Sirirat Mueankwan

Mrs. Sirirat Mueankwan

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 December 2018 in Aging & Mental Health
Verified
Journal Article
Closed access
MBMukda Banjongrewadee
Mukda Banjongrewadee
Nahathai WongpakaranNahathai Wongpakaran
Nahathai Wongpakaran
Tinakon WongpakaranTinakon Wongpakaran
Tinakon Wongpakaran
TPTanyong Pipanmekaporn
Tanyong Pipanmekaporn
YPYodying Punjasawadwong
Yodying Punjasawadwong
SMSirirat Mueankwan
Sirirat Mueankwan
Objectives: This study examined levels of perceived stress (PS), postoperative delirium (POD) and associated factors among Thai elderly patients undergoing elective noncardiac surgery. Background and aims: Preoperative PS and change after operation have not been widely studied. Moreover, psychological factors associated with PS and POD has been poorly investigated. Materials and Methods: In total, 429 elderly patients were recruited at a university hospital. The preoperative evaluation included sociodemographic data, health behaviors at risk, Perceived Stress Scale (PSS-10), Neuroticism Inventory (NI), Mental State Examination T10 (MSET10), Montreal Cognitive Assessment (MoCA) and Geriatric Depression Scale (GDS-15). Three-day postoperative evaluation included PSS-10 and Confusion Assessment Method Algorithm (CAM) or CAM-ICU for Delirium. Multiple regression and logistic regression analysis were performed to determine potential predictors. Results: Females were 58.97%, and the mean age was 69.93 ± 6.87 years. Mean pre- and postoperative PS were 12.77 ± 5.41 and 13.39 ± 5.26, respectively (P < 0.05). Multiple regression revealed that neuroticism, depression, and BMI predicted PS significantly. None of the independent variables was found to predict postoperative PS except for preoperative PS (p <.001). POD at the recovery room was predicted by preoperative PS (odds ratio = 1.181, 95% CI = 1.019–1.369), whereas overall POD was predicted by MoCA (odds ratio = .864, 95% CI = .771 -.968). Conclusion: Preoperative PS was significant in that it was associated with postoperative PS and POD. A careful assessment of preoperative PS as well as providing brief interventions for patients with high levels of this condition may reduce the risk of POD.

27 October 2020 in Perspectives in Psychiatric Care
Verified
Journal Article
Closed access
PDF file
TPTanyong Pipanmekaporn
Tanyong Pipanmekaporn
YPYodying Punjasawadwong
Yodying Punjasawadwong
Nahathai WongpakaranNahathai Wongpakaran
Nahathai Wongpakaran
Tinakon WongpakaranTinakon Wongpakaran
Tinakon Wongpakaran
KSKittinan Suwannachai
Kittinan Suwannachai
SMSirirat Mueankwan
Sirirat Mueankwan

Verified
Journal Article
Open access
PDF file
SMSirirat Mueankwan
Sirirat Mueankwan
KTKonlawij Trongtrakul
Konlawij Trongtrakul
PTPattraporn Tajarernmuang
Pattraporn Tajarernmuang
NNNutchanok Niyatiwatchanchai
Nutchanok Niyatiwatchanchai
Prit KusirisinPrit Kusirisin
Prit Kusirisin
PNPhoom Narongkiatikhun
Phoom Narongkiatikhun
Background/Objectives: Hemoperfusion (HP) is employed to modulate cytokine storms in severe coronavirus disease 2019 (COVID-19) patients, requiring careful attention for success and safety. Therefore, we investigated whether our care bundles could enhance HP performance. Methods: We conducted a retrospective cohort study on adult patients (≥20 years old) with severe COVID-19 pneumonia. In the first wave (Phase I), we identified HP-related issues and addressed them with care bundles in the second wave (Phase II). The care bundles included early temperature control, precise hemodynamic monitoring, and clot prevention measures for the HP membrane. The HP success rate and associated adverse events (AEs) were assessed between the two phases. Results: The study included 60 HP (HA330) sessions from 27 cases (Phase I: 21 sessions from 9 cases; Phase II: 39 sessions from 18 cases). Patient characteristics and treatments for COVID-19 were similar, except for baseline body temperature (BT) and heart rate (HR). Phase II showed a higher success rate (67% vs. 89%, p = 0.19), although it did not reach statistical significance. Phase I recorded a significantly higher frequency of AEs (3 [IQR 1, 4] events/case vs. 1 [IQR 0, 2] events/case, p = 0.014). After implementing the care bundles, hypothermia significantly decreased (78% vs. 33%, p = 0.037), with an adjusted odds ratio of 0.15; 95% CI 0.02–0.95, p = 0.044 for baseline BT. Conclusions: Further exploration with a larger sample size is required to establish the advantages of care bundles. However, the bundles’ implementation has significantly improved hypothermia prevention.