differential diagnosis.