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使用 HAMILTON‑C1/T1/MR1 呼吸机计算平台压

文章

作者: Simon Franz

日期: 14.07.2017

HAMILTON‑C1/T1/MR1 呼吸机用户提出的一个常见问题是如何用他们的设备测量/计算平台压。
使用 HAMILTON-C1/T1/MR1 呼吸机计算平台压

背景

即使“安全”平台压的想法已经受到质疑，使用它来定制急性呼吸窘迫综合征 (ARDS) 病人的肺保护性通气仍然是护理标准 Loring SH, Weiss JW. Plateau pressures in the ARDSnet protocol: cause of injury or indication of disease?. Am J Respir Crit Care Med.2007;176(1):99‑101. doi:10.1164/ajrccm.176.1.99b1​。 

平台压显示作为监测参数

由于 HAMILTON‑C1/T1/MR1 呼吸机中的无阀气动装置，不可能通过执行吸气屏气操作来获得平台压。尽管如此，平台压仍然可以作为监测参数，而且可能会根据您的呼吸机软件进行显示。
HAMILTON‑C1/T1/MR1 软件 < v2.2.0 HAMILTON‑C1/T1/MR1 软件 ≥ v2.2.0
吸气末压力始终显示为平台压。请考虑，如果存在吸气末流量，则显示的平台压高于实际平台压。 仅在吸气末流量接近零时，才显示平台压。显示的平台压仍然可以高于实际平台压。

在吸气末流量不接近零的情况下计算平台压

在吸气末流量不接近零或吸气末测得的压力不准确的情况下，计算平台压的一种可能的解决方法是：

  • 计算驱动压力 (∆P)：∆P = VTE/Cstat
  • 计算平台压：平台压 = ∆P + PEEP

此计算取决于准确的静态顺应性 (Cstat) 测量，这意味着没有发生显著的病人努力。吸气压应至少为 ~10cmH2O.

平台压 = (VTE ml  / Cstat ml/cmH2O) + PEEP cmH2O

示例
呼出潮气量：450 ml；静态顺应性：50 ml/cmH2O；PEEP：8 cmH2O

(450 ml / 50 ml/cmH2O) + 8 cmH2O = 17 cmH2O

平台压 = 17 cmH2O
∆P = 9 cmH2O

另一个优点是您可以获得 ∆P 作为计算的副产物。∆P 与 ADRS 病人的生存率密切相关，因此可能是更有趣的参数 Amato MB, Meade MO, Slutsky AS, et al.Driving pressure and survival in the acute respiratory distress syndrome.N Engl J Med.2015;372(8):747‑755. doi:10.1056/NEJMsa14106392​。

相关设备：HAMILTON‑C1/T1/MR1（所有软件版本）
 

了解 HAMILTON‑C1 的更多信息

脚注

参考文献

  1. 1. Loring SH, Weiss JW. Plateau pressures in the ARDSnet protocol: cause of injury or indication of disease?. Am J Respir Crit Care Med. 2007;176(1):99‑101. doi:10.1164/ajrccm.176.1.99b
  2. 2. Amato MB, Meade MO, Slutsky AS, et al. Driving pressure and survival in the acute respiratory distress syndrome. N Engl J Med. 2015;372(8):747‑755. doi:10.1056/NEJMsa1410639

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Plateau pressures in the ARDSnet protocol: cause of injury or indication of disease?

Loring SH, Weiss JW. Plateau pressures in the ARDSnet protocol: cause of injury or indication of disease?. Am J Respir Crit Care Med. 2007;176(1):99‑101. doi:10.1164/ajrccm.176.1.99b

Driving pressure and survival in the acute respiratory distress syndrome.

Amato MB, Meade MO, Slutsky AS, et al. Driving pressure and survival in the acute respiratory distress syndrome. N Engl J Med. 2015;372(8):747‑755. doi:10.1056/NEJMsa1410639



BACKGROUND

Mechanical‑ventilation strategies that use lower end‑inspiratory (plateau) airway pressures, lower tidal volumes (VT), and higher positive end‑expiratory pressures (PEEPs) can improve survival in patients with the acute respiratory distress syndrome (ARDS), but the relative importance of each of these components is uncertain. Because respiratory‑system compliance (CRS) is strongly related to the volume of aerated remaining functional lung during disease (termed functional lung size), we hypothesized that driving pressure (ΔP=VT/CRS), in which VT is intrinsically normalized to functional lung size (instead of predicted lung size in healthy persons), would be an index more strongly associated with survival than VT or PEEP in patients who are not actively breathing.

METHODS

Using a statistical tool known as multilevel mediation analysis to analyze individual data from 3562 patients with ARDS enrolled in nine previously reported randomized trials, we examined ΔP as an independent variable associated with survival. In the mediation analysis, we estimated the isolated effects of changes in ΔP resulting from randomized ventilator settings while minimizing confounding due to the baseline severity of lung disease.

RESULTS

Among ventilation variables, ΔP was most strongly associated with survival. A 1-SD increment in ΔP (approximately 7 cm of water) was associated with increased mortality (relative risk, 1.41; 95% confidence interval [CI], 1.31 to 1.51; P<0.001), even in patients receiving "protective" plateau pressures and VT (relative risk, 1.36; 95% CI, 1.17 to 1.58; P<0.001). Individual changes in VT or PEEP after randomization were not independently associated with survival; they were associated only if they were among the changes that led to reductions in ΔP (mediation effects of ΔP, P=0.004 and P=0.001, respectively).

CONCLUSIONS

We found that ΔP was the ventilation variable that best stratified risk. Decreases in ΔP owing to changes in ventilator settings were strongly associated with increased survival. (Funded by Fundação de Amparo e Pesquisa do Estado de São Paulo and others.).