重症监护病房患者多重耐药鲍曼不动杆菌感染及病死危险因素分析

目的 探讨重症监护病房患者多重耐药鲍曼不动杆菌（MDRAb）感染的危险因素及MDRAb感染患者病死的危险因素,为防治MDRAb提供依据。方法 回顾性分析2014年1月至2017年10月遂宁市中心医院重症监护病房197例鲍曼不动杆菌（Ab）感染患者,采用病例对照研究,根据抗生素敏感实验结果,将111例MDRAb感染者作为病例组,86例非MDRAb感染者作为对照组,收集其人口学资料、感染前的临床资料和实验室数据,应用单因素分析及多因素Logistic回归分析其感染的危险因素。同时将病例组分为病死组与存活组,分析其病死危险因素。结果 MDRAb检出率为56.35%。单因素Logistic分析显示,ICU停留时间、使用抗生素＞7 d、使用喹诺酮类抗生素、有创通气和胃管插管可能是MDRAb感染的危险因素（P＜0.05）。多因素Logistic回归分析显示,使用抗生素＞7 d（OR=2.338,95%CI：1.252~4.368）、使用喹诺酮类抗生素（OR=3.703,95%CI：1.665~8.234）、有创通气（OR=4.356,95%CI：1.695~11.192）是MDRAb感染的独立危险因素。单因素Logistic分析显示,年龄、高血压、血红蛋白量、昏迷可能是MDRAb感染患者病死的危险因素。多因素Logistic回归分析显示,高血压（OR=5.185,95%CI：2.012~13.361）、血红蛋白量（OR=0.976,95%CI：0.957~0.996）和昏迷（OR=4.061,95%CI：1.517~10.873）是MDRAb感染患者病死的独立危险因素。结论 使用抗生素＞7 d、使用喹诺酮类抗生素、有创通气是MDRAb感染的独立危险因素;高血压、血红蛋白量、昏迷是MDRAb感染患者病死的危险因素。     

Validation of a glucose meter at an intensive care unit

IntroductionHyperglycemic patients admitted to Intensive care units (ICUs) have higher morbidity and mortality than normoglycemic patients. Blood glucose levels of ICU patients are usually measured with a glucose meter. The aim of this study was to evaluate a glucose meter (StatStrip, Nova Biomedical) to assess its agreement with the standard laboratory method for testing glucose.Material and methodsEighty-nine different samples were collected from patients (76.4% men and 23.6% women) admitted to an ICU from September to December 2010. Each blood sample was collected into two tubes, a lithium heparin tube and an EDTA tube. The total blood aliquot was used to measure glycemia using the glucose meter. The lithium heparin tube was processed at the same time for measuring plasma glucose (Cobas 6000 Analyzer, Roche Diagnostics, SA). Agreement between the two methods was assessed according to the EP-9-A2 Clinical Laboratory Standards Institute guideline.ResultsMean whole blood glucose level measured by the glucose meter was 126.53 + 49.28 mg/dL (range, 33.5-431 mg/dL), while mean plasma glucose value measured by the laboratory reference method was 138.13 + 78.6 mg/dL (range, 43-451 mg/dL). Correlation coefficient was 0.99, with a 95% confidence interval of 0.98 to 0.99. Coefficient of determination (R2) was 0.97, and intraclass correlation coefficient was 0.99 with a 95% CI of 0.98 to 0.99.ConclusionsThe tested glucose meter (StatStrip) shows a good linear association, precision, and accuracy when compared to the laboratory reference method. This device is adequate for glucose monitoring.     

Diaphragm muscle weakness in an experimental porcine intensive care unit model

In critically ill patients, mechanisms underlying diaphragm muscle remodeling and resultant dysfunction contributing to weaning failure remain unclear. Ventilator-induced modifications as well as sepsis and administration of pharmacological agents such as corticosteroids and neuromuscular blocking agents may be involved. Thus, the objective of the present study was to examine how sepsis, systemic corticosteroid treatment (CS) and neuromuscular blocking agent administration (NMBA) aggravate ventilator-related diaphragm cell and molecular dysfunction in the intensive care unit. Piglets were exposed to different combinations of mechanical ventilation and sedation, endotoxin-induced sepsis, CS and NMBA for five days and compared with sham-operated control animals. On day 5, diaphragm muscle fibre structure (myosin heavy chain isoform proportion, cross-sectional area and contractile protein content) did not differ from controls in any of the mechanically ventilated animals. However, a decrease in single fibre maximal force normalized to cross-sectional area (specific force) was observed in all experimental piglets. Therefore, exposure to mechanical ventilation and sedation for five days has a key negative impact on diaphragm contractile function despite a preservation of muscle structure. Post-translational modifications of contractile proteins are forwarded as one probable underlying mechanism. Unexpectedly, sepsis, CS or NMBA have no significant additive effects, suggesting that mechanical ventilation and sedation are the triggering factors leading to diaphragm weakness in the intensive care unit.     

重症监护病房革兰阴性杆菌耐药性分析

目的了解深圳市人民医院重症监护病房(ICU)革兰阴性杆菌的分布及其耐药性,指导临床合理用药。方法收集来自重症监护病房各类标本分离的革兰阴性杆菌540株,用VITEK AMS-60或VITEK-Ⅱ全自动微生物分析仪进行菌种鉴定,用K-B法进行药敏试验。结果ICU检出的革兰阴性杆菌以鲍曼不动杆菌、大肠埃希菌、铜绿假单胞菌和肺炎克雷伯菌为主,ESBLs阳性的大肠埃希菌和肺炎克雷伯菌比例为61.6%和51.8%,各类细菌对常用抗菌药物表现为严重耐药和多重耐药。结论该院ICU检出的革兰阴性杆菌以鲍曼不动杆菌、大肠埃希菌、铜绿假单胞菌和肺炎克雷伯菌为主,且呈现多重耐药性。     

Intensive care unit admission parameters improve the accuracy of operative mortality predictive models in cardiac surgery

Background

Operative mortality risk in cardiac surgery is usually assessed using preoperative risk models. However, intraoperative factors may change the risk profile of the patients, and parameters at the admission in the intensive care unit may be relevant in determining the operative mortality. This study investigates the association between a number of parameters at the admission in the intensive care unit and the operative mortality, and verifies the hypothesis that including these parameters into the preoperative risk models may increase the accuracy of prediction of the operative mortality.

Methodology

929 adult patients who underwent cardiac surgery were admitted to the study. The preoperative risk profile was assessed using the logistic EuroSCORE and the ACEF score. A number of parameters recorded at the admission in the intensive care unit were explored for univariate and multivariable association with the operative mortality.

Principal Findings

A heart rate higher than 120 beats per minute and a blood lactate value higher than 4 mmol/L at the admission in the intensive care unit were independent predictors of operative mortality, with odds ratio of 6.7 and 13.4 respectively. Including these parameters into the logistic EuroSCORE and the ACEF score increased their accuracy (area under the curve 0.85 to 0.88 for the logistic EuroSCORE and 0.81 to 0.86 for the ACEF score).

Conclusions

A double-stage assessment of operative mortality risk provides a higher accuracy of the prediction. Elevated blood lactates and tachycardia reflect a condition of inadequate cardiac output. Their inclusion in the assessment of the severity of the clinical conditions after cardiac surgery may offer a useful tool to introduce more sophisticated hemodynamic monitoring techniques. Comparison between the predicted operative mortality risk before and after the operation may offer an assessment of the operative performance.     

Molecular typing of Staphylococcus aureus isolates from an intensive care unit

Seventeen S. aureus clinical isolates, collected from an Intensive Care Unit (ICU) during a seven-month period were analyzed to investigate their antimicrobial susceptibility and clonal diversity. Eleven isolates (65%) were found to be resistant to methicillin (MRSA). Pulsed-field gel electrophoresis (PFGE) profiles of genomic DNAs, and analysis of the polymorphisms of the variable regions of the protein A (spa) and coagulase (coa) genes revealed a lower clonal heterogeneity among MRSA than among methicillin-susceptible isolates (MSSA). Two of the MRSA clones were repeatedly isolated in different patients, within a variable period of time, suggesting the presence in the ward of a resident, endemic and multi-drug resistant MRSA population. Our results also emphasize the lower discriminatory power of spa and coa typing compared with PFGE typing.     

Hypothermia in a surgical intensive care unit

Background

Inadvertent hypothermia is not uncommon in the immediate postoperative period and it is associated with impairment and abnormalities in various organs and systems that can lead to adverse outcomes. The aim of this study was to estimate the prevalence, the predictive factors and outcome of core hypothermia on admission to a surgical ICU.

Methods

All consecutive 185 adult patients who underwent scheduled or emergency noncardiac surgery admitted to a surgical ICU between April and July 2004 were admitted to the study. Tympanic membrane core temperature (Tc) was measured before surgery, on arrival at ICU and every two hours until 6 hours after admission. The following variables were also recorded: age, sex, body weight and height, ASA physical status, type of surgery, magnitude of surgical procedure, anesthesia technique, amount of intravenous fluids administered during anesthesia, use of temperature monitoring and warming techniques, duration of the anesthesia, ICU length of stay, hospital length of stay and SAPS II score. Patients were classified as either hypothermic (Tc ≤ 35°C) or normothermic (Tc> 35°C). Univariate analysis and multiple regression binary logistic with an odds ratio (OR) and its 95% Confidence Interval (95%CI) were used to compare the two groups of patients and assess the relationship between each clinical predictor and hypothermia. Outcome measured as ICU length of stay and mortality was also assessed.

Results

Prevalence of hypothermia on ICU admission was 57.8%. In univariate analysis temperature monitoring, use of warming techniques and higher previous body temperature were significant protective factors against core hypothermia. In this analysis independent predictors of hypothermia on admission to ICU were: magnitude of surgery, use of general anesthesia or combined epidural and general anesthesia, total intravenous crystalloids administrated and total packed erythrocytes administrated, anesthesia longer than 3 hours and SAPS II scores. In multiple logistic regression analysis significant predictors of hypothermia on admission to the ICU were magnitude of surgery (OR 3.9, 95% CI, 1.4–10.6, p = 0.008 for major surgery; OR 3.6, 95% CI, 1.5–9.0, p = 0.005 for medium surgery), intravenous administration of crystalloids (in litres) (OR 1.4, 95% CI, 1.1–1.7, p = 0.012) and SAPS score (OR 1.0, 95% CI 1.0–1.7, p = 0.014); higher previous temperature in ward was a significant protective factor (OR 0.3, 95% CI 0.1–0.7, p = 0.003). Hypothermia was neither a risk factor for hospital mortality nor a predictive factor for staying longer in ICU.

Conclusion

The prevalence of patient hypothermia on ICU arrival was high. Hypothermia at time of admission to the ICU was not an independent factor for mortality or for staying longer in ICU.     

Reflections on neonatal intensive care unit

This article reflects on twelve years spent on a regional neonatal intensive care unit (NICU). The trials and tribulations experienced by parents and staff alike are described together with some of the initiatives developed to mitigate the effects of these. High standards of medical and nursing care, environmental conditions, good communications and a multi-disciplinary approach are all identified as crucial in giving holistic care to the neonate. Finally, the involvement of the professional team is recognised as transient but key in developing in the parents both competence and confidence in their roles for the future.     

Reduction in mortality after inappropriate early discharge from intensive care unit: logistic regression triage model

ObjectiveTo develop a predictive model to triage patients for discharge from intensive care units to reduce mortality after discharge.DesignLogistic regression analyses and modelling of data from patients who were discharged from intensive care units.SettingGuy''s hospital intensive care unit and 19 other UK intensive care units from 1989 to 1998.Participants5475 patients for the development of the model and 8449 for validation.ResultsMortality after discharge from intensive care was up to 12.4%. The triage model identified patients at risk from death on the ward with a sensitivity of 65.5% and specificity of 87.6%, and an area under the receiver operating curve of 0.86. Variables in the model were age, end stage disease, length of stay in unit, cardiothoracic surgery, and physiology. In the validation dataset the 34% of the patients identified as at risk had a discharge mortality of 25% compared with a 4% mortality among those not at risk.ConclusionsThe discharge mortality of at risk patients may be reduced by 39% if they remain in intensive care units for another 48 hours. The discharge triage model to identify patients at risk from too early and inappropriate discharge from intensive care may help doctors to make the difficult clinical decision of whom to discharge to make room for a patient requiring urgent admission to the unit. If confirmed, this study has implications on the provision of resources.

What is already known on this topic

In the United Kingdom, the mortality of patients who die on the ward after discharge from intensive care is unacceptably high (9% to 27%)Indirect evidence has shown that this is due to too early and inappropriate discharge from intensive care that has increased over the past 10 years

What this study adds

A triage model identifies patients at risk from inappropriate discharge from intensive careMortality after discharge from intensive care may be reduced by 39% if these patients were to stay in intensive care for another 48 hoursAn estimated 16% more beds are required if mortality after discharge from intensive care is to be reduced     

Genetic variety of Acinetobacter baumannii in an intensive care unit for burn patients

The genetic structure of A. baumannii hospital isolates, formed in the course of 2002 - 2004 in an intensive care unit for burn patients (St. Petersburg) was studied. The prolonged circulation of only some clonal strains was shown, 35% of the isolates belonged to dominating strains. Phenotypically, all cultures were characterized by resistance to the preparations of the cephalosporin row and gentamicin. The presence of class 1 integron with variable segment sized 2.5 kbp was found in the genotype of four isolates with the use the polymerase chain reaction. The restriction analysis revealed its similarity with integron, detected earlier (in 1989 - 2001 ) in A. baumannii in European hospitals abroad.     

Repertoire of intensive care unit pneumonia microbiota

Despite the considerable number of studies reported to date, the causative agents of pneumonia are not completely identified. We comprehensively applied modern and traditional laboratory diagnostic techniques to identify microbiota in patients who were admitted to or developed pneumonia in intensive care units (ICUs). During a three-year period, we tested the bronchoalveolar lavage (BAL) of patients with ventilator-associated pneumonia, community-acquired pneumonia, non-ventilator ICU pneumonia and aspiration pneumonia, and compared the results with those from patients without pneumonia (controls). Samples were tested by amplification of 16S rDNA, 18S rDNA genes followed by cloning and sequencing and by PCR to target specific pathogens. We also included culture, amoeba co-culture, detection of antibodies to selected agents and urinary antigen tests. Based on molecular testing, we identified a wide repertoire of 160 bacterial species of which 73 have not been previously reported in pneumonia. Moreover, we found 37 putative new bacterial phylotypes with a 16S rDNA gene divergence ≥ 98% from known phylotypes. We also identified 24 fungal species of which 6 have not been previously reported in pneumonia and 7 viruses. Patients can present up to 16 different microorganisms in a single BAL (mean ± SD; 3.77 ± 2.93). Some pathogens considered to be typical for ICU pneumonia such as Pseudomonas aeruginosa and Streptococcus species can be detected as commonly in controls as in pneumonia patients which strikingly highlights the existence of a core pulmonary microbiota. Differences in the microbiota of different forms of pneumonia were documented.