Abstract
目的
探究神经重症患者压力性损伤的临床特征、影响因素及预测模型的构建与评价。
方法
采用回顾性的研究方法，采集温州医科大学附属第一医院2020年4月–2024年4月的250例神经重症患者，分别收集其临床特征。依据患者治疗后是否发生压力性损伤，将250例神经重症患者分为损伤组和未损伤组，采集其是否昏迷或嗜睡、入住神经重症原发病以及急性生理与慢性健康评分系统（Acute Physiology and Chronic Health Evaluation Ⅱ, APACHE Ⅱ）评分等基线资料，比较急性脑血管病、昏迷或嗜睡以及APACHE Ⅱ评分受试者工作特征（receiver operating characteristics, ROC）曲线下面积（area under the curve, AUC）。
结果
接受治疗的250例神经重症患者中，发生压力性损伤的患者共有58例。其中35例（60.34%）为黏膜压力性损伤，23例（39.66%）为器械相关压力性损伤。按照压力性损伤分期标准1期46例（79.31%）、2期8例（13.97%）、3期4例（6.90%），无4期病例；logistic多因素回归分析显示，入住神经重症原发病（OR=3.102，95%CI：1.013～9.499）、昏迷或嗜睡（OR=3.769，95%CI：1.237～11.478）、APACHE Ⅱ评分（OR=0.201，95%CI：0.124～0.328）是神经重症患者发生压力性损伤的影响因素；ROC结果显示，三者联合预测的AUC为0.974，95%CI：0.957～0.992，灵敏度和特异度分别为91.40%和93.70%。联合预测模型的预测质量为0.96，显著单独构建的预测模型（P<0.05），Hosmer-Lemeshow检验显示模型拟合度良好（χ2=4.779，P=0.062），说明该模型具有较高的精确度。
结论
急性脑血管病、昏迷或嗜睡以及APACHE Ⅱ评分均对神经重症患者发生压力性损伤具有不同程度的预测价值，其中急性脑血管病和昏迷或嗜睡预测值相同，但三者联合预测的准确性更高，具有广阔的应用前景和临床推广价值。
Keywords: 神经重症, 压力性损伤, 临床特征, 模型构建
Abstract
Objective
To investigate the clinical characteristics and influencing factors of pressure injury in patients with severe neurological diseases and to construct and evaluate a predictive model for it.
Methods
A retrospective research method was adopted to collect 250 patients with severe neuropathy admitted to the First Affiliated Hospital of Wenzhou Medical University from April 2020 to April 2024, and their clinical characteristics were collected. The patients were then divided into a pressure injury group (n = 58) and a non-pressure injury group (n = 192) based on whether they development pressure injury after treatment. Baseline data on patient coma or lethargy status, primary diagnosis requiring neurocritical care admission, and Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ scores were collected. The area under the curve (AUC) of the receiver operating characteristic (ROC) curves for acute cerebrovascular disease, coma or lethargy status, and APACHE Ⅱ scores of the subjects was compared.
Results
Among the 250 patients with severe neurological diseases, 58 had pressure injuries. Of these, 35 (60.34%) had mucosal pressure injuries, while 23 (39.66%) had device-related pressure injuries. According to the National Pressure Injury Advisory Panel Pressure Injury Staging System, 46 cases (79.31%) had stage 1 pressure injuries, 8 cases(13.97%) had stage 2 pressure injuries, 4 cases (6.90%) had stage 3 pressure injuries, and no patients had stage 4 pressure injuries. Logistic multivariate regression analysis showed that primary diagnosis requiring neurocritical care admission (odds ratio [OR] = 3.102; 95% CI, 1.013-9.499), coma or lethargy status (OR =3.769; 95% CI, 1.237-11.478), and APACHE Ⅱ score (OR =0.201; 95% CI, 0.124-0.328) were influencing factors for pressure injury in patients with severe neurological diseases. The ROC results showed that the AUC of the prediction model combining the 3 influencing factors was 0.974 (95% CI, 0.957-0.992), and that the sensitivity and specificity were 91.40% and 93.70%, respectively. The prediction accuracy of the combination prediction model was 0.96, which was significantly higher than those of the prediction models based on the 3 separate influencing factors (P < 0.05). The Hosmer-Lemeshow test showed that the model had a good fit (χ2 = 4.779, P = 0.062), indicating that the model had a relatively high accuracy.
Conclusion
Acute cerebrovascular disease, coma or lethargy, and APACHE Ⅱ score have different predictive values for pressure injury in patients with severe neurological diseases. While acute cerebrovascular disease and coma or lethargy have the same predictive value separately, the combination prediction incorporating the 3 influencing factors demonstrated superior accuracy and holds considerable potential for clinical application.
Keywords: Severe neurological diseases, Pressure injury, Clinical features, Model construction
神经重症患者由于疾病的严重性和治疗的复杂性，常常需要长时间卧床和接受各种侵入性治疗，这使得他们成为压力性损伤的高危人群[1-3]。压力性损伤，也称为压疮或褥疮，是指由于身体局部组织长时间受压，导致血液循环受阻，皮肤和皮下组织无法获得足够的营养，从而形成溃烂和组织坏死[4-5]。在神经重症患者中，这一问题尤为突出，不仅给患者带来极大的痛苦，还可能引发严重感染，增加治疗难度和医疗成本。神经重症患者压力性损伤的临床特征多样，通常发生在头或脸或与医源性设备接触的部位，如骶尾部、胸部、背部等[6-7]。其临床表现从初期的皮肤红斑到后期的深层溃疡和组织坏死，严重程度不一[8]。这些损伤不仅影响患者的康复进程，还可能危及生命。另外，神经重症患者压力性损伤的发生受多种因素的影响，各因素间相互作用，共同增加了患者发生压力性损伤的风险。鉴于压力性损伤对神经重症患者的严重影响，构建有效的预测模型对于及早识别高危患者、实施预防性措施至关重要。目前，国内外研究者已经提出了多种预测模型，如临床预测模型、生理参数模型和机器学习模型等[9-10]。这些模型通过整合患者的临床数据、生理指标和风险因素，运用统计学方法和机器学习算法，对压力性损伤的发生风险进行预测。然而，不同模型的预测精度和适用性存在差异，需要进一步的研究和优化。因此，本研究旨在深入探讨神经重症患者压力性损伤的临床特征、影响因素，并构建基于多因素分析的预测模型，期望能够识别出压力性损伤的主要危险因素，并构建出具有较高预测精度的模型。同时，还将对模型的预测效果进行验证和评价，以期为临床实践中压力性损伤的预防和治疗提供科学依据。
1. 资料与方法
1.1. 一般资料
采集温州医科大学附属第一医院2020年4月–2024年4月的250例神经重症患者。此次研究已通过温州医科大学附属第一医院临床研究伦理委员会审批，批件号：(2023)第(R080)号。
1.2. 纳排标准
纳入标准：①符合临床压力性损伤的相关诊断标准[11]；②临床病历资料清晰完整；③年龄大于18周岁；④住院时间≥48 h。
排除标准：①合并其他急慢性皮肤病；②合并恶性肿瘤；③合并心力衰竭等心脏类疾病；④中途自愿退出。
剔除标准：在24 h内死亡、出院或者转科的患者。
1.3. 方法
本次研究采用回顾性的研究方法，对250例患者的临床资料进行收集，主要为研究人员通过检索既往相关文献，同时结合临床自行制作基线资料调查表，该量表包括患者年龄、性别、是否昏迷或嗜睡、入住神经重症原发病（急性脑血管病和非急性脑血管病）、医疗设备数量、压力性损伤的临床特征（部位、数量、性质、分期）以及急性生理与慢性健康评分系统（APACHE Ⅱ）评分[12]等7项内容。
1.4. 统计学方法
应用SPSS26.0统计软件对所得数据进行分析，计数资料以例数（%）表示，进行χ2检验；计量资料采用
表示，采用t检验；对组间具有差异的多个变量进行共线性检验，对于容差>0.1及方差膨胀因子（variance inflation factor, VIF）<5的自变量认为不具有共线性，纳入最终的logistic多因素回归分析。通过受试者工作特征（receiver operating characteristics, ROC）曲线下面积（area under the curve, AUC）评价神经重症患者发生压力性损伤的预测价值。P<0.05为差异有统计学意义。
2. 结果
2.1. 神经重症患者发生压力性损伤的情况
接受治疗的250例神经重症患者中，发生压力性损伤的患者共有58例。依据患者治疗后是否发生压力性损伤，将250例神经重症患者分为损伤组（n=58）和未损伤组（n=192）。
2.2. 神经重症患者发生压力性损伤的临床特征
58例发生压力性损伤的神经重症患者中有35例（60.34%）为黏膜压力性损伤，23例（39.66%）为器械相关压力性损伤。分期：1期46例（79.31%）、2期8例（13.97%）、3期4例（6.90%），无4期病例。见表1。
表 1. Clinical characteristics of pressure injury in patients with severe neurological diseases(case [%]).
神经重症患者发生压力性损伤的临床特征〔例数（%）〕
| Location | Mucosal pressure injury |
Device-related pressure injury |
Total |
| Head and face | 7 (12.07) | 0 (0.00) | 7 (12.07) |
| Occipital bone | 2 (3.45) | 0 (0.00) | 2 (3.45) |
| Forehead | 0 (0.00) | 2 (3.45) | 2 (3.45) |
| Cheek | 0 (0.00) | 0 (0.00) | 0 (0.00) |
| Nose | 0 (0.00) | 2 (3.45) | 2 (3.45) |
| Ear | 2 (3.45) | 0 (0.00) | 2 (3.45) |
| Temporal bone | 0 (0.00) | 3 (5.17) | 3 (5.17) |
| Upper limb | 0 (0.00) | 2 (3.45) | 2 (3.45) |
| Upper arm | 0 (0.00) | 2 (3.45) | 2 (3.45) |
| Elbow | 0 (0.00) | 3 (5.17) | 3 (5.17) |
| Lower limb | 10 (17.24) | 2 (3.45) | 12 (20.69) |
| Knee | 0 (0.00) | 2 (3.45) | 2 (3.45) |
| Heel | 15 (25.86) | 5 (8.62) | 20 (34.48) |
| Ankle | 3 (5.17) | 0 (0.00) | 3 (5.17) |
| Trunk | 2 (3.45) | 2 (3.45) | 4 (6.90) |
| Chest | 0 (0.00) | 2 (3.45) | 2 (3.45) |
| Back | 5 (8.62) | 5 (8.62) | 10 (17.24) |
| Sacrococcygeal region | 17 (29.31) | 15 (25.86) | 32 (55.17) |
| Total | 35 (60.34) | 23 (39.66) | 58 (100.00) |
2.3. 神经重症患者发生压力性损伤的单因素分析
根据本研究中损伤组和未损伤组的6个单因素（年龄、居住地、入住神经重症原发病、昏迷或嗜睡、医疗设备数量、APACHE Ⅱ评分）进行分析，研究结果表明，两组在年龄、性别、医疗设备数量这3个因素的比较，无统计学意义（P>0.05）；而入住神经重症原发病、昏迷或嗜睡以及APACHE Ⅱ评分这3个单因素的比较，具有统计学意义（均P<0.05）。见表2。
表 2. Univariate analysis of pressure injury in patients with severe neurological diseases.
神经重症患者发生压力性损伤的单因素分析
| Index | Pressure injury group (n = 58) | Non-pressure injury group (n = 192) | t/χ 2 | P |
Age /yr., 
|
52.88 ± 10.45 | 53.71 ± 11.29 | 0.499 | 0.618 |
| Sex/case (%) | 2.619 | 0.106 | ||
| Man | 33 (56.90) | 86 (44.79) | ||
| Woman | 25 (43.10) | 106 (55.21) | ||
| Primary diagnosis requiring neurocritical care admission/case (%) | ||||
| Acute cerebrovascular disease | 38 (65.52) | 42 (21.88) | 38.989 | 0.000 |
| Non-cerebrovascular disease | 20 (34.48) | 150 (78.13) | ||
| Coma or lethargy/case (%) | 57.765 | 0.000 | ||
| Yes | 40 (68.97) | 33 (17.19) | ||
| No | 18 (31.03) | 159 (82.81) | ||
Number of medical equipment ( ) |
7.41 ± 0.58 | 7.31 ± 0.68 | 1.014 | 0.312 |
APACHE Ⅱ score ( ) |
17.89 ± 1.31 | 21.34 ± 1.49 | 15.873 | 0.000 |
2.4. 多重共线性检验
为排除单因素分析结果中3个差异指标间的多重共线性，进行共线性检验。结果显示，入住神经重症原发病、昏迷或嗜睡以及APACHE Ⅱ评分的容差均>0.1、VIF均<5。因此，变量间无共线性，可纳入下一步研究，见表3。
表 3. Multicollinearity test.
多重共线性检验
| Factor | Tolerance | VIF |
| APACHE: Acute Physiology and Chronic Health Evaluation; VIF: variance inflation factor. | ||
| Primary diagnosis requiring neurocritical care admission | 0.681 | 1.469 |
| Coma or lethargy | 0.631 | 1.584 |
| APACHE Ⅱ score | 0.798 | 1.254 |
2.5. 神经重症患者发生压力性损伤的多因素分析
以神经重症患者是否发生压力性损伤作为因变量Y（未损伤组=0，损伤组=1），将表3中无共线性的因素（入住神经重症原发病、昏迷或嗜睡、APACHE Ⅱ评分）采用自变量重要性（Forward法）纳入logistic多因素回归分析，具体赋值标准见表4。
表 4. Value assignment methods.
赋值方法
| Factor | Value asignment |
| Primary diagnosis requiring neurocritical care admission |
Continuous variable |
| Coma or lethargy | No = 0, yes = 1 |
| APACHE Ⅱ score | Continuous variable |
logistic多因素回归分析显示，入住神经重症原发病（OR=3.102，95%CI: 1.013~9.499）、昏迷或嗜睡（OR=3.769，95%CI: 1.237~11.478）、APACHE Ⅱ评分（OR=0.201，95%CI: 0.124~0.328）是神经重症患者发生压力性损伤的影响因素，P均<0.05，见表5。
表 5. Multivariate analysis of pressure injury in patients with severe neurological diseases.
神经重症患者发生压力性损伤的多因素分析
| Variable | B | Standard error | Wald | P | Odds ratio | 95% CI |
| Primary diagnosis requiring neurocritical care admission | 1.132 | 0.571 | 3.930 | 0.047 | 3.102 | 1.013-9.499 |
| Coma or lethargy | 1.327 | 0.568 | 5.452 | 0.020 | 3.769 | 1.237-11.478 |
| APACHE Ⅱ score | －1.602 | 0.249 | 41.480 | 0.000 | 0.201 | 0.124-0.328 |
| Constant | 29.221 | 4.728 | 38.197 | 0.000 | 4.905 |
2.6. 神经重症患者发生压力性损伤预测模型的预测效果
ROC结果显示，入住神经重症原发病、昏迷或嗜睡、APACHE Ⅱ评分对神经重症患者发生压力性损伤预测的AUC分别为0.716、0.759、0.960，对应的灵敏度分别为65.50%、69.00%、89.70%，特异度分别为77.60%、82.80%、93.20%。三者联合预测的AUC为0.974，灵敏度和特异度分别为91.40%和93.70%。见表6和图1所示。联合预测模型的预测质量为0.96，显著优于急性脑血管病（0.64）、昏迷或嗜睡（0.68）以及APACHE Ⅱ评分（0.94）单独构建的预测模型（P<0.05），Hosmer-Lemeshow检验显示模型拟合度良好χ2=4.779，P=0.062，说明该模型具有较高的精确度。
表 6. Prediction performance analysis of pressure injury prediction model for severe neurological patients.
神经重症患者发生压力性损伤预测模型的预测效果分析
| Variable | AUC | Sensitivity/% | Specificity/% | 95% CI | Youden's index | |
| Lower limit | Upper limit | |||||
| Primary diagnosis requiring neurocritical care admission | 0.716 | 65.50 | 77.60 | 0.636 | 0.795 | 0.431 |
| Coma or lethargy | 0.759 | 69.00 | 82.80 | 0.683 | 0.835 | 0.518 |
| APACHE Ⅱ score | 0.960 | 89.70 | 93.20 | 0.936 | 0.984 | 0.829 |
| Combination of the 3 | 0.974 | 91.40 | 93.70 | 0.957 | 0.992 | 0.851 |
图 1.
ROC curves of the predictive value of primary diagnosis requiring neurocritical care admission, coma or drowsiness, and APACHE Ⅱ score for pressure injury in patients with neurocritical illness
入住神经重症原发病、昏迷或嗜睡、APACHE Ⅱ评分对神经重症患者发生压力性损伤的预测价值ROC曲线
3. 讨论
神经重症患者多是由于脑外伤、脑肿瘤、脑出血、脑梗死、感染、化学药物中毒等引起的大脑神经组织损伤，可导致患者意识障碍、活动受限，感知异常、大小便失禁等症状[13-14]。由于病情危重，血流动力学不稳定，血管活性药物及大量侵入性器械的使用，患者住院卧床时间增加，压力接触随之增加，大小便、汗液等的潮湿刺激、剪切力、摩擦力、营养状况、皮温、自身慢性疾病等均可导致患者组织耐受性降低，极容易发生压力性损伤[15-16]。压力性损伤主要是指患者入院24 h后新发生的压力性损伤，它包括医疗器械相关性压力性损伤和黏膜压力性损伤两大类[17]。当前，压力性损伤已成为临床备受关注的常见并发症。压力性损伤的危害也已被国内外众多研究证实，且美国医院评审联合委员会已将3期、4期压力性损伤认定为患者安全警讯事件[18-19]。目前我科近3年压力性损伤发生率为0.180%～0.237%，高于医院院内压力性损伤发生的质量目标值≤0.11%，而且科室之间、科室内部之间的交流欠缺，对患者皮肤关注度掌握不全面，缺乏信息共享。因此，早期诊断、预后评估及迅速有效的治疗干预对于减少患者损伤发生率具有至关重要的作用。本文研究结果报道如下：
本次研究结果显示，在接受治疗的250例神经重症患者中，发生压力性损伤的患者共有58例，占比23.20%，与何正超等[20]研究结果中的占比相近，但本次研究患者占比略高，可能与不同的患者群体等因素具有一定的联系。但是本次研究中的疾病占比也提示了，神经重症患者发生压力性损伤较为严重，临床需加强对损伤的重视程度，可在临床实践中，持续优化治疗措施和患者管理策略降低压力性损伤的发生风险。神经重症患者发生压力性损伤的主要原因包括力学因素、生理因素、疾病因素、治疗因素和护理因素。为预防压力性损伤的发生，应采取综合措施，包括减轻局部压力、保持皮肤清洁干燥、加强营养支持、合理使用医疗器械、及时翻身等。相关研究表明[21]，成年患者发生压力性损伤的重要原因是医疗设备。本次研究发现，在58例发生压力性损伤的神经重症患者中有35例（60.34%）为黏膜压力性损伤，23例（39.66%）为器械相关压力性损伤，1期46例（79.31%）、2期8例（13.97%）、3期4例（6.90%），无4期病例。原因是，成人的体质量相较于儿童更重，翻身等更加频繁，使得皮肤受到的压迫和摩擦程度更高，血液循环更差，因此神经重症患者发生压力性损伤后的损伤更重，且患者受到压力性损伤的多以骶尾部、脚后跟和背部为主，与既往报道研究相一致[19]。之后，通过单因素和logistic多因素法进行进一步分析得到，急性脑血管病、昏迷或嗜睡以及APACHE Ⅱ评分是神经重症患者发生压力性损伤的影响因素，更加证实了本次研究结果的可靠性和普适性以及研究方法的有效性。Howell-PIRO评分模型具有简单、评分方便等优势，已被神经科的相关研究所采纳[22]。本研究分析了急性脑血管病、昏迷或嗜睡以及APACHE Ⅱ评分对神经重症患者发生压力性损伤的预测价值，ROC结果显示，急性脑血管病、昏迷或嗜睡、APACHE Ⅱ评分对神经重症患者发生压力性损伤预测的AUC分别为0.716、0.759、0.960，对应的灵敏度分别为65.50%、69.00%、89.70%，特异度分别为77.60%、82.80%、93.20%。三者联合预测的AUC为0.974，灵敏度和特异度分别为91.40%和93.70%。联合预测模型的预测质量为0.96，显著优于急性脑血管病、昏迷或嗜睡以及APACHE Ⅱ评分单独构建的预测模型（P<0.05），Hosmer-Lemeshow检验显示模型拟合度良好χ2=4.779，P=0.062，说明该模型具有较高的精确度。提示了在神经重症患者发生压力性损伤的治疗过程中，综合考虑多种指标的变化可以提供更为准确和可靠的预测依据。不仅有助于医护人员更早地发现并及时采取治疗措施，还可以避免不必要的误诊和漏诊，提高患者的治疗效果和生活质量。而本次研究中的APACHE Ⅱ评分对神经重症患者发生压力性损伤的预测价值不如急性脑血管病和昏迷或嗜睡高，可能与该评分模型对器官功能评估缺乏具有一定的联系。
综上所述，急性脑血管病、昏迷或嗜睡以及APACHE Ⅱ评分均对神经重症患者发生压力性损伤具有不同程度的预测价值，其中急性脑血管病和昏迷或嗜睡预测值相同，但三者联合预测的准确性更高，具有广阔的应用前景和临床推广价值。
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作者贡献声明 姚明亚负责论文构思、正式分析、初稿写作和审读与编辑写作，黄可静负责正式分析和审读与编辑写作，陈晓青负责论文构思、经费获取和研究方法，缪爱梅负责监督指导和审读与编辑写作。所有作者已经同意将文章提交给本刊，且对将要发表的版本进行最终定稿，并同意对工作的所有方面负责。
Author Contribution YAO Mingya is responsible for conceptualization, formal analysis, writing--original draft, and writing--review and editing. HUANG Kejing is responsible for formal analysis and writing--review and editing. CHEN Xiaoqing is responsible for conceptualization, funding acquisition, and methodology. MIAO Aimei is responsible for supervision and writing--review and editing. All authors have agreed to submit the article to the journal and to finalize the version to be published, and agree to take responsibility for all aspects of the work.
利益冲突 所有作者均声明不存在利益冲突
Declaration of Conflicting Interests All authors declare no competing interests.
Funding Statement
温州市基础性科研项目（No. Y20210617）和浙江省中医药科技计划项目（No. 2024ZL106）资助
Contributor Information
明亚 姚 (Mingya YAO), Email: wzymy1112@163.com.
爱梅 缪 (Aimei MIAO), Email: 23692454@qq.com.
References
- 1.曹飘, 熊冰婕, 张霞, 等 神经重症患者留置鼻胃管或鼻肠管进行肠内营养的效果比较. 遵义医科大学学报. 2024;47(7):714–718. doi: 10.14169/j.cnki.zunyixuebao.2024.0094. [DOI] [Google Scholar]; CAO P, XIONG B J, ZHANG X, et al Analysis of the effect of indwelling nasogastric or nasoenteral tubes for enteral nutrition in patients with neurological intensive care. J Zunyi Med Univ. 2024;47(7):714–718. doi: 10.14169/j.cnki.zunyixuebao.2024.0094. [DOI] [Google Scholar]
- 2.高健, 杨芳杰, 薛瑞忠, 等 膈肌电刺激治疗对神经重症获得性衰弱患者肺功能及预后影响. 中国煤炭工业医学杂志. 2023;26(3):286–289. doi: 10.11723/mtgyyx.1007-9564.202303014. [DOI] [Google Scholar]; GAO J, YANG F J, XUE R Z, et al Effect of diaphragm electrical stimulation on pulmonary function and prognosis of patients with severe acquired neurasthenia. Chin J Coal Ind Med. 2023;26(3):286–289. doi: 10.11723/mtgyyx.1007-9564.202303014. [DOI] [Google Scholar]
- 3.中华医学会外科学分会血管外科学组 深静脉血栓形成的诊断和治疗指南(第三版) 中国血管外科杂志(电子版) 2017;9(4):250–257. doi: 10.3969/j.issn.1674-7429.2017.04.003. [DOI] [Google Scholar]; Vascular Surgery Group, Branch of Surgery, Chinese Medical Association Guidelines for the diagnosis and treatment of deep vein thrombosis (third edition) Chin J Vasc Surg (Electron Ed) 2017;9(4):250–257. doi: 10.3969/j.issn.1674-7429.2017.04.003. [DOI] [Google Scholar]
- 4.HAJHOSSEINI B, LONGAKER M T, GURTNER G C Pressure Injury. Ann Surg. 2020;271(4):671–679. doi: 10.1097/SLA.0000000000003567. [DOI] [PubMed] [Google Scholar]
- 5.ALSHAHRANI B, SIM J, MIDDLETON R Nursing interventions for pressure injury prevention among critically ill patients: a systematic review. J Clin Nurs. 2021;30(15/16):2151–2168. doi: 10.1111/jocn.15709.Epub2021Feb27. [DOI] [PubMed] [Google Scholar]
- 6.ALDERDEN J G, SHIBILY F, COWAN L Best practice in pressure injury prevention among critical care patients. Crit Care Nurs Clin North Am. 2020;32(4):489–500. doi: 10.1016/j.cnc.2020.08.001.Epub2020Oct7. [DOI] [PubMed] [Google Scholar]
- 7.MUNOZ N, POSTHAUER M E Nutrition strategies for pressure injury management: implementing the 2019 International Clinical Practice Guideline. Nutr Clin Pract. 2022;37(3):567–582. doi: 10.1002/ncp.10762. [DOI] [PubMed] [Google Scholar]
- 8.KANDI L A, RANGEL I C, MOVTCHAN N V, et al Comprehensive management of pressure injury: a review. Phys Med Rehabil Clin N Am. 2022;33(4):773–787. doi: 10.1016/j.pmr.2022.06.002. [DOI] [PubMed] [Google Scholar]
- 9.LOVEGROVE J, VEN S, MILES S J, et al Comparison of pressure injury risk assessment outcomes using a structured assessment tool versus clinical judgement: a systematic review. J Clin Nurs. 2023;32(9/10):1674–1690. doi: 10.1111/jocn.16154.Epub2021Dec1. [DOI] [PubMed] [Google Scholar]
- 10.陈慧慧, 陆真 个体化预测心脏瓣膜置换术后压力性损伤发生风险的列线图模型构建. 实用心脑肺血管病杂志. 2021;29(12):40–46. doi: 10.12114/j.issn.1008-5971.2021.00.274. [DOI] [Google Scholar]; CHEN H H, LU Z Establishment of nomogram model for individualized prediction of pressure injury risk after cardiac valve replacement. Pract J Card Cereb Pneum Vasc Dis. 2021;29(12):40–46. doi: 10.12114/j.issn.1008-5971.2021.00.274. [DOI] [Google Scholar]
- 11.邓欣, 吕娟, 陈佳丽, 等 2016年最新压疮指南解读. 华西医学. 2016;31(9):1496–1498. doi: 10.7507/1002-0179.201600408. [DOI] [Google Scholar]; DENG X, LYU J, CHEN J L, et al Interpretation of the latest pressure ulcer guidelines in 2016. West China Med J. 2016;31(9):1496–1498. doi: 10.7507/1002-0179.201600408. [DOI] [Google Scholar]
- 12.CURLEY M A, RAZMUS I S, ROBERTS K E, et al Predicting pressure ulcer risk in pediatric patients: the Braden Q Scale. Nurs Res. 2003;52(1):22–33. doi: 10.1097/00006199-200301000-00004. [DOI] [PubMed] [Google Scholar]
- 13.COOK A M, MORGAN JONES G, HAWRYLUK G W J, et al Guidelines for the acute treatment of cerebral edema in neurocritical care patients. Neurocrit Care. 2020;32(3):647–666. doi: 10.1007/s12028-020-00959-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.叶凯丽, 高笑侠, 杨建静, 等 聚力关键风险管控的综合管理在神经重症监护室失禁相关性皮炎患者中的应用效果. 中华全科医学. 2024;22(1):168–171. doi: 10.16766/j.cnki.issn.1674-4152.003356. [DOI] [Google Scholar]; YE K L, GAO X X, YANG J J, et al The application of comprehensive management of key risk control in Neurological Intensive Care Unit patients with incontinence-associated dermatitis. Chin J Gen Pract. 2024;22(1):168–171. doi: 10.16766/j.cnki.issn.1674-4152.003356. [DOI] [Google Scholar]
- 15.TREGGIARI M M, RABINSTEIN A A, BUSL K M, et al Guidelines for the neurocritical care management of aneurysmal subarachnoid hemorrhage. Neurocrit Care. 2023;39(1):1–28. doi: 10.1007/s12028-023-01713-5. [DOI] [PubMed] [Google Scholar]
- 16.张燕, 胡瑶瑶, 吴高伟, 等 压力再分布气垫预防主动脉夹层手术患者术中获得性压力性损伤的效果. 温州医科大学学报. 2022;52(7):587–591. doi: 10.3969/j.issn.2095-9400.2022.07.013. [DOI] [Google Scholar]; ZHANG Y, HU Y Y, WU G W, et al Preventive effect of pressure-redistribution air pad for intraoperative acquired pressure injury in patients with aortic dissection surgery. J Wenzhou Med Univ. 2022;52(7):587–591. doi: 10.3969/j.issn.2095-9400.2022.07.013. [DOI] [Google Scholar]
- 17.陈锐, 王志伟, 赵瑞玲, 等 ICU体外循环术后患者口腔黏膜压力性损伤列线图预测模型的构建. 遵义医科大学学报. 2024;47(3):262–269. doi: 10.14169/j.cnki.zunyixuebao.2024.0032. [DOI] [Google Scholar]; CHEN R, WANG Z W, ZHAO R L, et al Construction of nomogram prediction model for oral mucosal pressure injury in patients after extracorporeal circulation in ICU. J Zunyi Med Univ. 2024;47(3):262–269. doi: 10.14169/j.cnki.zunyixuebao.2024.0032. [DOI] [Google Scholar]
- 18.ASIRI S. Turning and repositioning frequency to prevent hospital-acquired pressure injuries among adult patients: systematic review. Inquiry, 2023, 60: 469580231215209. doi: 10.1177/00469580231215209.
- 19.COX J Risk factors for pressure injury development among critical care patients. Crit Care Nurs Clin North Am. 2020;32(4):473–488. doi: 10.1016/j.cnc.2020.07.001. [DOI] [PubMed] [Google Scholar]
- 20.何正超, 陈嘉玲, 徐春蕾, 等 PICU患儿压力性损伤的临床特征、影响因素及预测模型的构建与评价. 现代生物医学进展. 2023;23(13):2444–2449. doi: 10.13241/j.cnki.pmb.2023.13.009. [DOI] [Google Scholar]; HE Z C, CHEN J L, XU C L, et al Construction and evaluation of clinical characteristics, influencing factors and predictive models of pressure injury in children with PICU. Prog Mod Biomed. 2023;23(13):2444–2449. doi: 10.13241/j.cnki.pmb.2023.13.009. [DOI] [Google Scholar]
- 21.HU J Incidence and prevalence of medical device-related pressure ulcers in children and adults. Evid Based Nurs. 2020;23(2):62. doi: 10.1136/ebnurs-2019-103098. [DOI] [PubMed] [Google Scholar]
- 22.王庆玺, 郭闻师 早期微生态肠内营养对老年神经重症机械通气患者疗效及预后的影响. 中国老年学杂志. 2020;40(14):2943–2946. doi: 10.3969/j.issn.1005-9202.2020.14.011. [DOI] [Google Scholar]; WANG Q X, GUO W S The influence of early microecological enteral nutrition on the therapeutic effect and prognosis of elderly patients with neurosevere mechanical ventilation. Chin J Gerontol. 2020;40(14):2943–2946. doi: 10.3969/j.issn.1005-9202.2020.14.011. [DOI] [Google Scholar]