The Effectiveness of Four Intervention Methods for Preventing Inadvertent Perioperative Hypothermia During Total Knee or Total Hip Arthroplasty

Desenvolvimento de protocolo clínico assistencial para prevenção e tratamento da hipotermia perioperatória

Objetivo: desenvolver um protocolo de prevenção e tratamento da hipotermia perioperatória. Método: pesquisa do tipo desenvolvimento tecnológico em saúde, desenvolvida em três etapas: Revisão de diretrizes clínicas sobre fatores de risco para desenvolvimento de hipotermia perioperatória; Identificação da ocorrência de hipotermia perioperatória e dos fatores de risco associados ao seu desenvolvimento em um centro cirúrgico e Elaboração do protocolo de prevenção de hipotermia perioperatória. Resultados: os fatores de risco identificados nas diretrizes foram categorizados em características clínicas (idade, Índice de Massa Corporal, comorbidades, temperatura corporal) e anestésico-cirúrgicas (tipo e duração da anestesia e cirurgia, temperatura da sala cirúrgica). Na segunda etapa, 90 pacientes cirúrgicos foram avaliados. A ocorrência de hipotermia foi de 28,9% na admissão cirúrgica, 77,8% na admissão da Sala de Recuperação Pós-Anestésica e 45,6% alta do centro cirúrgico. Houve associação estatisticamente significativa entre ocorrência de hipotermia e índice ASA (p=0,049), idade (p=0,037), comorbidades (p=0,031), hipotermia pré-operatória (p=0,015). Conclusão: para elaboração do protocolo foram considerados os fatores de risco descritos na literatura, os resultados de estudo local e acesso às tecnologias disponíveis na instituição. As ações incluíram avaliação de fatores de risco e de situações desencadeantes, monitorização e registro da temperatura e outros parâmetros, aquecimento passivo para pacientes normotérmicos, aquecimento ativo para pacientes hipotérmicos, infusão de soluções endovenosas aquecidas e suporte de oxigênio para pacientes hipotérmicos.

Construction and validation of postoperative hypothermia prediction model for patients undergoing joint replacement surgery

AIM

To construct and validate a postoperative hypothermia prediction model for patients undergoing joint replacement surgery.

BACKGROUND

Postoperative hypothermia is one of the harmful perioperative complications in patients undergoing joint replacement surgery. The previous studies mainly focused on intraoperative hypothermia prediction models. The prediction model for postoperative hypothermia in patients with joint replacement surgery was understudied.

DESIGN

Cohort study.

METHODS

We collected data from 503 participants undergoing joint replacement surgery in a tertiary hospital from January 2019 to December 2021. Of those, 404 cases were assigned to the modelling and 99 to the validation groups. Logistic regression was used to construct the model. The AUC was used to test the predictive effect of the model. Finally, 99 cases were used to verify the application effect of the model. A TRIPOD checklist was used to guide the reporting of this study.

RESULTS

The factors entered into the prediction model were age, intraoperative hypothermia, BMI, heat preservation measures and platelet (PLT). The model was constructed as follows: Logit (P) = .537 + 3.669 × 1 (intraoperative hypothermia) + .030 × age - .289 × BMI + 2.857 × 1 (intraoperative insulation measures) + .003 × PLT. Hosmer-Lemeshow test, p = .608, the area under the receiver operating characteristic curve (AUC) was .861. The Youden index was .530, the sensitivity was .599 and the specificity was .93. The incidence of postoperative hypothermia in the modelling group was 42.93% (173/404), and that in the verification group was 43.43% (43/99), χ2 = .012, p = .912. The correct practical application rate was 87.88%. This model has a good application effect.

CONCLUSION

The current prediction model provided a reference for clinical screening of patients with high-risk hypothermia after joint replacement surgery.

RELEVANCE TO CLINICAL PRACTICE

Clinical nurses can use the developed prediction model to predict the occurrence of postoperative hypothermia and provide a reference for the preventive measure.

Implementation of multi-mode nursing insulation program for patients receiving surgery for spine tumor: a propensity score-matched analysis

BACKGROUND

Spinal tumor surgery usually involved long operation time, large area of soft tissue resection and long wound, and was prone to hypothermia during the operation. Therefore, actively promoting insulation and optimizing the intraoperative insulation program have great potential in reducing the incidence of hypothermia and reducing the incidence of postoperative complications. In this study, we compared patients who did not implement multi-mode nursing insulation program (MNIP) with those who implemented MNIP, observing and comparing clinical outcomes, and complications in both groups, with the aim of developing an optimal management plan for the preoperative, intraoperative, and postoperative periods, respectively.

METHODS

We selected 2 periods of 1 year, before (n = 120 patients) and after MINP implementation (n = 120 patients). Data were collected on patient demographics, operative, perioperative details, temperature changes, anesthesia recovery effect, incidence of postoperative wound infection, length of hospital stay and complications. PS analyses were used for dealing with confounding bias in this retrospective observational study.

RESULTS

After PS matching, the outcomes of 120 well-balanced pairs of patients were compared (No-MNIP vs MNIP). There was no significant difference concerning the satisfaction survey. The results indicated that the MNIP had better insulation effect at 90 min, 120 min, 150 min after anesthesia induction and after surgery. There were 16 cases of complications in the No-MNIP group and 5 cases in the MNIP group postoperative, which have significant statistical difference.

CONCLUSION

In this study, the incidence of intraoperative hypothermia was effectively reduced by adopting the multi-mode insulation scheme, thus reducing the incidence of incision infection and shortening the length of hospital stay of patients.

Analysis of the Risk Factors for the Onset of Postoperative Hypothermia in the Postanesthesia Care Unit

PURPOSE

Recent studies on hypothermia typically focused on a single anesthesia method or a particular surgical procedure. Although there are multiple risk factors leading to hypothermia, such as the use of cold solutions or nonhumidified and nonheated anesthetic gases, few studies have reported the incidence of postoperative hypothermia among patients in the postanesthesia care unit (PACU).

DESIGN

This is a retrospective analysis of patients who underwent surgery and were admitted to the PACU immediately after surgery at the Fourth Affiliated Hospital, College of Medicine, Zhejiang University, from September 2018 to March 2019.

METHODS

Patient data were collected and analyzed in two groups to understand the factors affecting the occurrence of hypothermia. Hypothermia was defined as a core temperature of less than 36°C. On the basis of body temperature, patients in the PACU were divided into hypothermic and nonhypothermic groups. Factors influencing hypothermia were studied by the univariate method, followed by logistic regression analysis to identify the risk factors for hypothermia onset.

FINDINGS

Of a total of 1,788 patients were enrolled in the study, 113 (6.32%) exhibited hypothermia (<36°C) in the PACU. The hypothermic and nonhypothermic groups displayed significant differences (P < .05) in the anesthesia method used as well as the American Society of Anesthesiologists physical classification status. The body temperature at the time the patients were admitted to the operating room influenced the occurrence of postoperative hypothermia (P < .01). These parameters were recognized as independent risk factors for postoperative hypothermia in the PACU.

CONCLUSIONS

Significant risk factors for the onset of hypothermia were general anesthesia and higher American Society of Anesthesiologists grade. However, epidural anesthesia was found to have a protective effect.