CN106021968A - Clinical intelligent blood gas analysis and diagnosis instrument - Google Patents
Clinical intelligent blood gas analysis and diagnosis instrument Download PDFInfo
- Publication number
- CN106021968A CN106021968A CN201610557630.8A CN201610557630A CN106021968A CN 106021968 A CN106021968 A CN 106021968A CN 201610557630 A CN201610557630 A CN 201610557630A CN 106021968 A CN106021968 A CN 106021968A
- Authority
- CN
- China
- Prior art keywords
- data
- data processor
- hco3
- paco
- blood gas
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Investigating Or Analysing Biological Materials (AREA)
Abstract
The invention provides a clinical intelligent blood gas analysis and diagnosis instrument. The instrument comprises a human-machine interface unit, a power supply unit, a host unit, a scanner, a database, a data processor and a memory. The instrument is characterized in that the human-machine interface unit, the power supply unit and the data processor are connected with the host unit, the database is connected with the data processor, the scanner is connected with the memory, and the data processor is connected with the memory. The clinical intelligent blood gas analysis and diagnosis instrument is reasonable in design and convenient to use; and a current blood gas analyzer is embedded into intelligent data computation and graph locating software, and accurate reference diagnosis on the detected serum electrolyte and blood acid-alkali balance condition indexes of a patient can be rapidly made.
Description
Technical field
Present invention relates particularly to a kind of clinical intelligence blood gas analysis diagnostic apparatus.
Background technology
At present blood gas analyzer is merely able to Accurate Determining to serum electrolyte and blood acid-base balance status index, such as: Na+、K+、Cl-、H+Concentration and pH, arterial blood CO2Dividing potential drop (paCO2), standard bicarbonate (SB) and actual bicarbonate (AB), slow
Rushing alkali (BB), buffuer excess (BE), aninon gap (AG) etc., vim and vigour detection is that diagnosis the decisive of acid base imbalance type depends on
According to, use compensatory predicted value and soda acid figure to contribute to acid base imbalance and make correct judgement, but to these indexs
Correct Analysis judges and uses compensatory predicted value and soda acid figure that acid base imbalance is made correct diagnosis, in addition it is also necessary to medical matters people
Member expends energy reckoning and reaches a conclusion.Owing to being affected by the clinical knowledge of medical worker and index are complicated and changeable, it is difficult to make
Diagnostic judges accurately.
Summary of the invention
It is an object of the invention to as solving above-mentioned deficiency, it is provided that a kind of clinical intelligence blood gas analysis diagnostic apparatus.
It is an object of the invention to be achieved through the following technical solutions:
A kind of clinical intelligence blood gas analysis diagnostic apparatus, including human and machine interface unit, power subsystem, main computer unit, scanner,
Data base, data processor and memorizer, human and machine interface unit, power subsystem and data processor all connect main computer unit, count
According to storehouse connect data processor, scanner connect memorizer, data processor connect memorizer, patient take vim and vigour checklist it
After, by document directly facing to scanning port scanning in blood gas analyzer, data are acquired by analyser, and memorizer is to collecting
Information store after feed back in data processor, data processor receive memorizer transmission information after, according to number
According to the preset algorithm in processor, blood gas data is calculated, calculate the pass bond number of patient's blood gas analysis through formula
According to, then it is analyzed by the data being provided each disease in data base, thus judges that the suffered from soda acid of patient is put down
The type that weighing apparatus is disorderly, it was therefore concluded that feeding back to main frame, main frame outputs results to man machine interface, typing before store in data base
The data message for disease.
Preset algorithm step is as follows:
Step one, judge the internal requirement of vim and vigour numerical value: according to Henderseon-Hasselbach formula: [H+]=
24×(PaCO2)/[HCO3-], the internal requirement of assessment vim and vigour numerical value, judge according to pH and [H+] numerical comparatives table, if pH
[H+] numerical value is inconsistent, illustrate that this vim and vigour result is probably mistake, if consistent, enter next step；
Step 2, according to pH value judge be alkalemia or acidemia: pH<7.35 acidemia pH>7.45 alkalemia；Even if
PH value also has three kinds of situations in normal range (7.35-7.45), needs to check PaCO2,HCO3-, and aninon gap (AG) is true
Fixed: normal person: indices normal range；Compensated acidosis or compensated alkalosis；Destructive acid base imbalance；
Step 3, according to pH value and PaCO2Changing walking direction is primary respiratory obstacle or primary metabolic disorder,
When primary respiratory obstacle, pH value and PaCO2Change in opposite direction；When primary metabolic disorder, pH value and PaCO2Change
Direction is identical；
Step 4, calculate anticipated compensatory zone by anticipated compensatory formula: in the range of is compensatory, otherwise loses compensatory conjunction
And other poisoning, it is shown in Table 3；
Step 5, calculating aninon gap: Aniongap:AG=[Na+]-[Cl-]-[HCO3-]；
Step 6, calculating Δ AG: Δ AG=record the normal AG of AG-；
[the HCO3 estimated-]=Δ AG+ records [HCO3-]；
IF ＜ 22 merges metabolic acidosis, and IF ＞ 26 merges metabolic alkalosis, and between IF22-26, explanation is pure
Acid base imbalance.
The present invention has a following beneficial effect:
The present invention is reasonable in design, easy to use, and current blood gas analyzer embeds intelligent data computing and chart location
Software, to serum electrolyte and the blood acid-base balance status index of patient being detected, quickly makes accurately with reference to diagnosis.
Accompanying drawing explanation
Fig. 1 is the overall structure schematic diagram of the present invention.
Detailed description of the invention
The present invention is further illustrated below in conjunction with the accompanying drawings:
As it is shown in figure 1, a kind of clinical intelligence blood gas analysis diagnostic apparatus, including human and machine interface unit 1, power subsystem 2, main frame
Unit 3, scanner 4, data base 5, data processor 6 and memorizer 7, human and machine interface unit 1, power subsystem 2 and data process
Device 6 all connects main computer unit 3, and data base 5 connects data processor 6, and scanner 4 connects memorizer 7, and data processor 6 connects
Memorizer 7, after patient takes vim and vigour checklist, by document directly facing to scanning port scanning, analyser in blood gas analyzer
Being acquired data, memorizer feeds back in data processor after storing the information collected, and data processor connects
After receiving the information of memorizer transmission, according to the preset algorithm in data processor, blood gas data is calculated, through formula
Calculate the critical data of patient's blood gas analysis, then carried out by the data being provided each disease in data base
Analyze, thus judge the type of the suffered from acid base imbalance of patient, it was therefore concluded that feeding back to main frame, main frame outputs results to man-machine
Interface, the data message for disease of typing before store in data base.
Preset algorithm step is as follows:
Step one, judge the internal requirement of vim and vigour numerical value: according to Henderseon-Hasselbach formula: [H+]=
24×(PaCO2)/[HCO3-], the internal requirement of assessment vim and vigour numerical value, judge according to pH and [H+] numerical comparatives table, if pH
[H+] numerical value is inconsistent, illustrate that this vim and vigour result is probably mistake, if consistent, enter next step；
Step 2, according to pH value judge be alkalemia or acidemia: pH<7.35 acidemia pH>7.45 alkalemia；Even if
PH value also has three kinds of situations in normal range (7.35-7.45), needs to check PaCO2,HCO3-, and aninon gap (AG) is true
Fixed: normal person: indices normal range；Compensated acidosis or compensated alkalosis；Destructive acid base imbalance；
Step 3, according to pH value and PaCO2Changing walking direction is primary respiratory obstacle or primary metabolic disorder,
When primary respiratory obstacle, pH value and PaCO2Change in opposite direction；When primary metabolic disorder, pH value and PaCO2Change
Direction is identical；
Step 4, calculate anticipated compensatory zone by anticipated compensatory formula: in the range of is compensatory, otherwise loses compensatory conjunction
And other poisoning, it is shown in Table 3；
Step 5, calculating aninon gap: Aniongap:AG=[Na+]-[Cl-]-[HCO3-]；
Step 6, calculating Δ AG: Δ AG=record the normal AG of AG-；
[the HCO3 estimated-]=Δ AG+ records [HCO3-]；
IF ＜ 22 merges metabolic acidosis, and IF ＞ 26 merges metabolic alkalosis, and between IF22-26, explanation is pure
Acid base imbalance.
1. information gathering: after patient takes vim and vigour checklist, by document directly facing to scanning port in blood gas analyzer
Scanning, data are acquired by analyser；
2. memorizer: memorizer feeds back in data processor after storing the information collected；
3. data processor: after data processor receives the information of memorizer transmission, blood gas data is calculated, warp
Cross formula and calculate the critical data of patient's blood gas analysis, then by the data being provided each disease in data base
It is analyzed, thus judges the type of the suffered from acid base imbalance of patient, it was therefore concluded that feed back to main frame, main frame output result
To man machine interface；
Data base: the data message for disease of typing before store in data base
Embodiment
22 years old diabetic men of case 1 one patient there occurs serious respiratory tract infection, and inspection numerical value is as follows？
Na+=128 K+=5.9 Cl-=94 HCO3-=6 PCO2=15 PO2=102pH=7.19 BG=324
Calculation step:
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=60 synopsis 1:PH7.20 is that 63 data are true
Step2: alkalemia or acidemia
PH=7.19 7.35 acidemia
Step3: primary is respiratory or metabolic？
PH=7.19, PCO2=15 reduce in the same direction: primary metabolic acidosis
Step4: in compensatory zone？
Anticipated PaCO2=1.5 × 6+8 ± 2=17 ± 2 so, the PaCO recorded2=15 be anticipated 15-19 it
In, so compensatory within normal range, the most do not lose compensatory.
Step5: aninon gap
Aniongap:AG=[Na+]-[Cl-]-[HCO3-]=128-94-6=28 > 12.In the highest AG metabolic acid
Poison.
Step6:ΔAG
[HCO3-]=18+6=24 that [HCO3-]=Δ AG+ anticipated for Δ AG=28-10=18 records estimates
[HCO3-]=18+6=24 is between 22-26.
Therefore, this patient is simple metabolic acidosis,compensated.Conclusion: diabetic ketoacidosis.
32 years old male patient of case 2: patient, has chronic drinking medical history, and to emergency department visits, there is Nausea and vomiting in main suit
With stomachache three days.Ate before four hours and ordered in the hope of alleviating pain.Clear consciousness, health check-up does not has anomaly.
Na+=132 K+=3.9 Cl-=82 HCO3-=4 PCO2=10 PO2=110pH=7.25 BG=68 BUN
=14bloodalcohol=106
Urinalysis: protein-, ketones-, has crystallization.
Calculation step:
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=60 synopsis 1:PH7.25 is that 56 data are true
Step2: alkalemia or acidemia: pH=7.25 7.35 acidemia
Step3: primary is respiratory or metabolic？PH=7.25, PCO2=10 reduce in the same direction: primary metabolic
Acidosis
Step4: in compensatory zone？Anticipated PaCO2=1.5 × 4+8 ± 2=14 ± 2 so, the PaCO recorded2=
10 is outside anticipated 12-16, i.e. has respiratory alkalosis.
Step5: aninon gap: AG=[Na+]-[Cl-]-[HCO3-] that is high AG metabolism of=132-82-4=46 > 12
Property acidosis.
Therefore, this patient is except high AG generation acid also for Step6: Δ AG=46-12=34 anticipated [HCO3-]=34+4=38
There is metabolic alkalosis (If ＞ 26, metabolic alkalosis)
Conclusion: the metabolic acidosis of high AG that ethylene glycol poisoning causes, the metabolic alkalosis that vomiting causes, and deposit and exhale
Absorption alkalosis, is a triple acid base imbalance.
3: one 46 years old women of case, the dyspnea gradually increased the weight of because of COPD, CXR prompting bottom right lung oozes out.
Na+=140 K+=4.1 Cl-=98 HCO3-=30 PCO2=66 PO2=38pH=7.28
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=52.8 synopsis 1:PH7.30 is that 50 data are true
Step2: alkalemia or acidemia: pH=7.28 7.35 acidemia
Step3: primary is respiratory or metabolic？PH=7.28, PCO2In the acid of=66 40 primary respiratories
Poison
Step4: in compensatory zone？
Acute respiratory acidosis [HCO3 -] rising=24+ [PaCO2-40)/10] ± 1.5=24+ (66-40)/10 ±
1.5=28.1-25.1.
Chronic respiratory acidosis=24+0.4 [(PaCO2-40)] ± 3=24+0.4 (66-40) ± 3=37.4-31.4
30 secondary metabolic acidosiss
4: one women of 47 years old of case, after heavy drinking because of pernicious, vomit and generate heat and be admitted to hospital.
Na+=140 K+=2.9 Cl-=96 HCO3-=18 PCO2=49 PO2=45pH=7.15 BG=96
Urinalysis: ketoboidies 4+X line prompting upper left leaf, right middle lobe and the exudative change of right lower lobe.Step1: whether data
It is consistent？
[H+]=24 × (PaCO2)/[HCO3-]=65.33 synopsis 1:PH7.15 is that 71 data are true
Step2: alkalemia or acidemia: pH=7.15 7.35 acidemia
Step3: primary is respiratory or metabolic？PH=7.15, PaCO2=49 respiratory acidosis.
Step4: in compensatory zone？
Acute respiratory acidosis [HCO3 -] rising=24+ [PaCO2-40)/10] ± 1.5=26.4-23.4 respiratory acid
Poisoning metabolic acidosis
Step5: aninon gap: AG=[Na+]-[Cl-]-[HCO3-]=140-96-18=26 > 12 that is high AG generation
Thanking property acidosis.
Step6: the normal AG=26-10=16 of AG-that Δ AG=records
[HCO3-]=16+18=34 that [the HCO3-]=Δ AG+ estimated records
If ＞ 26, metabolic alkalosis.
This patient is triple acid base imbalance, and pneumonia causes respiratory acidosis, is addicted to drink and causes in Alcoholic ketosis acid
Poison, vomiting causes metabolic alkalosis.
5: one 62 years old male of case, because serious dyspnea hospitalizes ICU, find some bottles at one's side, including furosemide,
Enalapril, potassium chloride and aspirin.Chest X ray prompting pulmonary edema.
Na=140 K=2.8 Cl=108 HCO3=10 PCO2=16 PO2=106pH=7.42
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=38.4 synopsis 1:PH7.4 is that 40 data are true
Step2: alkalemia or acidemia: pH=7.42, normally
Step3: primary is respiratory or metabolic？But, pH=7.42 and PCO2=16 is the most inconsistent, anxious
Property respiratory alkalosis.
Step4: in compensatory zone？
The compensatory formula of acute respiration alkalosis: prediction HCO3 -=24-0.2 △ PaCO2± 2.5=24.9-19.9 HCO3=
10 metabolic acidosiss
Step5: aninon gap: AG=[Na+]-[Cl-]-[HCO3-] A=140-108-10=22 12, high anion
Gap metabolic acidosis
Step6: the normal AG=22-12=10 of AG-that Δ AG=records
[HCO3-]=10+10=20 ＜ 22 that [the HCO3-]=Δ AG+ estimated records merges metabolic acidosis
In the respiratory alkali that this patient is the high AG metabolic acidosis that causes of a salicylism and pulmonary edema causes
Poison
6: one women of 28 years old of case, there is inexplicable delirium after holding the motorcycle of organic solvent wiping oneself in her
It is admitted to hospital with acidosis.
Na=139 K=1.7 Cl-=115 HCO3-=12 PCO2=28 PO2=92 pH=7.24BUN=7 urines
Analyze: pH=6.5
Specific gravity of urine 1.020 does not has cell and crystallization
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=56 synopsis 1:PH7.25 is that 56 data are true
Step2: alkalemia or acidemia: acidemia
Step3: primary is respiratory or metabolic？PCO2=28pH=7.24 homophase, metabolic acidosis
Step4: in compensatory zone？Anticipated PaCO2=1.5 × 12+8 ± 2=26 ± 2, PaCO2=28 is in advance
Within the 24-28 of meter, in compensatory normal range.
Step5: aninon gap: AG=[Na+]-[Cl-]-[HCO3-]=139-115-12=12, AG GPS survey chlorine
Metabolic acidosis.
Step6: be not necessary to survey Δ AG.
Case 7: one chronic emphysema patient's electrolyte and blood gas analysis following Na=140 Cl-=90HCO3-=40
PCO2=67 pH=7.40
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=40.2 synopsis 1:PH7.40 is that 40 data are true
Step2: alkalemia or acidemia: normal
Step3: primary is respiratory or metabolic？PCO2=67pH=7.40 not homophase, respiratory acidosis
Step4: in compensatory zone？
Chronic respiratory acidosis=24+0.4 [(PaCO2-40)] ± 3=24+0.4 (67-40) ± 3=37.4-31.4
40 metabolic alkalosis.
Case 8: patient's emergency treatment is admitted to hospital: electrolyte and blood gas analysis following Na=142 Cl-=96HCO3-=26 PCO2=
44 pH=7.40
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=40.6 synopsis 1:PH7.40 is that 40 data are true
Step2: alkalemia or acidemia: normal
Step3: primary is respiratory or metabolic？All look into AG=142-96-26=20 12 in normal range,
Generation acid high for AG
Step4: in compensatory zone？Anticipated PaCO2=1.5 × 26+8 ± 2=47 ± 2=49-45
Tep6: the normal AG=20-12=8 of AG-that Δ AG=records
[HCO3-]=8,+26,=34 26 that [the HCO3-]=Δ AG+ estimated records merges metabolic alkalosis
Two weeks electrolyte of case 9: patients with cor pulmonale and blood gas analysis following Na=140 Cl-=75HCO3-=36
PCO2=66 pH=7.34
Whether Step1: data are consistent？
[H+]=24 × (PaCO2)/[HCO3-]=44. synopsis 1:PH7.35 is that 45 data are true
Step2: alkalemia or acidemia: pH=7.34 acidemia
Step3: primary is respiratory or metabolic？PH=7.34PCO2=66 is anti-phase, respiratory acidosis
Step4: in compensatory zone？Chronic respiratory acidosis=24+0.4 [(PaCO2-40)] ± 3=24+0.4
(66-40) ± 3=37.4-31.4 30 secondary metabolic acidosis
Step5: aninon gap: AG=[Na+]-[Cl-]-[HCO3-] AG=140-75-36=29 12,
Generation acid high for AG
Tep6: the normal AG=29-12=17 of AG-that Δ AG=records
[HCO3-]=17,+36,=53 26 that [the HCO3-]=Δ AG+ estimated records merges metabolic alkalosis.
Table 1
Table 2
Table 3
Note: 1. " Δ " person is changing value, represents absolute value without " Δ ".
The most compensatory limit: refer to the compensatory minima that can reach of simple type acid base imbalance or maximum.
The most compensatory time limit: refer to the internal time reached needed for maximum compensation response.
Table 4
Table 5: partial miscibility and complexity acid base imbalance
Claims (2)
1. a clinical intelligence blood gas analysis diagnostic apparatus, including human and machine interface unit, power subsystem, main computer unit, scanner, number
According to storehouse, data processor and memorizer, it is characterised in that: human and machine interface unit, power subsystem and data processor all connect master
Machine unit, Database Connection data processor, scanner connects memorizer, and data processor connects memorizer, and patient takes blood
After gas checklist, by document directly facing to scanning port scanning in blood gas analyzer, data are acquired by analyser, storage
Device feeds back in data processor after storing the information collected, and data processor receives the information of memorizer transmission
After, according to the preset algorithm in data processor, blood gas data is calculated, calculate patient's blood gas analysis through formula
Critical data, be then analyzed by the data being provided each disease in data base, thus judge patient institute
Suffering from the type of acid base imbalance, it was therefore concluded that feed back to main frame, main frame outputs results to man machine interface, stores in data base
The data message for disease of typing before.
A kind of clinical intelligence blood gas analysis diagnostic apparatus the most according to claim 1, described preset algorithm step is as follows:
Step one, judge the internal requirement of vim and vigour numerical value: according to Henderseon-Hasselbach formula: [H+]=24 ×
(PaCO2)/[HCO3-], the internal requirement of assessment vim and vigour numerical value, judge according to pH and [H+] numerical comparatives table, if pH and [H+] numerical value is inconsistent, illustrate that this vim and vigour result is probably mistake, if consistent, enter next step；
Step 2, according to pH value judge be alkalemia or acidemia: pH<7.35 acidemia pH>7.45 alkalemia；Even if pH value
Also there are three kinds of situations in normal range (7.35-7.45), need to check PaCO2,HCO3-, and aninon gap (AG) determines: just
Ordinary person: indices normal range；Compensated acidosis or compensated alkalosis；Destructive acid base imbalance；
Step 3, according to pH value and PaCO2Changing walking direction is primary respiratory obstacle or primary metabolic disorder, former
When sending out respiratory obstacle, pH value and PaCO2Change in opposite direction；When primary metabolic disorder, pH value and PaCO2Change direction
Identical；
Step 4, calculate anticipated compensatory zone by anticipated compensatory formula: in the range of is compensatory, otherwise lose compensatory merging its
Its poisoning, is shown in Table 3；
Step 5, calculating aninon gap: Aniongap:AG=[Na+]-[Cl-]-[HCO3-]；
Step 6, calculating Δ AG: Δ AG=record the normal AG of AG-；
[the HCO3 estimated-]=Δ AG+ records [HCO3-]；
IF ＜ 22 merges metabolic acidosis, and IF ＞ 26 merges metabolic alkalosis, and between IF22-26, explanation is the acid of pure
Soda balance is disorderly.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610557630.8A CN106021968A (en) | 2016-07-13 | 2016-07-13 | Clinical intelligent blood gas analysis and diagnosis instrument |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610557630.8A CN106021968A (en) | 2016-07-13 | 2016-07-13 | Clinical intelligent blood gas analysis and diagnosis instrument |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106021968A true CN106021968A (en) | 2016-10-12 |
Family
ID=57118957
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610557630.8A Pending CN106021968A (en) | 2016-07-13 | 2016-07-13 | Clinical intelligent blood gas analysis and diagnosis instrument |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106021968A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107610782A (en) * | 2017-08-28 | 2018-01-19 | 佛山科学技术学院 | A kind of acid-base balance state analysis method and system |
| CN112071416A (en) * | 2020-09-01 | 2020-12-11 | 新疆维吾尔自治区人民医院 | Blood gas analysis and judgment simulation system and method |
| GB2585410A (en) * | 2019-02-20 | 2021-01-13 | Sancho Rodriguez Villar | Analysis |
| CN113113134A (en) * | 2021-04-07 | 2021-07-13 | 闵东 | Clinical etiology prejudgment device and system |
| CN113974578A (en) * | 2021-10-27 | 2022-01-28 | 川北医学院 | Device for estimating physiological heart measurement according to qi and blood analysis |
| CN114842978A (en) * | 2022-07-04 | 2022-08-02 | 佛山科学技术学院 | Intelligent blood gas analysis detection system and method based on medical big data |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2348391Y (en) * | 1998-10-26 | 1999-11-10 | 成都市第一人民医院 | Organism blood gas analyzer |
| CN204484121U (en) * | 2015-02-07 | 2015-07-22 | 孟素秋 | Multifunctional, air blood system analyzer |
-
2016
- 2016-07-13 CN CN201610557630.8A patent/CN106021968A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2348391Y (en) * | 1998-10-26 | 1999-11-10 | 成都市第一人民医院 | Organism blood gas analyzer |
| CN204484121U (en) * | 2015-02-07 | 2015-07-22 | 孟素秋 | Multifunctional, air blood system analyzer |
Non-Patent Citations (2)
| Title |
|---|
| 何权瀛 等: "《基层常见呼吸疾病诊断常规》", 30 November 2015 * |
| 马春蕾 等: "《医用机能实验学（第4版）》", 31 August 2015 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107610782A (en) * | 2017-08-28 | 2018-01-19 | 佛山科学技术学院 | A kind of acid-base balance state analysis method and system |
| GB2585410A (en) * | 2019-02-20 | 2021-01-13 | Sancho Rodriguez Villar | Analysis |
| GB2585410B (en) * | 2019-02-20 | 2023-05-31 | Advanced Medical Analytics Ltd | Analysis |
| CN112071416A (en) * | 2020-09-01 | 2020-12-11 | 新疆维吾尔自治区人民医院 | Blood gas analysis and judgment simulation system and method |
| CN113113134A (en) * | 2021-04-07 | 2021-07-13 | 闵东 | Clinical etiology prejudgment device and system |
| CN113974578A (en) * | 2021-10-27 | 2022-01-28 | 川北医学院 | Device for estimating physiological heart measurement according to qi and blood analysis |
| CN114842978A (en) * | 2022-07-04 | 2022-08-02 | 佛山科学技术学院 | Intelligent blood gas analysis detection system and method based on medical big data |
| CN114842978B (en) * | 2022-07-04 | 2022-09-27 | 佛山科学技术学院 | Intelligent blood gas analysis detection system and method based on medical big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106021968A (en) | Clinical intelligent blood gas analysis and diagnosis instrument | |
| Küpers et al. | A clinical prediction score to diagnose unilateral primary aldosteronism | |
| Rabinovich et al. | Validity of physical activity monitors during daily life in patients with COPD | |
| Pääkkönen et al. | Sensitivity of erythrocyte sedimentation rate and C-reactive protein in childhood bone and joint infections | |
| Mehta et al. | Refining predictive models in critically ill patients with acute renal failure | |
| Soto et al. | Cystatin C as a marker of acute kidney injury in the emergency department | |
| Strauß et al. | The prognostic significance of respiratory rate in patients with pneumonia: a retrospective analysis of data from 705 928 hospitalized patients in Germany from 2010–2012 | |
| Morriss Jr et al. | Effectiveness of a barcode medication administration system in reducing preventable adverse drug events in a neonatal intensive care unit: a prospective cohort study | |
| Gershon et al. | Factors associated with undiagnosed and overdiagnosed COPD | |
| Cooke et al. | Respiratory tract infections (RTIs) in primary care: narrative review of C reactive protein (CRP) point-of-care testing (POCT) and antibacterial use in patients who present with symptoms of RTI | |
| Morton et al. | Reviews: Is the calcium correct? Measuring serum calcium in dialysis patients | |
| CN108139384A (en) | Analysis of respiratory gas | |
| Beckett et al. | Lecture Notes: Clinical Biochemistry | |
| US20120165639A1 (en) | Storage of calibration data at a continuous glucose monitor | |
| Hadique et al. | Derivation and validation of a prognostic model to predict 6-month mortality in an intensive care unit population | |
| Mandzuka et al. | Mobile clinical decision support system for acid-base balance diagnosis and treatment recommendation | |
| Lin et al. | Prognostic value of acute-on-chronic liver failure (ACLF) score in critically ill patients with cirrhosis and ACLF | |
| Nekoee et al. | Are type-2 biomarkers of any help in asthma diagnosis? | |
| Fortenberry et al. | Development of an electronic trigger tool at a children’s hospital within an academic medical center | |
| Ertan et al. | Impact on the survival of neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, and monocyte-lymphocyte ratio on prognosis in children with Hodgkin lymphoma | |
| Kalani et al. | Prognostic value of intensive care scores concerning the prediction of 30-day mortality in COVID-19 | |
| Kim et al. | Decreased Cystatin C–Estimated Glomerular Filtration Rate Is Correlated with Prolonged Hospital Stay in Transient Tachypnea of Newborn Infants | |
| Kazaks et al. | Multiple measures of magnesium status are comparable in mild asthma and control subjects | |
| Zheng et al. | Identifying possible surrogate markers of COVID19 as a supplement to diagnostic testing in Upstate New York | |
| Tucker et al. | Spot sample urine specific gravity does not accurately represent small decreases in plasma volume in resting healthy males |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161012 |
|
| RJ01 | Rejection of invention patent application after publication |