四种评分系统对重症脓毒症病人动态评分的比较

目的观察APACHEⅡ、APACHEⅢ、SAPSⅡ和MODS评分对重症脓毒症病人动态评分评估预后的适用性和可行性。方法回顾性分析56例符合重症脓毒症标准者病人，分成两组：生存组（A组）和死亡组（B组），分别在第1天、第3天和第7天记录病人一般情况、APACHEⅡ、APACHEⅢ、SAPSH和MODS的各项评分项目并计算得出结果。结果按P〈0．01水平，生存组和死亡组使用四种评分系统7d内进行动态评分，MODS评分得分仅在第1天差异有显著性意义，而APACHEⅡ评分、APACHEⅢ评分和SAPSⅡ评分得分差异均有显著性意义。7d内四种评分系统比较，APACHEⅢ评分P值始终最小，MODS评分最大。结论评分系统并不是越新就越好，不同疾病评分系统的选择应该有所不同。SICU中重症脓毒症病人7d内运用四种评分系统动态评分来评估病情和预后，APACHEⅢ评分系统最优，APACHEⅡ评分系统和SAPSⅡ评分系统次之，MODS评分系统最差。     

危重病评分系统对急诊内科危重病人预后预测的对比研究

目的 研究危重病评分系统对急诊内科危重病人预后预测的对比结果.方法 选取2005年10月～2006年8月的急诊内科危重病人103例,应用APACHEI Ⅱ、APACHE Ⅲ、SAPS Ⅱ、MPM0、MPM 24评分系统计算入急诊抢救室当时及24 h最差值时分值及预测病死率,分析比较入急诊抢救室当时及24 h最差值时对预测预后的差异有无统计学意义.结果 各种评分系统在入院当时及24 h最差值时取值对预后预测均无明显差异(P＞0.05).各种评分系统的分值和预计死亡率在存活组和死亡组之间差异显著,且入院时分数越高,病情越重,死亡率越高.结论 各种评分系统均可用于预测急诊内科危重病人的预后.选取入院当时的参数进行评分,对预测预后无明显影响,但仍以入院时APACHE Ⅱ评分系统为首选.     

APACHEⅡ与SAPSⅡ评分系统对急诊内科危重患者病情评估价值的比较

目的评价急性生理与慢性健康状况评分Ⅱ(APACHEⅡ)评分系统和简化急性生理学评分Ⅱ(SAPSⅡ)评分系统在急诊内科危重患者病情评估中的适用性和可行性;比较二者评价效力的优劣.方法对207例急诊内科危重患者分别进行APACHEⅡ、SAPSⅡ评分和计算预计死亡危险度,以校准度及分辨度评价其预测效力.结果存活组(178例)与死亡组(29例)之间的APACHEⅡ和SAPSⅡ分值差异有统计学意义(P<0.01),死亡组患者分值[(22.66±7.30)分,(52.48±11.59)分]明显高于存活组患者[(11.26±6.32)分,(33.12±11.67)分].随着分值增加,病死率也增加.APACHEⅡ的预计死亡危险度(18.81%)与实际病死率(14.01%)之间差异无统计学意义(P>0.05),即APACHEⅡ能准确预测病死率.而SAPSⅡ则不能,SAPSⅡ的预计死亡危险度(23.51%)高于实际病死率(P<0.05).APACHEⅡ和SAPSⅡ都有较大的ROC曲线下面积(>0.85),其分辨度好,能较好区分可能死亡的患者和可能存活的患者.结论APACHEⅡ和SAPSⅡ评分系统均有较好的分辨度;APACHEⅡ的校准度优于SAPSⅡ.临床上对急诊内科危重患者病情的评价及预测预后宜以APACHEⅡ为首选.     

血清胆碱酯酶浓度联合APACHEⅢ评分对急性重症胆管炎患者病情及预后的评估价值

目的 探讨急性重症胆管炎(ACST)患者入院24 h 内急性生理及慢性健康状况评分Ⅲ(APACHEⅢ)和胆碱酯酶(ChE)浓度在预测病情及预后中的价值.方法 对83例入院24 h内的ACST患者进行APACHEⅢ评分,同时测定ChE浓度.根据患者预后分为存活组和死亡组,分析ChE浓度和APACHEⅢ评分与病情及预后的关系.结果存活组APACHEⅢ评分明显低于死亡组(P<0.01),而ChE浓度明显高于死亡组(P<0.01).随着APACHEⅢ评分升高,ChE浓度降低,且死亡率上升.二项指标与预后的Logistic回归分析均有统计学意义(P<0.01),APACHEⅢ评分(OR 95%CI 1.0507～1.1256),ChE浓度(OR 95%CI 0.9989～0.9996).APACHEⅢ评分和ChE浓度与预后的ROC曲线下面积(AUC)分别是0.926和0.875,但二者比较差异无统计学意义(P>0.05),二者联合预测时AUC为0.960,预测的准确性大于其中任何一项单独预测(P<0.05).结论 APACHEⅢ评分和ChE浓度与ACST患者病情及预后有显著的相关性,二者联合预测可明显提高对ACST预后判断的准确性,为临床救治提供一定的指导.     

探讨APACHEⅡ评分系统对EICU患者病情评估的效果

目的探讨急性生理学与慢性健康状况评分Ⅱ（APACHEII）对评估急诊重症监护病房（EICU）中危重患者的病情及判断其预后的应用价值。方法回顾性分析2012年6月至2013年3月期间收治的114例危重患者临床资料。根据患者预后,将其分为死亡组（57例）和存活组（57例）,分别计算患者入科第1天、第3天及第5天的APACHEⅡ评分并行比较,并通过受试者工作特征曲线（ROC）下面积分析APACHEⅡ评分中的三个时间段对预后的评估价值及效果。结果死亡组患者入科第1天、第3天及第5天的的APACHEⅡ评分均高于存活组患者,分别为[（24．58±8．87）VS（16．42±6．70）;（25．76±8．59）VS（13．44±5．38）;（24．664±7．64）VS（12．114±4．22）],两者比较差异有统计学意义（P〈0．05）,APACHEⅡ评分和患者预后有关。根据三组数据ROC曲线分析,对预后评估能力的大小依次为第5天、第3天、、第1天的APACHEⅡ评分。结论APACHEⅡ评分系统可很好的评估EICU中危重患者的病情及预后,其中第5天的APACHEⅡ评分能力最强。可为合理制定诊治计划和利用EICU资源提供参考。     

两种评分系统对慢性阻塞性肺疾病急性加重期患者病情严重程度及预后评估的研究

目的探讨慢性阻塞性肺疾病急性加重期(acute exacerbation of chronic obstructive pulmonary disease,AECOPD)患者急性生理学与慢性健康状况评分Ⅱ(acute physiology and chronic health evaluationⅡ,APACHEⅡ)及慢性阻塞性肺疾病和支气管哮喘生理评分(COPD and asthma physiology score,CAPS)与病情严重程度及预后的关系及评估价值。方法回顾性分析2013年1月至2018年11月于北京积水潭医院呼吸与危重症医学科住院治疗的AECOPD患者239例。根据住院期间有无机械通气分为无机械通气组和机械通气组;根据预后分为存活组和死亡组。住院后计算APACHEⅡ评分及CAPS评分。进行两种评分系统的不同组间比较;进行两种评分系统与住院期间需要行机械通气的可能性及疾病转归的相关性分析;评估入院时两种评分系统对住院期间需要行机械通气的可能性及死亡发生风险的预测价值。结果①AECOPD无机械通气组患者两种评分均明显低于机械通气组[APACHEⅡ分别为(12.09±3.48)分、(18.74±4.06)分,CAPS分别为(18.70±5.70)分、(26.35±7.87)分,P<0.05];②AECOPD存活组患者两种评分均明显低于死亡组[APACHEⅡ分别为(13.88±4.06)分、(20.86±4.43)分,CAPS分别为(19.66±5.37)分、(32.84±6.74)分,P<0.05];③Spearman相关分析显示,AECOPD患者APACHEⅡ评分、CAPS评分与住院期间需要行机械通气的可能性均呈显著相关(r值分别为0.694、0.525,P<0.05);④Spearman相关分析显示,AECOPD患者APACHEⅡ评分、CAPS评分与死亡发生风险均呈显著相关(r值分别为0.554、0.612,P<0.05)。结论AECOPD患者入院时APACHEⅡ评分及CAPS评分与病情严重程度及预后密切相关;对于评估患者病情严重程度、住院期间需要行机械通气的可能性,APACHEⅡ评分优于CAPS评分;两者对于AECOPD患者预后的预测价值基本相当,均具有较高的预测价值。     

APACHEⅢ评分用于重症监护病房脑损伤病人的临床评价

[目的]评估分析APACHE．Ⅲ评分系统对判断重症监护病房（ICU）脑损伤病人病情严重程度和预后的价值。[方法]收集整理128例ICU脑损伤危重症病人临床资料（存活组46例．死亡组82例），采用APAC脏Ⅲ评分系统评估脑损伤病人的严重程度和预后。[结果]脑损伤危重症病人存活组与死亡组入院24h内、72h的APACHEⅢ评分的得分越高，病情越重．预后越差。两组病死率比较，P〈0．01：将入院72hAPCHE Ⅲ评分〉60分作为预后凶险的判断指标，其灵敏度为92．7％，特异度为97．8％。[结论]APAC陬Ⅲ评分的分值与脑损伤病人病情严重程度和预后有关，作为评价医疗质量较客观的量化指标有实用价值。     

重症监护室患者的焦虑状况与急性生理和慢性健康状况评估Ⅱ评分的相关性

目的:探讨重症监护室(ICU)患者的焦虑状况与急性生理和慢性健康状况评估(APACHE)Ⅱ评分的相关性。方法:纳入ICU患者150例,采用医院焦虑抑郁量表(HADS)对患者进行测评。分别根据性别、年龄、住院费用报销方式、病房类型、是否机械通气及APACHEⅡ评分分组,比较不同组别患者的HADS评分,并分析HADS焦虑总分与APACHEⅡ评分的相关性。结果:性别、年龄、报销方式、机械通气、APACHEⅡ评分均与患者焦虑状态有关,APACHEⅡ评分与ICU患者焦虑程度成正相关。结论:ICU患者焦虑情绪与多因素有关,其焦虑情绪可以加重患者病情及影响患者预后。     

危重病人评分在ICU护理人力资源分配中的应用

[目的]探讨利用急性生理学及慢性健康状况评分Ⅱ(APACHEⅡ)评分系统指导临床科学分配护理人力资源的应用价值.[方法]将2008年5月-2009年4月入住重症监护病房(ICU)的340例病人按病床分为对照组与实验组.对照组根据主观判断病人的病情来分配护理人力资源;实验组每日对所有病人进行评分,根据评分科学分配护理人力资源;比较两组护理质量、并发症发生率、抢救成功率、病人满意度、入住ICU平均时间.[结果]实验组在护理质量、并发症发生率、抢救成功率、病人满意度、入住ICU平均时间等方面与对照组相比,差异有统计学意义(P＜0.05或P＜0.01).[结论]应用APACHEⅡ评分进行护理人力资源分配科学、实用.     

Renal failure in the respiratory intensive care unit.

The development of renal failure during respiratory failure is of grave prognostic significance. In 686 patients with respiratory failure, 74 developed renal failure; these had a mortality of 80%. The leading predisposing factors are: 1) gastrointestinal bleeding with hypovolemic shock; 2) sepsis with shock; 3) drug induced nephrotoxicity; and 4) hypotension. With antacid gastric neutralization, judicious use of nephrotoxic antibiotics, the incidence of renal failure can be reduced. Once renal failure occurs, early dialysis may increase the chances of recovery in these critically ill patients.     

Nosocomial infections in a respiratory intensive care unit

A total of 250 consecutive admissions to an open-plan respiratory ICU were analyzed prospectively to identify the incidence of secondary hospital-acquired infections and possible predisposing factors. Despite preventative measures and a restricted antibiotic policy, 23.6% of patients developed secondary infections. Patients admitted after multiple trauma were the only diagnostic category of patients who showed a significantly increased incidence of secondary infections. The length of hospitalization and number of patients who had intubations or tracheostomies was higher in the group with secondary infection; the causal relationship was difficult to establish. Patients who were not intubated or tracheostomized did not develop secondary infection. Prior administration of antibiotics did not appear to influence the incidence of secondary infection. There was a significant increase in secondary infections in patients with a higher therapeutic intervention scoring system score. The predominant pathogens cultured were highly resistant Gram-negative organisms, particularly Acinetobacter sp. and Pseudomonas sp. Staphylococcus aureus was the most common Gram-positive pathogen. The ICU course was probably prolonged by the complication of nosocomial infection, which may have contributed to the deaths.     

Recent innovations in intensive care unit risk-prediction models

During the past 20 years, ICU risk-prediction models have undergone significant development, validation, and refinement. Among the general ICU severity of illness scoring systems, the Acute Physiology and Chronic Health Evaluation (APACHE), Mortality Prediction Model (MPM), and the Simplified Acute Physiology Score (SAPS) have become the most accepted and used. To risk-adjust patients with longer, more severe illnesses like sepsis and acute respiratory distress syndrome, several models of organ dysfunction or failure have become available, including the Multiple Organ Dysfunction Score (MODS), the Sequential Organ Failure Assessment (SOFA), and the Logistic Organ Dysfunction Score (LODS). Recent innovations in risk adjustment include automatic physiology and diagnostic variable retrieval and the use of artificial intelligence. These innovations have the potential of extending the uses of case-mix and severity-of-illness adjustment in the areas of clinical research, patient care, and administration. The challenges facing intensivists in the next few years are to further develop these models so that they can be used throughout the IUC stay to assess quality of care and to extend them to more specific patient groups such as the elderly and patients with chronic ICU courses.     

A paediatric respiratory intensive care unit in Lagos.

The respiratory Intensive Care Unit was created at the Lagos University Teaching Hospital in 1963. Experience shows that mortality has been highest in neonates who had congenital anomalies, as well as in children under 2 years of age. The predominant cause of death was preventable respiratory failure. The incidence of mortality was 43 percent. This was related to several factors: (i) the severity of illness, types of illness and antecedent period of neglect; (ii) lack of a critical care medicine programme; (iii) insufficient skilled full-time intensive care personnel, including physicians, nurses, physiotherapists and paramedical specialists; (iv) the high incidence of infection in the Intensive Care Unit.     

Mortality predictions in the intensive care unit: comparing physicians with scoring systems

OBJECTIVE: Risk-prediction models offer potential advantages over physician predictions of outcomes in the intensive care unit (ICU). Our systematic review compared the accuracy of ICU physicians' and scoring system predictions of ICU or hospital mortality of critically ill adults. DATA SOURCE: MEDLINE (1966-2005), CINAHL (1982-2005), Ovid Healthstar (1975-2004), EMBASE (1980-2005), SciSearch (1980-2005), PsychLit (1985-2004), the Cochrane Library (Issue 1, 2005), PubMed "related articles," personal files, abstract proceedings, and reference lists. STUDY SELECTION: We considered all studies that compared physician predictions of ICU or hospital survival of critically ill adults to an objective scoring system, computer model, or prediction rule. We excluded studies if they focused exclusively on the development or economic evaluation of a scoring system, computer model, or prediction rule. DATA EXTRACTION AND ANALYSIS: We independently abstracted data and assessed study quality in duplicate. We determined summary receiver operating characteristic curves and areas under the summary receiver operating characteristic curves+/-se and summary diagnostic odds ratios. DATA SYNTHESIS: We included 12 observational studies of moderate methodological quality. The area under the summary receiver operating characteristic curves for seven studies was 0.85+/-0.03 for physician predictions compared with 0.63+/-0.06 for scoring system predictions (p=.002). Physicians' summary diagnostic odds ratios derived from the area under the summary receiver operating characteristic curves were significantly higher (12.43; 95% confidence interval 5.47, 27.11) than scoring systems' summary diagnostic odds ratios (2.25; 95% confidence interval 0.78, 6.52, p=.001). Combined results of all 12 studies indicated that physicians predict mortality more accurately than do scoring systems: ratio of diagnostic odds ratios (95% confidence interval) 1.92 (1.19, 3.08) (p=.007). CONCLUSIONS: Observational studies suggest that ICU physicians discriminate between survivors and nonsurvivors more accurately than do scoring systems in the first 24 hrs of ICU admission. The overall accuracy of both predictions of patient mortality was moderate, implying limited usefulness of outcome prediction in the first 24 hrs for clinical decision making.     

RICU呼吸机安全性目标管理

目的探讨呼吸机安全性目标管理方法。方法制定呼吸机安全性管理制度;建立呼吸机档案资料;由专人管理;加强呼吸机使用培训;做好用电安全管理;防止交叉感染。结果无一例因呼吸机管理和使用不当引发投诉;未发生因呼吸机使用与操作不当造成的损坏现象。结论呼吸机安全性目标管理的实施,提高了呼吸机使用过程中的安全性及可靠性。     

Predicting mortality in intensive care unit survivors using a subjective scoring system

Most prognostic models rely on variables recorded within 24 hours of admission to predict the mortality rate of patients in the intensive care unit (ICU). Although a significant number of patients die after discharge from the ICU, there is a paucity of data related to predicting hospital mortality based on information obtained at ICU discharge. It is likely that experienced intensivists may be able to predict the likelihood of hospital death at ICU discharge accurately if they incorporate patients' age, preferences regarding life support, comorbidities, prehospital quality of life, and clinical course in the ICU into their prediction. However, if it is to be generalizable and reproducible and to perform well without bias, then a good prediction model should be based on objectively defined variables.     

呼吸监护病区金黄色葡萄球菌耐药性监测(附21株资料分析)

目的：对呼吸监护病区（ＲＩＣＵ）分离的２１株金黄色葡萄球菌（金葡菌）进行耐药性监测，方法；药敏试验采用纸片扩散法，用色原头孢菌素（ｎｉｔｒｏｃｅｆｉｎ）纸片法检测内酰胺酶，结果：ＲＩＣＵ分离的金葡菌高于普通病房，检出耐甲氧西林金葡菌（ＭＲＳＡ）１７株，ＭＲＳＡ有１２株产内酰胺酶，结论：金葡菌产酶株与非产朱的耐药相比有差别，万古霉素是唯一对金葡菌完全敏感的抗菌药物。