clinmon {clinmon} | R Documentation |

`clinmon()`

uses a *continuous* recording and returns a dataframe with hemodynamic indices for every period, epoch or block depending on the chosen output. Calculates `COest`

, `CPPopt`

, `CVRi`

, `Dx`

, `Mx`

, `PI`

, `PRx`

, `PWA`

, `RI`

, and `Sx`

(see *Hemodynamic indices*).

```
clinmon(df, variables,
trigger = NULL, deleter = NULL,
blocksize = 3, epochsize = 20,
overlapping = FALSE, freq = 1000,
blockmin = 0.5, epochmin = 0.5,
output = "period", fast = FALSE)
```

`df` |
Raw |

`variables` |
Defining the type and order of the recorded variables as a list. Middle cerebral artery blood velocity ( |

`trigger` |
Trigger with two columns: first is start, and second is end of periods to be analyzed. Every row corresponds to a period. Default is |

`deleter` |
Deleter with two columns: first is start and second is end of period with artefacts, which need to be deleted. Every row is a period with artefacts. Default is |

`blocksize` |
Length of a block, in seconds. Default is |

`epochsize` |
Size of epochs in number of blocks. Default is |

`overlapping` |
The number of block which should overlap when calculating correlation based indices, and remain blank if overlapping calculations should not be utilized. Default is |

`freq` |
Frequency of recorded data, in Hz. Default is |

`blockmin` |
Minimum measurements required to create a block in ratio. Default is |

`epochmin` |
Minimum number of blocks required to create an epoch in ratio. Default is |

`output` |
Select what each row should represent in the output. Correlation based indices are not presented when selecting blocks for every row. Currently |

`fast` |
Select if you want the data to aggregated before analysis resulting in a faster, but perhaps more imprecise run, in Hz. Default is |

Using a *continuous* raw recording, `clinmon()`

calculates hemodynamic indices for every period, epoch or block depending on the chosen output.

View(data)

`time` | `abp` | `mcav` |

`7.00` | `78` | `45` |

`7.01` | `78` | `46` |

`...` | `...` | `...` |

`301.82` | `82` | `70` |

`301.83` | `81` | `69` |

To calculate the indices insert the data and select the relevant variables.

clinmon(df=data, variables=c("abp","mcav"))

See **Value** for output description.

Returns a dataframe with the results, with either every blocks, epochs or periods as rows, depending on the chosen output.

Column | Description |

`period` | The period number corresponding to the row-number in the trigger file. |

`epoch` | The epoch number, or if `period` is chosen as output it reflects the number of epochs in the period. |

`block` | The block number, or if `period` or `epoch` is chosen as output it reflects the number of blocks in the `period` or `epoch` . |

`time_min` | The minimum time value or the `period` , `epoch` or `block` . |

`time_max` | The maximum time value or the `period` , `epoch` or `block` . |

`missing_percent` | The percentage of missing data in the `period` , `epoch` or `block` . |

`*_mean` | The mean value of each variable for the `period` , `epoch` or `block` . |

`*_min` | The minimum value of each variable for the `period` , `epoch` or `block` . |

`*_max` | The maximum value of each variable for the `period` , `epoch` or `block` . |

`*` | The indices in each column. |

`COest`

| Estimated cardiac output*Required variables:* `abp`

, `hr`

; *Required output:* `-`

.

Estimated cardiac output (`COest`

) is calculated by utilizing the method described by Koenig et al. [1]:

`COest = PP / (SBP+DBP) * HR`

PP: Pulse pressure; SBP: systolic blood pressure; DBP: diastolic blood pressure; HR: heart rate.

`CPPopt`

| Optimal cerebral perfusion pressure*Required variables:* `abp`

, `icp`

; *Required output:* `period`

.

Optimal cerebral perfusion pressure (`CPPopt`

) is calculated utilizing the method described by Steiner et al. [2]. The CPPopt return `NA`

if CPPopt is the maximum or minimum CPP investigated. CPPopt is recommended to only be calculated after 'several hours' of recording:

`CPPopt = 5 mmHg_CPP_interval_with_lowest_mean_PRx ) `

CPP: cerebral perfusion pressure; PRx: Pressure reactivity index.

`CVRi`

| Cardiovascular resistance index*Required variables:* `abp`

, `mcav`

; *Required output:* `-`

.

Cardiovascular resistance index (`CVRi`

) is calculated utilizing the method described by Fan et al. [3]:

`CVRi = mean ABP / mean MCAv `

ABP: arterial blood pressure; MCAv: middle cerebral artery blood velocity.

`Dx`

| Diastolic flow index*Required variables:* `cpp`

/`abp`

, `mcav`

; *Required output:* `epoch`

, `period`

.

Diastolic flow index (`Dx`

) is calculated utilizing the method described by Reinhard et al. [4]:

`Dx = cor( mean CPP / min MCAv ) `

`Dxa = cor( mean ABP / min MCAv ) `

cor: correlation coefficient; CPP: cerebral perfusion pressure; ABP: arterial blood pressure; MCAv: middle cerebral artery blood velocity.

`Mx`

| Mean flow index*Required variables:* `cpp`

/`abp`

, `mcav`

; *Required output:* `epoch`

, `period`

.

Mean flow index (`Mx`

) is calculated utilizing the method described by Czosnyka et al. [5]:

`Mx = cor( mean CPP / mean MCAv ) `

`Mxa = cor( mean ABP / mean MCAv ) `

cor: correlation coefficient; CPP: cerebral perfusion pressure; ABP: arterial blood pressure; MCAv: middle cerebral artery blood velocity.

`PI`

| Gosling index of pulsatility*Required variables:* `mcav`

; *Required output:* `-`

.

Gosling index of pulsatility (`PI`

) is calculated utilizing the method described by Michel et al. [6]:

`PI = (systolic MCAv - diastolic MCAv) / mean MCAv `

MCAv: middle cerebral artery blood velocity.

`PRx`

| Pressure reactivity index*Required variables:* `abp`

, `icp`

; *Required output:* `epoch`

, `period`

.

Pressure reactivity index (`PRx`

) is calculated utilizing the method described by Czosnyka et al. [7]:

`PRx = cor( mean ABP / mean ICP ) `

cor: correlation coefficient; CPP: cerebral perfusion pressure; ICP: intracranial pressure.

`PWA`

| Pulse wave amplitude*Required variables:* `cpp`

/`icp`

/`abp`

/`mcav`

; *Required output:* `-`

.

Pulse wave amplitude (`PWA`

) is calculated utilizing the method described by Norager et al. [8]:

`PWA = systolic - diastolic `

`RI`

| Pourcelots resistive (resistance) index*Required variables:* `mcav`

; *Required output:* `-`

.

Pourcelots resistive (resistance) index (`RI`

) is calculated utilizing the method described by Forster et al. [9]:

`RI = (systolic MCAv - diastolic MCAv) / systolic MCAv `

MCAv: middle cerebral artery blood velocity.

`Sx`

| Systolic flow index*Required variables:* `cpp`

/`abp`

, `mcav`

; *Required output:* `epoch`

, `period`

.

Systolic flow index (`Sx`

) is calculated utilizing the method described by Czosnyka et al. [5]:

`Sx = cor( mean CPP / systolic MCAv ) `

`Sxa = cor( mean ABP / systolic MCAv ) `

cor: correlation coefficient; CPP: cerebral perfusion pressure; ABP: arterial blood pressure; MCAv: middle cerebral artery blood velocity.

Koenig et al. (2015) Biomed Sci Instrum. 2015;51:85-90. (PubMed)

Steiner et al. (2002) Crit Care Med. 2002 Apr;30(4):733-8. (PubMed)

Fan et al. (2018) Front Physiol. 2018 Jul 16;9:869. (PubMed)

Reinhard et al. (2003) Stroke. 2003 Sep;34(9):2138-44. (PubMed)

Czosnyka et al. (1996) Stroke. 1996 Oct;27(10):1829-34. (PubMed)

Michel et al. (1998) Ultrasound Med Biol. 1998 May;24(4):597-9. (PubMed)

Czosnyka et al. (1997) Neurosurgery. 1997 Jul;41(1):11-7; discussion 17-9. (PubMed)

Norager et al. (2020) Acta Neurochir (Wien). 2020 Dec;162(12):2983-2989. (PubMed)

Forster et al. (2017) J Paediatr Child Health. 2018 Jan;54(1):61-68. (PubMed)

```
data(testdata)
clinmon(df.data10, variables=c('abp','mcav','hr'), freq=10)
```

[Package *clinmon* version 0.6.0 Index]