| Literature DB >> 35070469 |
Nipin Kalal1, Suresh K Sharma1, Kapil Soni2.
Abstract
BACKGROUND: The COVID-19 pandemic is a serious global health threat and it has numerous impacts on human life. India faced the problem of the second wave of COVID-19 and an unexpected new predicament in the form of mucormycosis has been added. The use of steroids drugs for long duration and comorbidity with COVID-19 infections are the risk factors of mucormycosis. It is important to understand the postoperative clinical pathway to assess and determine the policy and protocol, which help patients fasten their recovery, prevent further complications and readmission.Entities:
Keywords: COVID-19; Clinical pathway; Nursing care; Postoperative care; Postoperative recovery assessment
Year: 2021 PMID: 35070469 PMCID: PMC8730340 DOI: 10.3126/nje.v11i4.40498
Source DB: PubMed Journal: Nepal J Epidemiol
Frequency and percentage distribution of demographic variables (n = 90)
| Variables | Frequency (%) | |
|---|---|---|
|
| ||
|
| 46 (51.1) | |
|
| 44 (48.9) | |
|
| ||
|
| 57 (63.3) | |
|
| 33 (36.7) | |
|
| ||
|
| 46 (51.1) | |
|
| 44 (48.9) | |
|
| ||
|
| 21 (23.3) | |
|
| 35 (38.9) | |
|
| 34 (37.8) | |
|
| ||
|
| 01 (1.1) | |
|
| 89 (98.9) | |
|
| ||
|
| 31 (34.4) | |
|
| 59 (65.6) | |
|
| ||
|
| 71 (78.9) | |
|
| 19 (21.1) | |
|
| ||
|
| 53 (58.9) | |
|
| 37 (41.1) | |
|
| ||
|
| 65 (72.2) | |
|
| 25 (27.8) | |
|
| ||
|
| 33 (36.7) | |
|
| 57 (63.3) | |
|
| ||
|
| 58 (64.44) | |
|
| 32 (35.56) | |
|
| 1st Dose | 2nd Dose |
|
| 2 (2.22) | 3(3.33) |
|
| 17 (18.88) | 10(11.11) |
|
| ||
|
| 46 (51.11) | |
|
| 11 (12.22) | |
|
| 01 (1.11) | |
|
| 01 (1.11) | |
Table 2: Day-wise mean score of participants
| Clinical Recovery Domains | Day-1 | Day-2 | Day-3 | Day-4 | Day-5 | Day-6 | Day-7 |
|---|---|---|---|---|---|---|---|
|
| 11.73 | 12.08 | 13.64 | 15.95 | 16.86 | 17.51 | 17.60 |
|
| 5.24 | 5.91 | 7.06 | 8.0 | 8.33 | 8.82 | 8.86 |
|
| 0.60 | 0.68 | 0.91 | 1.33 | 1.71 | 1.77 | 1.77 |
|
| 2.15 | 2.17 | 2.21 | 2.28 | 2.32 | 2.51 | 2.51 |
Domain wise mean and standard deviation of participants
| Clinical Recovery Domains | Score range | Mean±SD | Percentage |
|---|---|---|---|
|
| 0-20 | 15.05±2.34 | 75.25% |
|
| 0-10 | 7.46±1.32 | 74.60% |
|
| 0-6 | 1.25±0.48 | 20.83% |
|
| 0-4 | 2.30±0.13 | 57.50% |
Correlation between the Domains
| Correlations | ||||
|---|---|---|---|---|
| Domains | Physiological | Physical | Psychosocial | Medication status |
|
| .987** | .993** | .909** | |
|
| .987** | .970** | .892** | |
|
| .993** | .970** | .911** | |
|
| .909** | .892** | .911** | |
Association of Clinical Recovery Domains with demographic variables among participants
| Variables | Physiological | P value | Physical | P value | Psycho-social | P value | Medication status | P value |
|---|---|---|---|---|---|---|---|---|
|
| ||||||||
|
| 17.39 ±2.76 | .460 | 9.08±2.21 | .394 | 1.91±2.66 | .619 | 2.32±.70 | .021 |
|
| 17.81 ±2.68 | 8.63±2.75 | 1.63±2.59 | 2.70±.82 | ||||
|
| ||||||||
|
| 17.85±2.29 | .236 | 9.15±1.72 | .146 | 1.92±2.67 | .473 | 2.57±.82 | .282 |
|
| 17.15±3.31 | 8.36±3.40 | 1.51±2.55 | 2.39±.70 | ||||
|
| ||||||||
|
| 17.38±2.79 | .139 | 8.73±2.73 | .326 | 1.69±2.56 | .543 | 2.47±.79 | .453 |
|
| 18.42±2.26 | 9.36±1.16 | 2.10±2.86 | 2.63±.76 | ||||
|
| ||||||||
|
| 17.58±2.58 | .950 | 8.90±2.55 | .860 | 2.11±2.75 | .147 | 2.52±.82 | .805 |
|
| 17.62±2.93 | 8.81±2.42 | 1.29±2.36 | 2.48±.73 | ||||
|
| ||||||||
|
| 17.32±2.87 | 8.61±2.82 | .124 | 1.50±2.47 | .116 | 2.43±.74 | .117 | |
|
| 18.32±2.13 | .120 | 9.52±1.04 | 2.48±2.90 | 2.72±.84 | |||
|
| ||||||||
|
| 16.90±3.24 | .046 | 8.66±2.72 | .565 | 2.36±2.80 | .107 | 2.66±.85 | .152 |
|
| 18±2.29 | 8.98±2.36 | 1.43±2.47 | 2.42±.73 | ||||
|
| ||||||||
|
| 17.93±2.33 | .120 | 8.96±2.34 | .615 | 1.86±2.61 | .684 | 2.44±.72 | .308 |
|
| 17±2.25 | 8.68±2.76 | 1.62±2.66 | 2.62±.87 | ||||
*Significant (p< 0.05)